Wireless Avionics Packet to Support Fault Tolerance for Flight Applications

NASA Technical Reports Server (NTRS)

Block, Gary L.; Whitaker, William D.; Dillon, James W.; Lux, James P.; Ahmad, Mohammad

2009-01-01

In this protocol and packet format, data traffic is monitored by all network interfaces to determine the health of transmitter and subsystems. When failures are detected, the network inter face applies its recover y policies to provide continued service despite the presence of faults. The protocol, packet format, and inter face are independent of the data link technology used. The current demonstration system supports both commercial off-the-shelf wireless connections and wired Ethernet connections. Other technologies such as 1553 or serial data links can be used for the network backbone. The Wireless Avionics packet is divided into three parts: a header, a data payload, and a checksum. The header has the following components: magic number, version, quality of service, time to live, sending transceiver, function code, payload length, source Application Data Interface (ADI) address, destination ADI address, sending node address, target node address, and a sequence number. The magic number is used to identify WAV packets, and allows the packet format to be updated in the future. The quality of service field allows routing decisions to be made based on this value and can be used to route critical management data over a dedicated channel. The time to live value is used to discard misrouted packets while the source transceiver is updated at each hop. This information is used to monitor the health of each transceiver in the network. To identify the packet type, the function code is used. Besides having a regular data packet, the system supports diagnostic packets for fault detection and isolation. The payload length specifies the number of data bytes in the payload, and this supports variable-length packets in the network. The source ADI is the address of the originating interface. This can be used by the destination application to identify the originating source of the packet where the address consists of a subnet, subsystem class within the subnet, a subsystem unit, and the local ADI number. The destination ADI is used to route the packet to its ultimate destination. At each hop, the sending interface uses the destination address to determine the next node for the data. The sending node is the node address of the interface that is broadcasting the packet. This field is used to determine the health of the subsystem that is sending the packet. In the case of a packet that traverses several intermediate nodes, it may be the node address of the intermediate node. The target node is the node address of the next hop for the packet. It may be an intermediate node, or the final destination for the packet. The sequence number is used to identify duplicate packets. Because each interface has multiple transceivers, the same packet will appear at both receivers. The sequence number allows the interface to correlate the reception and forward a single, unique packet for additional processing. The subnet field allows data traffic to be partitioned into segregated local networks to support large networks while keeping each subnet at a manageable size. This also keeps the routing table small enough so routing can be done by a simple table lookup in an FPGA device. The subsystem class identifies members of a set of redundant subsystems, and, in a hot standby configuration, all members of the subsystem class will receive the data packets. Only the active subsystem will generate data traffic. Specific units in a class of redundant units can be identified and, if the hot standby configuration is not used, packets will be directed to a specific subsystem unit.

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

An energy-efficient and secure hybrid algorithm for wireless sensor networks using a mobile data collector

NASA Astrophysics Data System (ADS)

Dayananda, Karanam Ravichandran; Straub, Jeremy

2017-05-01

This paper proposes a new hybrid algorithm for security, which incorporates both distributed and hierarchal approaches. It uses a mobile data collector (MDC) to collect information in order to save energy of sensor nodes in a wireless sensor network (WSN) as, in most networks, these sensor nodes have limited energy. Wireless sensor networks are prone to security problems because, among other things, it is possible to use a rogue sensor node to eavesdrop on or alter the information being transmitted. To prevent this, this paper introduces a security algorithm for MDC-based WSNs. A key use of this algorithm is to protect the confidentiality of the information sent by the sensor nodes. The sensor nodes are deployed in a random fashion and form group structures called clusters. Each cluster has a cluster head. The cluster head collects data from the other nodes using the time-division multiple access protocol. The sensor nodes send their data to the cluster head for transmission to the base station node for further processing. The MDC acts as an intermediate node between the cluster head and base station. The MDC, using its dynamic acyclic graph path, collects the data from the cluster head and sends it to base station. This approach is useful for applications including warfighting, intelligent building and medicine. To assess the proposed system, the paper presents a comparison of its performance with other approaches and algorithms that can be used for similar purposes.

An improved PRoPHET routing protocol in delay tolerant network.

PubMed

Han, Seung Deok; Chung, Yun Won

2015-01-01

In delay tolerant network (DTN), an end-to-end path is not guaranteed and packets are delivered from a source node to a destination node via store-carry-forward based routing. In DTN, a source node or an intermediate node stores packets in buffer and carries them while it moves around. These packets are forwarded to other nodes based on predefined criteria and finally are delivered to a destination node via multiple hops. In this paper, we improve the dissemination speed of PRoPHET (probability routing protocol using history of encounters and transitivity) protocol by employing epidemic protocol for disseminating message m, if forwarding counter and hop counter values are smaller than or equal to the threshold values. The performance of the proposed protocol was analyzed from the aspect of delivery probability, average delay, and overhead ratio. Numerical results show that the proposed protocol can improve the delivery probability, average delay, and overhead ratio of PRoPHET protocol by appropriately selecting the threshold forwarding counter and threshold hop counter values.

Mobile Sinks Assisted Geographic and Opportunistic Routing Based Interference Avoidance for Underwater Wireless Sensor Network

PubMed Central

Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil

2018-01-01

The distinctive features of acoustic communication channel-like high propagation delay, multi-path fading, quick attenuation of acoustic signal, etc. limit the utilization of underwater wireless sensor networks (UWSNs). The immutable selection of forwarder node leads to dramatic death of node resulting in imbalanced energy depletion and void hole creation. To reduce the probability of void occurrence and imbalance energy dissipation, in this paper, we propose mobility assisted geo-opportunistic routing paradigm based on interference avoidance for UWSNs. The network volume is divided into logical small cubes to reduce the interference and to make more informed routing decisions for efficient energy consumption. Additionally, an optimal number of forwarder nodes is elected from each cube based on its proximity with respect to the destination to avoid void occurrence. Moreover, the data packets are recovered from void regions with the help of mobile sinks which also reduce the data traffic on intermediate nodes. Extensive simulations are performed to verify that our proposed work maximizes the network lifetime and packet delivery ratio. PMID:29614794

Mobile Sinks Assisted Geographic and Opportunistic Routing Based Interference Avoidance for Underwater Wireless Sensor Network.

PubMed

Ahmed, Farwa; Wadud, Zahid; Javaid, Nadeem; Alrajeh, Nabil; Alabed, Mohamad Souheil; Qasim, Umar

2018-04-02

The distinctive features of acoustic communication channel-like high propagation delay, multi-path fading, quick attenuation of acoustic signal, etc. limit the utilization of underwater wireless sensor networks (UWSNs). The immutable selection of forwarder node leads to dramatic death of node resulting in imbalanced energy depletion and void hole creation. To reduce the probability of void occurrence and imbalance energy dissipation, in this paper, we propose mobility assisted geo-opportunistic routing paradigm based on interference avoidance for UWSNs. The network volume is divided into logical small cubes to reduce the interference and to make more informed routing decisions for efficient energy consumption. Additionally, an optimal number of forwarder nodes is elected from each cube based on its proximity with respect to the destination to avoid void occurrence. Moreover, the data packets are recovered from void regions with the help of mobile sinks which also reduce the data traffic on intermediate nodes. Extensive simulations are performed to verify that our proposed work maximizes the network lifetime and packet delivery ratio.

The use of nodes attributes in social network analysis with an application to an international trade network

NASA Astrophysics Data System (ADS)

de Andrade, Ricardo Lopes; Rêgo, Leandro Chaves

2018-02-01

The social network analysis (SNA) studies the interactions among actors in a network formed through some relationship (friendship, cooperation, trade, among others). The SNA is constantly approached from a binary point of view, i.e., it is only observed if a link between two actors is present or not regardless of the strength of this link. It is known that different information can be obtained in weighted and unweighted networks and that the information extracted from weighted networks is more accurate and detailed. Another rarely discussed approach in the SNA is related to the individual attributes of the actors (nodes), because such analysis is usually focused on the topological structure of networks. Features of the nodes are not incorporated in the SNA what implies that there is some loss or misperception of information in those analyze. This paper aims at exploring more precisely the complexities of a social network, initially developing a method that inserts the individual attributes in the topological structure of the network and then analyzing the network in four different ways: unweighted, edge-weighted and two methods for using both edge-weights and nodes' attributes. The international trade network was chosen in the application of this approach, where the nodes represent the countries, the links represent the cash flow in the trade transactions and countries' GDP were chosen as nodes' attributes. As a result, it is possible to observe which countries are most connected in the world economy and with higher cash flows, to point out the countries that are central to the intermediation of the wealth flow and those that are most benefited from being included in this network. We also made a principal component analysis to study which metrics are more influential in describing the data variability, which turn out to be mostly the weighted metrics which include the nodes' attributes.

Inclusion of tank configurations as a variable in the cost optimization of branched piped-water networks

NASA Astrophysics Data System (ADS)

Hooda, Nikhil; Damani, Om

2017-06-01

The classic problem of the capital cost optimization of branched piped networks consists of choosing pipe diameters for each pipe in the network from a discrete set of commercially available pipe diameters. Each pipe in the network can consist of multiple segments of differing diameters. Water networks also consist of intermediate tanks that act as buffers between incoming flow from the primary source and the outgoing flow to the demand nodes. The network from the primary source to the tanks is called the primary network, and the network from the tanks to the demand nodes is called the secondary network. During the design stage, the primary and secondary networks are optimized separately, with the tanks acting as demand nodes for the primary network. Typically the choice of tank locations, their elevations, and the set of demand nodes to be served by different tanks is manually made in an ad hoc fashion before any optimization is done. It is desirable therefore to include this tank configuration choice in the cost optimization process itself. In this work, we explain why the choice of tank configuration is important to the design of a network and describe an integer linear program model that integrates the tank configuration to the standard pipe diameter selection problem. In order to aid the designers of piped-water networks, the improved cost optimization formulation is incorporated into our existing network design system called JalTantra.

Implementation of body area networks based on MICS/WMTS medical bands for healthcare systems.

PubMed

Yuce, Mehmet R; Ho, Chee Keong

2008-01-01

A multi-hoping sensor network system has been implemented to monitor physiological parameters from multiple patient bodies by means of medical communication standards MICS (Medical Implant Communication Service) and WMTS (Wireless Medical Telemetry Service). Unlike the other medical sensor networks (they usually use 2.4 GHz ISM band), we used the two medical standards occupying the frequency bands that are mainly assigned to medical applications. The prototype system uses the MICS band (402-405 MHz) between the sensor nodes and a remote central control unit (CCU). And WMTS frequencies (608-614MHz) are used between the CCUs and the remote base stations allowing for a much larger range acting as an intermediate node. The sensor nodes in the prototype can measure up to four body signals (i.e. 4-channel) where one is dedicated to a continuous physiological signal such as ECC/EEG. The system includes firmware and software designs that can provide a long distance data transfer through the internet or a mobile network.

Massively parallel processor networks with optical express channels

DOEpatents

Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.

1999-08-24

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.

Massively parallel processor networks with optical express channels

DOEpatents

Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.

1999-01-01

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.

Takeover times for a simple model of network infection.

PubMed

Ottino-Löffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

2017-07-01

We study a stochastic model of infection spreading on a network. At each time step a node is chosen at random, along with one of its neighbors. If the node is infected and the neighbor is susceptible, the neighbor becomes infected. How many time steps T does it take to completely infect a network of N nodes, starting from a single infected node? An analogy to the classic "coupon collector" problem of probability theory reveals that the takeover time T is dominated by extremal behavior, either when there are only a few infected nodes near the start of the process or a few susceptible nodes near the end. We show that for N≫1, the takeover time T is distributed as a Gumbel distribution for the star graph, as the convolution of two Gumbel distributions for a complete graph and an Erdős-Rényi random graph, as a normal for a one-dimensional ring and a two-dimensional lattice, and as a family of intermediate skewed distributions for d-dimensional lattices with d≥3 (these distributions approach the convolution of two Gumbel distributions as d approaches infinity). Connections to evolutionary dynamics, cancer, incubation periods of infectious diseases, first-passage percolation, and other spreading phenomena in biology and physics are discussed.

Takeover times for a simple model of network infection

NASA Astrophysics Data System (ADS)

Ottino-Löffler, Bertrand; Scott, Jacob G.; Strogatz, Steven H.

2017-07-01

We study a stochastic model of infection spreading on a network. At each time step a node is chosen at random, along with one of its neighbors. If the node is infected and the neighbor is susceptible, the neighbor becomes infected. How many time steps T does it take to completely infect a network of N nodes, starting from a single infected node? An analogy to the classic "coupon collector" problem of probability theory reveals that the takeover time T is dominated by extremal behavior, either when there are only a few infected nodes near the start of the process or a few susceptible nodes near the end. We show that for N ≫1 , the takeover time T is distributed as a Gumbel distribution for the star graph, as the convolution of two Gumbel distributions for a complete graph and an Erdős-Rényi random graph, as a normal for a one-dimensional ring and a two-dimensional lattice, and as a family of intermediate skewed distributions for d -dimensional lattices with d ≥3 (these distributions approach the convolution of two Gumbel distributions as d approaches infinity). Connections to evolutionary dynamics, cancer, incubation periods of infectious diseases, first-passage percolation, and other spreading phenomena in biology and physics are discussed.

Prioritized Degree Distribution in Wireless Sensor Networks with a Network Coded Data Collection Method

PubMed Central

Wan, Jan; Xiong, Naixue; Zhang, Wei; Zhang, Qinchao; Wan, Zheng

2012-01-01

The reliability of wireless sensor networks (WSNs) can be greatly affected by failures of sensor nodes due to energy exhaustion or the influence of brutal external environment conditions. Such failures seriously affect the data persistence and collection efficiency. Strategies based on network coding technology for WSNs such as LTCDS can improve the data persistence without mass redundancy. However, due to the bad intermediate performance of LTCDS, a serious ‘cliff effect’ may appear during the decoding period, and source data are hard to recover from sink nodes before sufficient encoded packets are collected. In this paper, the influence of coding degree distribution strategy on the ‘cliff effect’ is observed and the prioritized data storage and dissemination algorithm PLTD-ALPHA is presented to achieve better data persistence and recovering performance. With PLTD-ALPHA, the data in sensor network nodes present a trend that their degree distribution increases along with the degree level predefined, and the persistent data packets can be submitted to the sink node according to its degree in order. Finally, the performance of PLTD-ALPHA is evaluated and experiment results show that PLTD-ALPHA can greatly improve the data collection performance and decoding efficiency, while data persistence is not notably affected. PMID:23235451

The Sojourn Time in a Three Node, Acyclic, Jackson Queueing Network.

DTIC Science & Technology

1982-01-27

Effect of Intermediate Storage on Production Lines with Dependent Machines, Robert D. Foley and Petcharat Chansaenwilai 8015 Some Conditions for the...Queues, Robert D. Foley 8105 Reversibility of Production Lines with Dependent Machines, Petcharat Chansaenwilai 1 8106 Queues with Delayed Feedback, Robert

Wavelength assignment algorithm considering the state of neighborhood links for OBS networks

NASA Astrophysics Data System (ADS)

Tanaka, Yu; Hirota, Yusuke; Tode, Hideki; Murakami, Koso

2005-10-01

Recently, Optical WDM technology is introduced into backbone networks. On the other hand, as the future optical switching scheme, Optical Burst Switching (OBS) systems become a realistic solution. OBS systems do not consider buffering in intermediate nodes. Thus, it is an important issue to avoid overlapping wavelength reservation between partially interfered paths. To solve this problem, so far, the wavelength assignment scheme which has priority management tables has been proposed. This method achieves the reduction of burst blocking probability. However, this priority management table requires huge memory space. In this paper, we propose a wavelength assignment algorithm that reduces both the number of priority management tables and burst blocking probability. To reduce priority management tables, we allocate and manage them for each link. To reduce burst blocking probability, our method announces information about the change of their priorities to intermediate nodes. We evaluate its performance in terms of the burst blocking probability and the reduction rate of priority management tables.

Process-in-Network: A Comprehensive Network Processing Approach

PubMed Central

Urzaiz, Gabriel; Villa, David; Villanueva, Felix; Lopez, Juan Carlos

2012-01-01

A solid and versatile communications platform is very important in modern Ambient Intelligence (AmI) applications, which usually require the transmission of large amounts of multimedia information over a highly heterogeneous network. This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network processing technologies. PIN can take advantage of waiting times in queues of routers, idle processing capacity in intermediate nodes, and the information that passes through the network. PMID:22969390

High speed all optical networks

NASA Technical Reports Server (NTRS)

Chlamtac, Imrich; Ganz, Aura

1990-01-01

An inherent problem of conventional point-to-point wide area network (WAN) architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. The first solution to wavelength division multiplexing (WDM) based WAN networks that overcomes this limitation is presented. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs. The principle of the Lightnet architecture is the construction and use of virtual topology networks, embedded in the original network in the wavelength domain. For this construction Lightnets utilize the new concept of lightpaths which constitute the links of the virtual topology. Lightpaths are all-optical, multihop, paths in the network that allow data to be switched through intermediate nodes using high throughput passive optical switches. The use of the virtual topologies and the associated switching design introduce a number of new ideas, which are discussed in detail.

Advanced information processing system: Authentication protocols for network communication

NASA Technical Reports Server (NTRS)

Harper, Richard E.; Adams, Stuart J.; Babikyan, Carol A.; Butler, Bryan P.; Clark, Anne L.; Lala, Jaynarayan H.

1994-01-01

In safety critical I/O and intercomputer communication networks, reliable message transmission is an important concern. Difficulties of communication and fault identification in networks arise primarily because the sender of a transmission cannot be identified with certainty, an intermediate node can corrupt a message without certainty of detection, and a babbling node cannot be identified and silenced without lengthy diagnosis and reconfiguration . Authentication protocols use digital signature techniques to verify the authenticity of messages with high probability. Such protocols appear to provide an efficient solution to many of these problems. The objective of this program is to develop, demonstrate, and evaluate intercomputer communication architectures which employ authentication. As a context for the evaluation, the authentication protocol-based communication concept was demonstrated under this program by hosting a real-time flight critical guidance, navigation and control algorithm on a distributed, heterogeneous, mixed redundancy system of workstations and embedded fault-tolerant computers.

Think locally, act locally: detection of small, medium-sized, and large communities in large networks.

PubMed

Jeub, Lucas G S; Balachandran, Prakash; Porter, Mason A; Mucha, Peter J; Mahoney, Michael W

2015-01-01

It is common in the study of networks to investigate intermediate-sized (or "meso-scale") features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify "communities," which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that communities are associated with bottlenecks of locally biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for "size-resolved community structure" that can arise in real (and realistic) networks: (1) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (2) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (3) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify "good" communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that, for many large realistic networks, the output of locally biased methods that focus on communities that are centered around a given seed node (or set of seed nodes) might have better conceptual grounding and greater practical utility than the output of global community-detection methods. They also illustrate structural properties that are important to consider in the development of better benchmark networks to test methods for community detection.

Think locally, act locally: Detection of small, medium-sized, and large communities in large networks

NASA Astrophysics Data System (ADS)

Jeub, Lucas G. S.; Balachandran, Prakash; Porter, Mason A.; Mucha, Peter J.; Mahoney, Michael W.

2015-01-01

It is common in the study of networks to investigate intermediate-sized (or "meso-scale") features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify "communities," which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that communities are associated with bottlenecks of locally biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for "size-resolved community structure" that can arise in real (and realistic) networks: (1) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (2) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (3) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify "good" communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that, for many large realistic networks, the output of locally biased methods that focus on communities that are centered around a given seed node (or set of seed nodes) might have better conceptual grounding and greater practical utility than the output of global community-detection methods. They also illustrate structural properties that are important to consider in the development of better benchmark networks to test methods for community detection.

Systematic network coding for two-hop lossy transmissions

NASA Astrophysics Data System (ADS)

Li, Ye; Blostein, Steven; Chan, Wai-Yip

2015-12-01

In this paper, we consider network transmissions over a single or multiple parallel two-hop lossy paths. These scenarios occur in applications such as sensor networks or WiFi offloading. Random linear network coding (RLNC), where previously received packets are re-encoded at intermediate nodes and forwarded, is known to be a capacity-achieving approach for these networks. However, a major drawback of RLNC is its high encoding and decoding complexity. In this work, a systematic network coding method is proposed. We show through both analysis and simulation that the proposed method achieves higher end-to-end rate as well as lower computational cost than RLNC for finite field sizes and finite-sized packet transmissions.

Metabolic PathFinding: inferring relevant pathways in biochemical networks.

PubMed

Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques

2005-07-01

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).

Robust Self-Authenticating Network Coding

DTIC Science & Technology

2008-11-30

efficient as traditional point-to-point coding schemes 3m*b*c*ts»tt a«2b»c*dt4g »4.0»C* 3d *Sh Number of symbols that an intermediate node has to...Institute of Technology This work was partly supported by the Fundacao para a Ciencia e Tecnologia (Portuguese foundation lor Science and Technology

About the specialized myocardial conducting tissue.

PubMed

de Micheli Serra, Alfredo; Iturralde Torres, Pedro; Aranda Fraustro, Alberto

2013-01-01

The chronological succession of discoveries on the location and structure of the atrio-ventricular conducting system are described. The starting point of this system is located in the sinus atrial node, identified by the English scientists A. Keith and M. W. Flack in 1907. The atrioventricular conducting system was pointed out by the Swiss physician Wilhelm His Jr. in 1893. The atrioventricular node (AV) was first identified by the Japanese pathologist Sumao Tawara and his German professor Ludwig Aschoff in 1906. Likewise the structure and routes of the three internodal bundles are described. These bundles include: Bachmann's bundle (1916) connecting the right with the left atrium and the AV node; the middle Wenckebach's bundle (1910) and the posterior or Thörel's bundle (1910), extending from the region of the sinus atrial node towards the posterior margin of the AV node. Lastly, the ventricular left and right conduction systems are detailed. These include the main trunk and their peripheral subdivisions with respective networks. Regarding the controversial existence of the left middle subdivision, it can exist in animal and human hearts. Nevertheless, an intermediate left septal network of specialized fibers seems to act as a functional equivalent of this subdivision. Copyright © 2012 Instituto Nacional de Cardiología Ignacio Chávez. Published by Masson Doyma México S.A. All rights reserved.

A multi-hop teleportation protocol of arbitrary four-qubit states through intermediate nodes

NASA Astrophysics Data System (ADS)

Choudhury, Binayak S.; Samanta, Soumen

Teleportation processes over long distances become affected by the almost inevitable existence of noise which interferes with the entangled quantum channels. In view of this, intermediate nodes are introduced in the scheme. These nodes are connected in series through quantum entanglement. In this paper, we present a protocol for transferring an entangled four-particle cluster-type state in an integrated manner through the intermediate nodes. Its efficiency and advantage over the corresponding part by part teleportation process is discussed.

Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks

PubMed Central

Jeub, Lucas G. S.; Balachandran, Prakash; Porter, Mason A.; Mucha, Peter J.; Mahoney, Michael W.

2016-01-01

It is common in the study of networks to investigate intermediate-sized (or “meso-scale”) features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify “communities,” which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that “communities” are associated with bottlenecks of locally-biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for “size-resolved community structure” that can arise in real (and realistic) networks: (i) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (ii) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (iii) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify “good” communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that, for many large realistic networks, the output of locally-biased methods that focus on communities that are centered around a given seed node might have better conceptual grounding and greater practical utility than the output of global community-detection methods. They also illustrate subtler structural properties that are important to consider in the development of better benchmark networks to test methods for community detection. PMID:25679670

Noise-induced polarization switching in complex networks

NASA Astrophysics Data System (ADS)

Haerter, Jan O.; Díaz-Guilera, Albert; Serrano, M. Ángeles

2017-04-01

The combination of bistability and noise is ubiquitous in complex systems, from biology to social interactions, and has important implications for their functioning and resilience. Here we use a simple three-state dynamical process, in which nodes go from one pole to another through an intermediate state, to show that noise can induce polarization switching in bistable systems if dynamical correlations are significant. In large, fully connected networks, where dynamical correlations can be neglected, increasing noise yields a collapse of bistability to an unpolarized configuration where the three possible states of the nodes are equally likely. In contrast, increased noise induces abrupt and irreversible polarization switching in sparsely connected networks. In multiplexes, where each layer can have a different polarization tendency, one layer is dominant and progressively imposes its polarization state on the other, offsetting or promoting the ability of noise to switch its polarization. Overall, we show that the interplay of noise and dynamical correlations can yield discontinuous transitions between extremes, which cannot be explained by a simple mean-field description.

On service differentiation in mobile Ad Hoc networks.

PubMed

Zhang, Shun-liang; Ye, Cheng-qing

2004-09-01

A network model is proposed to support service differentiation for mobile Ad Hoc networks by combining a fully distributed admission control approach and the DIFS based differentiation mechanism of IEEE802.11. It can provide different kinds of QoS (Quality of Service) for various applications. Admission controllers determine a committed bandwidth based on the reserved bandwidth of flows and the source utilization of networks. Packets are marked when entering into networks by markers according to the committed rate. By the mark in the packet header, intermediate nodes handle the received packets in different manners to provide applications with the QoS corresponding to the pre-negotiated profile. Extensive simulation experiments showed that the proposed mechanism can provide QoS guarantee to assured service traffic and increase the channel utilization of networks.

Performance analysis of signaling protocols on OBS switches

NASA Astrophysics Data System (ADS)

Kirci, Pinar; Zaim, A. Halim

2005-10-01

In this paper, Just-In-Time (JIT), Just-Enough-Time (JET) and Horizon signalling schemes for Optical Burst Switched Networks (OBS) are presented. These signaling schemes run over a core dWDM network and a network architecture based on Optical Burst Switches (OBS) is proposed to support IP, ATM and Burst traffic. In IP and ATM traffic several packets are assembled in a single packet called burst and the burst contention is handled by burst dropping. The burst length distribution in IP traffic is arbitrary between 0 and 1, and is fixed in ATM traffic at 0,5. Burst traffic on the other hand is arbitrary between 1 and 5. The Setup and Setup ack length distributions are arbitrary. We apply the Poisson model with rate λ and Self-Similar model with pareto distribution rate α to identify inter-arrival times in these protocols. We consider a communication between a source client node and a destination client node over an ingress and one or more multiple intermediate switches.We use buffering only in the ingress node. The communication is based on single burst connections in which, the connection is set up just before sending a burst and then closed as soon as the burst is sent. Our analysis accounts for several important parameters, including the burst setup, burst setup ack, keepalive messages and the optical switching protocol. We compare the performance of the three signalling schemes on the network under as burst dropping probability under a range of network scenarios.

Fault tolerant hypercube computer system architecture

NASA Technical Reports Server (NTRS)

Madan, Herb S. (Inventor); Chow, Edward (Inventor)

1989-01-01

A fault-tolerant multiprocessor computer system of the hypercube type comprising a hierarchy of computers of like kind which can be functionally substituted for one another as necessary is disclosed. Communication between the working nodes is via one communications network while communications between the working nodes and watch dog nodes and load balancing nodes higher in the structure is via another communications network separate from the first. A typical branch of the hierarchy reporting to a master node or host computer comprises, a plurality of first computing nodes; a first network of message conducting paths for interconnecting the first computing nodes as a hypercube. The first network provides a path for message transfer between the first computing nodes; a first watch dog node; and a second network of message connecting paths for connecting the first computing nodes to the first watch dog node independent from the first network, the second network provides an independent path for test message and reconfiguration affecting transfers between the first computing nodes and the first switch watch dog node. There is additionally, a plurality of second computing nodes; a third network of message conducting paths for interconnecting the second computing nodes as a hypercube. The third network provides a path for message transfer between the second computing nodes; a fourth network of message conducting paths for connecting the second computing nodes to the first watch dog node independent from the third network. The fourth network provides an independent path for test message and reconfiguration affecting transfers between the second computing nodes and the first watch dog node; and a first multiplexer disposed between the first watch dog node and the second and fourth networks for allowing the first watch dog node to selectively communicate with individual ones of the computing nodes through the second and fourth networks; as well as, a second watch dog node operably connected to the first multiplexer whereby the second watch dog node can selectively communicate with individual ones of the computing nodes through the second and fourth networks. The branch is completed by a first load balancing node; and a second multiplexer connected between the first load balancing node and the first and second watch dog nodes, allowing the first load balancing node to selectively communicate with the first and second watch dog nodes.

Asynchronous broadcast for ordered delivery between compute nodes in a parallel computing system where packet header space is limited

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Sameer

Disclosed is a mechanism on receiving processors in a parallel computing system for providing order to data packets received from a broadcast call and to distinguish data packets received at nodes from several incoming asynchronous broadcast messages where header space is limited. In the present invention, processors at lower leafs of a tree do not need to obtain a broadcast message by directly accessing the data in a root processor's buffer. Instead, each subsequent intermediate node's rank id information is squeezed into the software header of packet headers. In turn, the entire broadcast message is not transferred from the rootmore » processor to each processor in a communicator but instead is replicated on several intermediate nodes which then replicated the message to nodes in lower leafs. Hence, the intermediate compute nodes become "virtual root compute nodes" for the purpose of replicating the broadcast message to lower levels of a tree.« less

Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks

PubMed Central

Liu, Jun; Jiang, Peng; Wu, Feng; Yu, Shanen; Song, Chunyue

2016-01-01

During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. PMID:28029124

Flexible embedding of networks

NASA Astrophysics Data System (ADS)

Fernandez-Gracia, Juan; Buckee, Caroline; Onnela, Jukka-Pekka

We introduce a model for embedding one network into another, focusing on the case where network A is much bigger than network B. Nodes from network A are assigned to the nodes in network B using an algorithm where we control the extent of localization of node placement in network B using a single parameter. Starting from an unassigned node in network A, called the source node, we first map this node to a randomly chosen node in network B, called the target node. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk based approach. To assign each neighbor of the source node to one of the nodes in network B, we perform a random walk starting from the target node with stopping probability α. We repeat this process until all nodes in network A have been mapped to the nodes of network B. The simplicity of the model allows us to calculate key quantities of interest in closed form. By varying the parameter α, we are able to produce embeddings from very local (α = 1) to very global (α --> 0). We show how our calculations fit the simulated results, and we apply the model to study how social networks are embedded in geography and how the neurons of C. Elegans are embedded in the surrounding volume.

Network Disruption in the Preclinical Stages of Alzheimer's Disease: From Subjective Cognitive Decline to Mild Cognitive Impairment.

PubMed

López-Sanz, David; Garcés, Pilar; Álvarez, Blanca; Delgado-Losada, María Luisa; López-Higes, Ramón; Maestú, Fernando

2017-12-01

Subjective Cognitive Decline (SCD) is a largely unknown state thought to represent a preclinical stage of Alzheimer's Disease (AD) previous to mild cognitive impairment (MCI). However, the course of network disruption in these stages is scarcely characterized. We employed resting state magnetoencephalography in the source space to calculate network smallworldness, clustering, modularity and transitivity. Nodal measures (clustering and node degree) as well as modular partitions were compared between groups. The MCI group exhibited decreased smallworldness, clustering and transitivity and increased modularity in theta and beta bands. SCD showed similar but smaller changes in clustering and transitivity, while exhibiting alterations in the alpha band in opposite direction to those showed by MCI for modularity and transitivity. At the node level, MCI disrupted both clustering and nodal degree while SCD showed minor changes in the latter. Additionally, we observed an increase in modular partition variability in both SCD and MCI in theta and beta bands. SCD elders exhibit a significant network disruption, showing intermediate values between HC and MCI groups in multiple parameters. These results highlight the relevance of cognitive concerns in the clinical setting and suggest that network disorganization in AD could start in the preclinical stages before the onset of cognitive symptoms.

Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks

PubMed Central

Yu, Shanen; Xu, Yiming; Jiang, Peng; Wu, Feng; Xu, Huan

2017-01-01

At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. PMID:28338615

Resource Sharing via Planed Relay for [InlineEquation not available: see fulltext.

NASA Astrophysics Data System (ADS)

Shen, Chong; Rea, Susan; Pesch, Dirk

2008-12-01

We present an improved version of adaptive distributed cross-layer routing algorithm (ADCR) for hybrid wireless network with dedicated relay stations ([InlineEquation not available: see fulltext.]) in this paper. A mobile terminal (MT) may borrow radio resources that are available thousands mile away via secure multihop RNs, where RNs are placed at pre-engineered locations in the network. In rural places such as mountain areas, an MT may also communicate with the core network, when intermediate MTs act as relay node with mobility. To address cross-layer network layers routing issues, the cascaded ADCR establishes routing paths across MTs, RNs, and cellular base stations (BSs) and provides appropriate quality of service (QoS). We verify the routing performance benefits of [InlineEquation not available: see fulltext.] over other networks by intensive simulation.

Reconfigureable network node

DOEpatents

Vanderveen, Keith B [Tracy, CA; Talbot, Edward B [Livermore, CA; Mayer, Laurence E [Davis, CA

2008-04-08

Nodes in a network having a plurality of nodes establish communication links with other nodes using available transmission media, as the ability to establish such links becomes available and desirable. The nodes predict when existing communications links will fail, become overloaded or otherwise degrade network effectiveness and act to establish substitute or additional links before the node's ability to communicate with the other nodes on the network is adversely affected. A node stores network topology information and programmed link establishment rules and criteria. The node evaluates characteristics that predict existing links with other nodes becoming unavailable or degraded. The node then determines whether it can form a communication link with a substitute node, in order to maintain connectivity with the network. When changing its communication links, a node broadcasts that information to the network. Other nodes update their stored topology information and consider the updated topology when establishing new communications links for themselves.

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network. PMID:28481245

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods.

PubMed

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-05-06

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J; Faraj, Ahmad A; Inglett, Todd A; Ratterman, Joseph D

2013-04-16

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

Simple Peer-to-Peer SIP Privacy

NASA Astrophysics Data System (ADS)

Koskela, Joakim; Tarkoma, Sasu

In this paper, we introduce a model for enhancing privacy in peer-to-peer communication systems. The model is based on data obfuscation, preventing intermediate nodes from tracking calls, while still utilizing the shared resources of the peer network. This increases security when moving between untrusted, limited and ad-hoc networks, when the user is forced to rely on peer-to-peer schemes. The model is evaluated using a Host Identity Protocol-based prototype on mobile devices, and is found to provide good privacy, especially when combined with a source address hiding scheme. The contribution of this paper is to present the model and results obtained from its use, including usability considerations.

Determining a bisection bandwidth for a multi-node data communications network

DOEpatents

Faraj, Ahmad A.

2010-01-26

Methods, systems, and products are disclosed for determining a bisection bandwidth for a multi-node data communications network that include: partitioning nodes in the network into a first sub-network and a second sub-network in dependence upon a topology of the network; sending, by each node in the first sub-network to a destination node in the second sub-network, a first message having a predetermined message size; receiving, by each node in the first sub-network from a source node in the second sub-network, a second message; measuring, by each node in the first sub-network, the elapsed communications time between the sending of the first message and the receiving of the second message; selecting the longest elapsed communications time; and calculating the bisection bandwidth for the network in dependence upon the number of the nodes in the first sub-network, the predetermined message size of the first test message, and the longest elapsed communications time.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selectedmore » link to the adjacent compute node connected to the compute node through the selected link.« less

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

PubMed Central

Jiang, Peng; Xu, Yiming; Wu, Feng

2016-01-01

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. PMID:26784193

Large-scale quantum networks based on graphs

NASA Astrophysics Data System (ADS)

Epping, Michael; Kampermann, Hermann; Bruß, Dagmar

2016-05-01

Society relies and depends increasingly on information exchange and communication. In the quantum world, security and privacy is a built-in feature for information processing. The essential ingredient for exploiting these quantum advantages is the resource of entanglement, which can be shared between two or more parties. The distribution of entanglement over large distances constitutes a key challenge for current research and development. Due to losses of the transmitted quantum particles, which typically scale exponentially with the distance, intermediate quantum repeater stations are needed. Here we show how to generalise the quantum repeater concept to the multipartite case, by describing large-scale quantum networks, i.e. network nodes and their long-distance links, consistently in the language of graphs and graph states. This unifying approach comprises both the distribution of multipartite entanglement across the network, and the protection against errors via encoding. The correspondence to graph states also provides a tool for optimising the architecture of quantum networks.

Analysis of complex network performance and heuristic node removal strategies

NASA Astrophysics Data System (ADS)

Jahanpour, Ehsan; Chen, Xin

2013-12-01

Removing important nodes from complex networks is a great challenge in fighting against criminal organizations and preventing disease outbreaks. Six network performance metrics, including four new metrics, are applied to quantify networks' diffusion speed, diffusion scale, homogeneity, and diameter. In order to efficiently identify nodes whose removal maximally destroys a network, i.e., minimizes network performance, ten structured heuristic node removal strategies are designed using different node centrality metrics including degree, betweenness, reciprocal closeness, complement-derived closeness, and eigenvector centrality. These strategies are applied to remove nodes from the September 11, 2001 hijackers' network, and their performance are compared to that of a random strategy, which removes randomly selected nodes, and the locally optimal solution (LOS), which removes nodes to minimize network performance at each step. The computational complexity of the 11 strategies and LOS is also analyzed. Results show that the node removal strategies using degree and betweenness centralities are more efficient than other strategies.

Balance of Interactions Determines Optimal Survival in Multi-Species Communities.

PubMed

Choudhary, Anshul; Sinha, Sudeshna

2015-01-01

We consider a multi-species community modelled as a complex network of populations, where the links are given by a random asymmetric connectivity matrix J, with fraction 1 - C of zero entries, where C reflects the over-all connectivity of the system. The non-zero elements of J are drawn from a Gaussian distribution with mean μ and standard deviation σ. The signs of the elements Jij reflect the nature of density-dependent interactions, such as predatory-prey, mutualism or competition, and their magnitudes reflect the strength of the interaction. In this study we try to uncover the broad features of the inter-species interactions that determine the global robustness of this network, as indicated by the average number of active nodes (i.e. non-extinct species) in the network, and the total population, reflecting the biomass yield. We find that the network transitions from a completely extinct system to one where all nodes are active, as the mean interaction strength goes from negative to positive, with the transition getting sharper for increasing C and decreasing σ. We also find that the total population, displays distinct non-monotonic scaling behaviour with respect to the product μC, implying that survival is dependent not merely on the number of links, but rather on the combination of the sparseness of the connectivity matrix and the net interaction strength. Interestingly, in an intermediate window of positive μC, the total population is maximal, indicating that too little or too much positive interactions is detrimental to survival. Rather, the total population levels are optimal when the network has intermediate net positive connection strengths. At the local level we observe marked qualitative changes in dynamical patterns, ranging from anti-phase clusters of period 2 cycles and chaotic bands, to fixed points, under the variation of mean μ of the interaction strengths. We also study the correlation between synchronization and survival, and find that synchronization does not necessarily lead to extinction. Lastly, we propose an effective low dimensional map to capture the behavior of the entire network, and this provides a broad understanding of the interplay of the local dynamical patterns and the global robustness trends in the network.

Innovative research of AD HOC network mobility model

NASA Astrophysics Data System (ADS)

Chen, Xin

2017-08-01

It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.

Understanding the influence of all nodes in a network

PubMed Central

Lawyer, Glenn

2015-01-01

Centrality measures such as the degree, k-shell, or eigenvalue centrality can identify a network's most influential nodes, but are rarely usefully accurate in quantifying the spreading power of the vast majority of nodes which are not highly influential. The spreading power of all network nodes is better explained by considering, from a continuous-time epidemiological perspective, the distribution of the force of infection each node generates. The resulting metric, the expected force, accurately quantifies node spreading power under all primary epidemiological models across a wide range of archetypical human contact networks. When node power is low, influence is a function of neighbor degree. As power increases, a node's own degree becomes more important. The strength of this relationship is modulated by network structure, being more pronounced in narrow, dense networks typical of social networking and weakening in broader, looser association networks such as the Internet. The expected force can be computed independently for individual nodes, making it applicable for networks whose adjacency matrix is dynamic, not well specified, or overwhelmingly large. PMID:25727453

Identifying messaging completion in a parallel computer by checking for change in message received and transmitted count at each node

DOEpatents

Archer, Charles J [Rochester, MN; Hardwick, Camesha R [Fayetteville, NC; McCarthy, Patrick J [Rochester, MN; Wallenfelt, Brian P [Eden Prairie, MN

2009-06-23

Methods, parallel computers, and products are provided for identifying messaging completion on a parallel computer. The parallel computer includes a plurality of compute nodes, the compute nodes coupled for data communications by at least two independent data communications networks including a binary tree data communications network optimal for collective operations that organizes the nodes as a tree and a torus data communications network optimal for point to point operations that organizes the nodes as a torus. Embodiments include reading all counters at each node of the torus data communications network; calculating at each node a current node value in dependence upon the values read from the counters at each node; and determining for all nodes whether the current node value for each node is the same as a previously calculated node value for each node. If the current node is the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is complete and if the current node is not the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is currently incomplete.

Neighboring and connectivity-aware routing in VANETs.

PubMed

Ghafoor, Huma; Koo, Insoo; Gohar, Nasir-ud-Din

2014-01-01

A novel position-based routing protocol anchor-based connectivity-aware routing (ACAR) for vehicular ad hoc networks (VANETs) is proposed in this paper to ensure connectivity of routes with more successfully delivered packets. Both buses and cars are considered as vehicular nodes running in both clockwise and anticlockwise directions in a city scenario. Both directions are taken into account for faster communication. ACAR is a hybrid protocol, using both the greedy forwarding approach and the store-carry-and-forward approach to minimize the packet drop rate on the basis of certain assumptions. Our solution to situations that occur when the network is sparse and when any (source or intermediate) node has left its initial position makes this protocol different from those existing in the literature. We consider only vehicle-to-vehicle (V2V) communication in which both the source and destination nodes are moving vehicles. Also, no road-side units are considered. Finally, we compare our protocol with A-STAR (a plausible connectivity-aware routing protocol for city environments), and simulation results in NS-2 show improvement in the number of packets delivered to the destination using fewer hops. Also, we show that ACAR has more successfully-delivered long-distance packets with reasonable packet delay than A-STAR.

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

The molecular kink paradigm for rubber elasticity: Numerical simulations of explicit polyisoprene networks at low to moderate tensile strains

NASA Astrophysics Data System (ADS)

Hanson, David E.

2011-08-01

Based on recent molecular dynamics and ab initio simulations of small isoprene molecules, we propose a new ansatz for rubber elasticity. We envision a network chain as a series of independent molecular kinks, each comprised of a small number of backbone units, and the strain as being imposed along the contour of the chain. We treat chain extension in three distinct force regimes: (Ia) near zero strain, where we assume that the chain is extended within a well defined tube, with all of the kinks participating simultaneously as entropic elastic springs, (II) when the chain becomes sensibly straight, giving rise to a purely enthalpic stretching force (until bond rupture occurs) and, (Ib) a linear entropic regime, between regimes Ia and II, in which a force limit is imposed by tube deformation. In this intermediate regime, the molecular kinks are assumed to be gradually straightened until the chain becomes a series of straight segments between entanglements. We assume that there exists a tube deformation tension limit that is inversely proportional to the chain path tortuosity. Here we report the results of numerical simulations of explicit three-dimensional, periodic, polyisoprene networks, using these extension-only force models. At low strain, crosslink nodes are moved affinely, up to an arbitrary node force limit. Above this limit, non-affine motion of the nodes is allowed to relax unbalanced chain forces. Our simulation results are in good agreement with tensile stress vs. strain experiments.

The molecular kink paradigm for rubber elasticity: numerical simulations of explicit polyisoprene networks at low to moderate tensile strains.

PubMed

Hanson, David E

2011-08-07

Based on recent molecular dynamics and ab initio simulations of small isoprene molecules, we propose a new ansatz for rubber elasticity. We envision a network chain as a series of independent molecular kinks, each comprised of a small number of backbone units, and the strain as being imposed along the contour of the chain. We treat chain extension in three distinct force regimes: (Ia) near zero strain, where we assume that the chain is extended within a well defined tube, with all of the kinks participating simultaneously as entropic elastic springs, (II) when the chain becomes sensibly straight, giving rise to a purely enthalpic stretching force (until bond rupture occurs) and, (Ib) a linear entropic regime, between regimes Ia and II, in which a force limit is imposed by tube deformation. In this intermediate regime, the molecular kinks are assumed to be gradually straightened until the chain becomes a series of straight segments between entanglements. We assume that there exists a tube deformation tension limit that is inversely proportional to the chain path tortuosity. Here we report the results of numerical simulations of explicit three-dimensional, periodic, polyisoprene networks, using these extension-only force models. At low strain, crosslink nodes are moved affinely, up to an arbitrary node force limit. Above this limit, non-affine motion of the nodes is allowed to relax unbalanced chain forces. Our simulation results are in good agreement with tensile stress vs. strain experiments.

Combined diffusion-weighted and functional magnetic resonance imaging reveals a temporal-occipital network involved in auditory-visual object processing

PubMed Central

Beer, Anton L.; Plank, Tina; Meyer, Georg; Greenlee, Mark W.

2013-01-01

Functional magnetic resonance imaging (MRI) showed that the superior temporal and occipital cortex are involved in multisensory integration. Probabilistic fiber tracking based on diffusion-weighted MRI suggests that multisensory processing is supported by white matter connections between auditory cortex and the temporal and occipital lobe. Here, we present a combined functional MRI and probabilistic fiber tracking study that reveals multisensory processing mechanisms that remained undetected by either technique alone. Ten healthy participants passively observed visually presented lip or body movements, heard speech or body action sounds, or were exposed to a combination of both. Bimodal stimulation engaged a temporal-occipital brain network including the multisensory superior temporal sulcus (msSTS), the lateral superior temporal gyrus (lSTG), and the extrastriate body area (EBA). A region-of-interest (ROI) analysis showed multisensory interactions (e.g., subadditive responses to bimodal compared to unimodal stimuli) in the msSTS, the lSTG, and the EBA region. Moreover, sounds elicited responses in the medial occipital cortex. Probabilistic tracking revealed white matter tracts between the auditory cortex and the medial occipital cortex, the inferior occipital cortex (IOC), and the superior temporal sulcus (STS). However, STS terminations of auditory cortex tracts showed limited overlap with the msSTS region. Instead, msSTS was connected to primary sensory regions via intermediate nodes in the temporal and occipital cortex. Similarly, the lSTG and EBA regions showed limited direct white matter connections but instead were connected via intermediate nodes. Our results suggest that multisensory processing in the STS is mediated by separate brain areas that form a distinct network in the lateral temporal and inferior occipital cortex. PMID:23407860

Weighted compactness function based label propagation algorithm for community detection

NASA Astrophysics Data System (ADS)

Zhang, Weitong; Zhang, Rui; Shang, Ronghua; Jiao, Licheng

2018-02-01

Community detection in complex networks, is to detect the community structure with the internal structure relatively compact and the external structure relatively sparse, according to the topological relationship among nodes in the network. In this paper, we propose a compactness function which combines the weight of nodes, and use it as the objective function to carry out the node label propagation. Firstly, according to the node degree, we find the sets of core nodes which have great influence on the network. The more the connections between the core nodes and the other nodes are, the larger the amount of the information these kernel nodes receive and transform. Then, according to the similarity of the nodes between the core nodes sets and the nodes degree, we assign weights to the nodes in the network. So the label of the nodes with great influence will be the priority in the label propagation process, which effectively improves the accuracy of the label propagation. The compactness function between nodes and communities in this paper is based on the nodes influence. It combines the connections between nodes and communities with the degree of the node belongs to its neighbor communities based on calculating the node weight. The function effectively uses the information of nodes and connections in the network. The experimental results show that the proposed algorithm can achieve good results in the artificial network and large-scale real networks compared with the 8 contrast algorithms.

Opinion formation driven by PageRank node influence on directed networks

NASA Astrophysics Data System (ADS)

Eom, Young-Ho; Shepelyansky, Dima L.

2015-10-01

We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.

The congestion control algorithm based on queue management of each node in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Wei, Yifei; Chang, Lin; Wang, Yali; Wang, Gaoping

2016-12-01

This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. As the network load increases, local congestion of mobile ad hoc network may lead to network performance degradation, hot node's energy consumption increase even failure. If small energy nodes congested because of forwarding data packets, then when it is used as the source node will cause a lot of packet loss. This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. Controlling nodes buffer queue in different levels of congestion area probability by adjusting the upper limits and lower limits, thus nodes can adjust responsibility of forwarding data packets according to their own situation. The proposed algorithm will slow down the send rate hop by hop along the data package transmission direction from congestion node to source node so that to prevent further congestion from the source node. The simulation results show that, the algorithm can better play the data forwarding ability of strong nodes, protect the weak nodes, can effectively alleviate the network congestion situation.

Protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

Protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1994-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

Research on centrality of urban transport network nodes

NASA Astrophysics Data System (ADS)

Wang, Kui; Fu, Xiufen

2017-05-01

Based on the actual data of urban transport in Guangzhou, 19,150 bus stations in Guangzhou (as of 2014) are selected as nodes. Based on the theory of complex network, the network model of Guangzhou urban transport is constructed. By analyzing the degree centrality index, betweenness centrality index and closeness centrality index of nodes in the network, the level of centrality of each node in the network is studied. From a different point of view to determine the hub node of Guangzhou urban transport network, corresponding to the city's key sites and major transfer sites. The reliability of the network is determined by the stability of some key nodes (transport hub station). The research of network node centralization can provide a theoretical basis for the rational allocation of urban transport network sites and public transport system planning.

Performance Evaluation of AODV with Blackhole Attack

NASA Astrophysics Data System (ADS)

Dara, Karuna

2010-11-01

A Mobile Ad Hoc Network (MANET) is a temporary network set up by a wireless mobile computers moving arbitrary in the places that have no network infrastructure. These nodes maintain connectivity in a decentralized manner. Since the nodes communicate with each other, they cooperate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. However, due to security vulnerabilities of the routing protocols, mobile ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Black Hole Attack against network integrity absorbing all data packets in the network. Since the data packets do not reach the destination node on account of this attack, data loss will occur. In this paper, we simulated the black hole attack in various mobile ad-hoc network scenarios using AODV routing protocol of MANET and have tried to find a effect if number of nodes are increased with increase in malicious nodes.

Network testbed creation and validation

DOEpatents

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.; Watts, Kristopher K.; Sweeney, Andrew John

2017-03-21

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

Network testbed creation and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices,more » embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.« less

Visualizing weighted networks: a performance comparison of adjacency matrices versus node-link diagrams

NASA Astrophysics Data System (ADS)

McIntire, John P.; Osesina, O. Isaac; Bartley, Cecilia; Tudoreanu, M. Eduard; Havig, Paul R.; Geiselman, Eric E.

2012-06-01

Ensuring the proper and effective ways to visualize network data is important for many areas of academia, applied sciences, the military, and the public. Fields such as social network analysis, genetics, biochemistry, intelligence, cybersecurity, neural network modeling, transit systems, communications, etc. often deal with large, complex network datasets that can be difficult to interact with, study, and use. There have been surprisingly few human factors performance studies on the relative effectiveness of different graph drawings or network diagram techniques to convey information to a viewer. This is particularly true for weighted networks which include the strength of connections between nodes, not just information about which nodes are linked to other nodes. We describe a human factors study in which participants performed four separate network analysis tasks (finding a direct link between given nodes, finding an interconnected node between given nodes, estimating link strengths, and estimating the most densely interconnected nodes) on two different network visualizations: an adjacency matrix with a heat-map versus a node-link diagram. The results should help shed light on effective methods of visualizing network data for some representative analysis tasks, with the ultimate goal of improving usability and performance for viewers of network data displays.

Robustness of weighted networks

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

Community detection using preference networks

NASA Astrophysics Data System (ADS)

Tasgin, Mursel; Bingol, Haluk O.

2018-04-01

Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

Parameters affecting the resilience of scale-free networks to random failures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Link, Hamilton E.; LaViolette, Randall A.; Lane, Terran

2005-09-01

It is commonly believed that scale-free networks are robust to massive numbers of random node deletions. For example, Cohen et al. in (1) study scale-free networks including some which approximate the measured degree distribution of the Internet. Their results suggest that if each node in this network failed independently with probability 0.99, most of the remaining nodes would still be connected in a giant component. In this paper, we show that a large and important subclass of scale-free networks are not robust to massive numbers of random node deletions. In particular, we study scale-free networks which have minimum node degreemore » of 1 and a power-law degree distribution beginning with nodes of degree 1 (power-law networks). We show that, in a power-law network approximating the Internet's reported distribution, when the probability of deletion of each node is 0.5 only about 25% of the surviving nodes in the network remain connected in a giant component, and the giant component does not persist beyond a critical failure rate of 0.9. The new result is partially due to improved analytical accommodation of the large number of degree-0 nodes that result after node deletions. Our results apply to power-law networks with a wide range of power-law exponents, including Internet-like networks. We give both analytical and empirical evidence that such networks are not generally robust to massive random node deletions.« less

Coupling effect of nodes popularity and similarity on social network persistence.

PubMed

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Data driven CAN node reliability assessment for manufacturing system

NASA Astrophysics Data System (ADS)

Zhang, Leiming; Yuan, Yong; Lei, Yong

2017-01-01

The reliability of the Controller Area Network(CAN) is critical to the performance and safety of the system. However, direct bus-off time assessment tools are lacking in practice due to inaccessibility of the node information and the complexity of the node interactions upon errors. In order to measure the mean time to bus-off(MTTB) of all the nodes, a novel data driven node bus-off time assessment method for CAN network is proposed by directly using network error information. First, the corresponding network error event sequence for each node is constructed using multiple-layer network error information. Then, the generalized zero inflated Poisson process(GZIP) model is established for each node based on the error event sequence. Finally, the stochastic model is constructed to predict the MTTB of the node. The accelerated case studies with different error injection rates are conducted on a laboratory network to demonstrate the proposed method, where the network errors are generated by a computer controlled error injection system. Experiment results show that the MTTB of nodes predicted by the proposed method agree well with observations in the case studies. The proposed data driven node time to bus-off assessment method for CAN networks can successfully predict the MTTB of nodes by directly using network error event data.

When Does Neoadjuvant Chemotherapy Really Avoid Radiotherapy? Clinical Predictors of Adjuvant Radiotherapy in Cervical Cancer.

PubMed

Papadia, Andrea; Bellati, Filippo; Bogani, Giorgio; Ditto, Antonino; Martinelli, Fabio; Lorusso, Domenica; Donfrancesco, Cristina; Gasparri, Maria Luisa; Raspagliesi, Francesco

2015-12-01

The aim of this study was to identify clinical variables that may predict the need for adjuvant radiotherapy after neoadjuvant chemotherapy (NACT) and radical surgery in locally advanced cervical cancer patients. A retrospective series of cervical cancer patients with International Federation of Gynecology and Obstetrics (FIGO) stages IB2-IIB treated with NACT followed by radical surgery was analyzed. Clinical predictors of persistence of intermediate- and/or high-risk factors at final pathological analysis were investigated. Statistical analysis was performed using univariate and multivariate analysis and using a model based on artificial intelligence known as artificial neuronal network (ANN) analysis. Overall, 101 patients were available for the analyses. Fifty-two (51 %) patients were considered at high risk secondary to parametrial, resection margin and/or lymph node involvement. When disease was confined to the cervix, four (4 %) patients were considered at intermediate risk. At univariate analysis, FIGO grade 3, stage IIB disease at diagnosis and the presence of enlarged nodes before NACT predicted the presence of intermediate- and/or high-risk factors at final pathological analysis. At multivariate analysis, only FIGO grade 3 and tumor diameter maintained statistical significance. The specificity of ANN models in evaluating predictive variables was slightly superior to conventional multivariable models. FIGO grade, stage, tumor diameter, and histology are associated with persistence of pathological intermediate- and/or high-risk factors after NACT and radical surgery. This information is useful in counseling patients at the time of treatment planning with regard to the probability of being subjected to pelvic radiotherapy after completion of the initially planned treatment.

Constrained target controllability of complex networks

NASA Astrophysics Data System (ADS)

Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

2017-06-01

It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

Quantum information transmission in the quantum wireless multihop network based on Werner state

NASA Astrophysics Data System (ADS)

Shi, Li-Hui; Yu, Xu-Tao; Cai, Xiao-Fei; Gong, Yan-Xiao; Zhang, Zai-Chen

2015-05-01

Many previous studies about teleportation are based on pure state. Study of quantum channel as mixed state is more realistic but complicated as pure states degenerate into mixed states by interaction with environment, and the Werner state plays an important role in the study of the mixed state. In this paper, the quantum wireless multihop network is proposed and the information is transmitted hop by hop through teleportation. We deduce a specific expression of the recovered state not only after one-hop teleportation but also across multiple intermediate nodes based on Werner state in a quantum wireless multihop network. We also obtain the fidelity of multihop teleportation. Project supported by the Prospective Future Network Project of Jiangsu Province, China (Grant No. BY2013095-1-18) and the Independent Project of State Key Laboratory of Millimeter Waves (Grant No. Z201504).

Multiple-Ring Digital Communication Network

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

UMDR: Multi-Path Routing Protocol for Underwater Ad Hoc Networks with Directional Antenna

NASA Astrophysics Data System (ADS)

Yang, Jianmin; Liu, Songzuo; Liu, Qipei; Qiao, Gang

2018-01-01

This paper presents a new routing scheme for underwater ad hoc networks based on directional antennas. Ad hoc networks with directional antennas have become a hot research topic because of space reuse may increase networks capacity. At present, researchers have applied traditional self-organizing routing protocols (such as DSR, AODV) [1] [2] on this type of networks, and the routing scheme is based on the shortest path metric. However, such routing schemes often suffer from long transmission delays and frequent link fragmentation along the intermediate nodes of the selected route. This is caused by a unique feature of directional transmission, often called as “deafness”. In this paper, we take a different approach to explore the advantages of space reuse through multipath routing. This paper introduces the validity of the conventional routing scheme in underwater ad hoc networks with directional antennas, and presents a special design of multipath routing algorithm for directional transmission. The experimental results show a significant performance improvement in throughput and latency.

The robustness of multiplex networks under layer node-based attack

PubMed Central

Zhao, Da-wei; Wang, Lian-hai; Zhi, Yong-feng; Zhang, Jun; Wang, Zhen

2016-01-01

From transportation networks to complex infrastructures, and to social and economic networks, a large variety of systems can be described in terms of multiplex networks formed by a set of nodes interacting through different network layers. Network robustness, as one of the most successful application areas of complex networks, has attracted great interest in a myriad of research realms. In this regard, how multiplex networks respond to potential attack is still an open issue. Here we study the robustness of multiplex networks under layer node-based random or targeted attack, which means that nodes just suffer attacks in a given layer yet no additional influence to their connections beyond this layer. A theoretical analysis framework is proposed to calculate the critical threshold and the size of giant component of multiplex networks when nodes are removed randomly or intentionally. Via numerous simulations, it is unveiled that the theoretical method can accurately predict the threshold and the size of giant component, irrespective of attack strategies. Moreover, we also compare the robustness of multiplex networks under multiplex node-based attack and layer node-based attack, and find that layer node-based attack makes multiplex networks more vulnerable, regardless of average degree and underlying topology. PMID:27075870

The robustness of multiplex networks under layer node-based attack.

PubMed

Zhao, Da-wei; Wang, Lian-hai; Zhi, Yong-feng; Zhang, Jun; Wang, Zhen

2016-04-14

From transportation networks to complex infrastructures, and to social and economic networks, a large variety of systems can be described in terms of multiplex networks formed by a set of nodes interacting through different network layers. Network robustness, as one of the most successful application areas of complex networks, has attracted great interest in a myriad of research realms. In this regard, how multiplex networks respond to potential attack is still an open issue. Here we study the robustness of multiplex networks under layer node-based random or targeted attack, which means that nodes just suffer attacks in a given layer yet no additional influence to their connections beyond this layer. A theoretical analysis framework is proposed to calculate the critical threshold and the size of giant component of multiplex networks when nodes are removed randomly or intentionally. Via numerous simulations, it is unveiled that the theoretical method can accurately predict the threshold and the size of giant component, irrespective of attack strategies. Moreover, we also compare the robustness of multiplex networks under multiplex node-based attack and layer node-based attack, and find that layer node-based attack makes multiplex networks more vulnerable, regardless of average degree and underlying topology.

F77NNS - A FORTRAN-77 NEURAL NETWORK SIMULATOR

NASA Technical Reports Server (NTRS)

Mitchell, P. H.

1994-01-01

F77NNS (A FORTRAN-77 Neural Network Simulator) simulates the popular back error propagation neural network. F77NNS is an ANSI-77 FORTRAN program designed to take advantage of vectorization when run on machines having this capability, but it will run on any computer with an ANSI-77 FORTRAN Compiler. Artificial neural networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to biological nerve cells. Problems which involve pattern matching or system modeling readily fit the class of problems which F77NNS is designed to solve. The program's formulation trains a neural network using Rumelhart's back-propagation algorithm. Typically the nodes of a network are grouped together into clumps called layers. A network will generally have an input layer through which the various environmental stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. The back-propagation training algorithm can require massive computational resources to implement a large network such as a network capable of learning text-to-phoneme pronunciation rules as in the famous Sehnowski experiment. The Sehnowski neural network learns to pronounce 1000 common English words. The standard input data defines the specific inputs that control the type of run to be made, and input files define the NN in terms of the layers and nodes, as well as the input/output (I/O) pairs. The program has a restart capability so that a neural network can be solved in stages suitable to the user's resources and desires. F77NNS allows the user to customize the patterns of connections between layers of a network. The size of the neural network to be solved is limited only by the amount of random access memory (RAM) available to the user. The program has a memory requirement of about 900K. The standard distribution medium for this package is a .25 inch streaming magnetic tape cartridge in UNIX tar format. It is also available on a 3.5 inch diskette in UNIX tar format. F77NNS was developed in 1989.

Node property of weighted networks considering connectability to nodes within two degrees of separation.

PubMed

Amano, Sun-Ichi; Ogawa, Ken-Ichiro; Miyake, Yoshihiro

2018-05-31

Weighted networks have been extensively studied because they can represent various phenomena in which the diversity of edges is essential. To investigate the properties of weighted networks, various centrality measures have been proposed, such as strength, weighted clustering coefficients, and weighted betweenness centrality. In such measures, only direct connections or entire network connectivity from arbitrary nodes have been used to calculate the connectivity of each node. However, in weighted networks composed of autonomous elements such as humans, middle ranges from each node are also considered to be meaningful for characterizing each node's connectability. In this study, we define a new node property in weighted networks to consider connectability to nodes within a range of two degrees of separation, then apply this new centrality to face-to-face human communication networks in corporate organizations. Our results show that the proposed centrality distinguishes inherent communities corresponding to the job types in each organization with a high degree of accuracy. This indicates the possibility that connectability to nodes within two degrees of separation reveals potential trends of weighted networks that are not apparent from conventional measures.

A novel unbalanced multiple description coder for robust video transmission over ad hoc wireless networks

NASA Astrophysics Data System (ADS)

Huang, Feng; Sun, Lifeng; Zhong, Yuzhuo

2006-01-01

Robust transmission of live video over ad hoc wireless networks presents new challenges: high bandwidth requirements are coupled with delay constraints; even a single packet loss causes error propagation until a complete video frame is coded in the intra-mode; ad hoc wireless networks suffer from bursty packet losses that drastically degrade the viewing experience. Accordingly, we propose a novel UMD coder capable of quickly recovering from losses and ensuring continuous playout. It uses 'peg' frames to prevent error propagation in the High-Resolution (HR) description and improve the robustness of key frames. The Low-Resolution (LR) coder works independent of the HR one, but they can also help each other recover from losses. Like many UMD coders, our UMD coder is drift-free, disruption-tolerant and able to make good use of the asymmetric available bandwidths of multiple paths. The simulation results under different conditions show that the proposed UMD coder has the highest decoded quality and lowest probability of pause when compared with concurrent UMDC techniques. The coder also has a comparable decoded quality, lower startup delay and lower probability of pause than a state-of-the-art FEC-based scheme. To provide robustness for video multicast applications, we propose non-end-to-end UMDC-based video distribution over a multi-tree multicast network. The multiplicity of parents decorrelates losses and the non-end-to-end feature increases the throughput of UMDC video data. We deploy an application-level service of LR description reconstruction in some intermediate nodes of the LR multicast tree. The principle behind this is to reconstruct the disrupted LR frames by the correctly received HR frames. As a result, the viewing experience at the downstream nodes benefits from the protection reconstruction at the upstream nodes.

Message propagation in the network based on node credibility

NASA Astrophysics Data System (ADS)

Nian, Fuzhong; Dang, Zhongkai

2018-04-01

In the propagation efficiency point of view, the node credibility is introduced in this paper. For the message receiver, the node would partially believe the message according to the credibility of the propagator. For a node, the credibility is variable. The more the true message spread, the higher the credibility, and vice versa, the credibility becomes smaller. Based on the idea, a new network was established with the node credibility. Finally, a comparing experiment between the fully trusted network and the network with the node credibility was implemented. The results indicate that the spread effect of messages is better in the network with the node credibility.

Understanding the implementation of evidence-based care: a structural network approach.

PubMed

Parchman, Michael L; Scoglio, Caterina M; Schumm, Phillip

2011-02-24

Recent study of complex networks has yielded many new insights into phenomenon such as social networks, the internet, and sexually transmitted infections. The purpose of this analysis is to examine the properties of a network created by the 'co-care' of patients within one region of the Veterans Health Affairs. Data were obtained for all outpatient visits from 1 October 2006 to 30 September 2008 within one large Veterans Integrated Service Network. Types of physician within each clinic were nodes connected by shared patients, with a weighted link representing the number of shared patients between each connected pair. Network metrics calculated included edge weights, node degree, node strength, node coreness, and node betweenness. Log-log plots were used to examine the distribution of these metrics. Sizes of k-core networks were also computed under multiple conditions of node removal. There were 4,310,465 encounters by 266,710 shared patients between 722 provider types (nodes) across 41 stations or clinics resulting in 34,390 edges. The number of other nodes to which primary care provider nodes have a connection (172.7) is 42% greater than that of general surgeons and two and one-half times as high as cardiology. The log-log plot of the edge weight distribution appears to be linear in nature, revealing a 'scale-free' characteristic of the network, while the distributions of node degree and node strength are less so. The analysis of the k-core network sizes under increasing removal of primary care nodes shows that about 10 most connected primary care nodes play a critical role in keeping the k-core networks connected, because their removal disintegrates the highest k-core network. Delivery of healthcare in a large healthcare system such as that of the US Department of Veterans Affairs (VA) can be represented as a complex network. This network consists of highly connected provider nodes that serve as 'hubs' within the network, and demonstrates some 'scale-free' properties. By using currently available tools to explore its topology, we can explore how the underlying connectivity of such a system affects the behavior of providers, and perhaps leverage that understanding to improve quality and outcomes of care.

Identification of hybrid node and link communities in complex networks

PubMed Central

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-01-01

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately. PMID:25728010

Identification of hybrid node and link communities in complex networks.

PubMed

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-02

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

Identification of hybrid node and link communities in complex networks

NASA Astrophysics Data System (ADS)

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-01

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

The effects of malicious nodes on performance of mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Li, Fanzhi; Shi, Xiyu; Jassim, Sabah; Adams, Christopher

2006-05-01

Wireless ad hoc networking offers convenient infrastructureless communication over the shared wireless channel. However, the nature of ad hoc networks makes them vulnerable to security attacks. Unlike their wired counterpart, infrastructureless ad hoc networks do not have a clear line of defense, their topology is dynamically changing, and every mobile node can receive messages from its neighbors and can be contacted by all other nodes in its neighborhood. This poses a great danger to network security if some nodes behave in a malicious manner. The immediate concern about the security in this type of networks is how to protect the network and the individual mobile nodes against malicious act of rogue nodes from within the network. This paper is concerned with security aspects of wireless ad hoc networks. We shall present results of simulation experiments on ad hoc network's performance in the presence of malicious nodes. We shall investigate two types of attacks and the consequences will be simulated and quantified in terms of loss of packets and other factors. The results show that network performance, in terms of successful packet delivery ratios, significantly deteriorates when malicious nodes act according to the defined misbehaving characteristics.

Information transmission on hybrid networks

NASA Astrophysics Data System (ADS)

Chen, Rongbin; Cui, Wei; Pu, Cunlai; Li, Jie; Ji, Bo; Gakis, Konstantinos; Pardalos, Panos M.

2018-01-01

Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. The fixed nodes (base stations) are connected as a spatial lattice on the plane forming the information-carrying backbone, while the mobile nodes (users), which are the sources and destinations of information packets, connect to their current nearest fixed nodes respectively to deliver and receive information packets. We observe the phase transition of traffic load in the hybrid network when the packet generation rate goes from below and then above a critical value, which measures the network capacity of packets delivery. We obtain the optimal speed of moving nodes leading to the maximum network capacity. We further improve the network capacity by rewiring the fixed nodes and by considering the current load of fixed nodes during packets transmission. Our purpose is to optimize the network capacity of hybrid networks from the perspective of network science, and provide some insights for the construction of future communication infrastructures.

Hemispheric asymmetry of electroencephalography-based functional brain networks.

PubMed

Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Value of peripheral nodes in controlling multilayer scale-free networks

NASA Astrophysics Data System (ADS)

Zhang, Yan; Garas, Antonios; Schweitzer, Frank

2016-01-01

We analyze the controllability of a two-layer network, where driver nodes can be chosen randomly only from one layer. Each layer contains a scale-free network with directed links and the node dynamics depends on the incoming links from other nodes. We combine the in-degree and out-degree values to assign an importance value w to each node, and distinguish between peripheral nodes with low w and central nodes with high w . Based on numerical simulations, we find that the controllable part of the network is larger when choosing low w nodes to connect the two layers. The control is as efficient when peripheral nodes are driver nodes as it is for the case of more central nodes. However, if we assume a cost to utilize nodes that is proportional to their overall degree, utilizing peripheral nodes to connect the two layers or to act as driver nodes is not only the most cost-efficient solution, it is also the one that performs best in controlling the two-layer network among the different interconnecting strategies we have tested.

Multi-attribute integrated measurement of node importance in complex networks.

PubMed

Wang, Shibo; Zhao, Jinlou

2015-11-01

The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

Coupling effect of nodes popularity and similarity on social network persistence

PubMed Central

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-01-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology. PMID:28220840

Coupling effect of nodes popularity and similarity on social network persistence

NASA Astrophysics Data System (ADS)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Virulence genes and plasmid profiles in Rhodococcus equi isolates from domestic pigs and wild boars (Sus scrofa) in Brazil.

PubMed

Ribeiro, Márcio Garcia; Takai, Shinji; Guazzelli, Alessandro; Lara, Gustavo Henrique Batista; da Silva, Aristeu Vieira; Fernandes, Marta Catarina; Condas, Larissa Anuska Zeni; Siqueira, Amanda Keller; Salerno, Tatiana

2011-12-01

The virulence genes and plasmid profiles of 23 Rhodococcus equi isolates from 258 lymph nodes from domestic pigs (129 nodes with lesions and 129 without lesions) and 120 lymph nodes from slaughtered wild boars (60 nodes with lesions and 60 without) were characterized. R. equi was obtained from 19 lymph nodes of domestic pigs, 17 with, and two without lesions, and from four lymph nodes with lesions, from wild boars. The 23 isolates were tested for the presence of vapA and vapB genes, responsible for the 15-17 and 20 kDa virulence-associated proteins, respectively, by PCR in order to characterize as virulent (VapA), intermediately virulent (VapB) and avirulent. Plasmid DNAs were isolated and analyzed by digestion with restriction endonucleases to estimate size and compare their polymorphisms. Of the 19 domestic pigs strains, seven (36.8%) were avirulent and 12 (63.2%) were intermediately virulent, with the intermediately virulent isolates being plasmid types 8 (8 isolates), 10 (2 isolates), 1 (1 isolate) and 29 (1 isolate). The plasmid type of four strains isolated from wild boars was also intermediately virulent type 8. None of the domestic pigs and wild boar isolates showed the vapA gene. These findings demonstrate a high occurrence of plasmid type 8 in isolates from pigs and wild boars, and the similarity of plasmid types in the domestic pigs, wild boars and human isolates in Brazil. Copyright © 2010 Elsevier Ltd. All rights reserved.

Error recovery to enable error-free message transfer between nodes of a computer network

DOEpatents

Blumrich, Matthias A.; Coteus, Paul W.; Chen, Dong; Gara, Alan; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd; Steinmacher-Burow, Burkhard; Vranas, Pavlos M.

2016-01-26

An error-recovery method to enable error-free message transfer between nodes of a computer network. A first node of the network sends a packet to a second node of the network over a link between the nodes, and the first node keeps a copy of the packet on a sending end of the link until the first node receives acknowledgment from the second node that the packet was received without error. The second node tests the packet to determine if the packet is error free. If the packet is not error free, the second node sets a flag to mark the packet as corrupt. The second node returns acknowledgement to the first node specifying whether the packet was received with or without error. When the packet is received with error, the link is returned to a known state and the packet is sent again to the second node.

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by dynamically adjusting local routing strategies

DOEpatents

Archer, Charles Jens; Musselman, Roy Glenn; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen; Wallenfelt, Brian Paul

2010-03-16

A massively parallel computer system contains an inter-nodal communications network of node-to-node links. Each node implements a respective routing strategy for routing data through the network, the routing strategies not necessarily being the same in every node. The routing strategies implemented in the nodes are dynamically adjusted during application execution to shift network workload as required. Preferably, adjustment of routing policies in selective nodes is performed at synchronization points. The network may be dynamically monitored, and routing strategies adjusted according to detected network conditions.

Summarisation of weighted networks

NASA Astrophysics Data System (ADS)

Zhou, Fang; Qu, Qiang; Toivonen, Hannu

2017-09-01

Networks often contain implicit structure. We introduce novel problems and methods that look for structure in networks, by grouping nodes into supernodes and edges to superedges, and then make this structure visible to the user in a smaller generalised network. This task of finding generalisations of nodes and edges is formulated as 'network Summarisation'. We propose models and algorithms for networks that have weights on edges, on nodes or on both, and study three new variants of the network summarisation problem. In edge-based weighted network summarisation, the summarised network should preserve edge weights as well as possible. A wider class of settings is considered in path-based weighted network summarisation, where the resulting summarised network should preserve longer range connectivities between nodes. Node-based weighted network summarisation in turn allows weights also on nodes and summarisation aims to preserve more information related to high weight nodes. We study theoretical properties of these problems and show them to be NP-hard. We propose a range of heuristic generalisation algorithms with different trade-offs between complexity and quality of the result. Comprehensive experiments on real data show that weighted networks can be summarised efficiently with relatively little error.

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-06-08

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-11-23

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Compressive sensing of high betweenness centrality nodes in networks

NASA Astrophysics Data System (ADS)

Mahyar, Hamidreza; Hasheminezhad, Rouzbeh; Ghalebi K., Elahe; Nazemian, Ali; Grosu, Radu; Movaghar, Ali; Rabiee, Hamid R.

2018-05-01

Betweenness centrality is a prominent centrality measure expressing importance of a node within a network, in terms of the fraction of shortest paths passing through that node. Nodes with high betweenness centrality have significant impacts on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. Thus, identifying k-highest betweenness centrality nodes in networks will be of great interest in many applications. In this paper, we introduce CS-HiBet, a new method to efficiently detect top- k betweenness centrality nodes in networks, using compressive sensing. CS-HiBet can perform as a distributed algorithm by using only the local information at each node. Hence, it is applicable to large real-world and unknown networks in which the global approaches are usually unrealizable. The performance of the proposed method is evaluated by extensive simulations on several synthetic and real-world networks. The experimental results demonstrate that CS-HiBet outperforms the best existing methods with notable improvements.

Vulnerability of networks of interacting Markov chains.

PubMed

Kocarev, L; Zlatanov, N; Trajanov, D

2010-05-13

The concept of vulnerability is introduced for a model of random, dynamical interactions on networks. In this model, known as the influence model, the nodes are arranged in an arbitrary network, while the evolution of the status at a node is according to an internal Markov chain, but with transition probabilities that depend not only on the current status of that node but also on the statuses of the neighbouring nodes. Vulnerability is treated analytically and numerically for several networks with different topological structures, as well as for two real networks--the network of infrastructures and the EU power grid--identifying the most vulnerable nodes of these networks.

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Analyses of the response of a complex weighted network to nodes removal strategies considering links weight: The case of the Beijing urban road system

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Lu, Zhe-Ming; Cassi, Davide; Scotognella, Francesco

2018-02-01

Complex network response to node loss is a central question in different fields of science ranging from physics, sociology, biology to ecology. Previous studies considered binary networks where the weight of the links is not accounted for. However, in real-world networks the weights of connections can be widely different. Here, we analyzed the response of real-world road traffic complex network of Beijing, the most prosperous city in China. We produced nodes removal attack simulations using classic binary node features and we introduced weighted ranks for node importance. We measured the network functioning during nodes removal with three different parameters: the size of the largest connected cluster (LCC), the binary network efficiency (Bin EFF) and the weighted network efficiency (Weg EFF). We find that removing nodes according to weighted rank, i.e. considering the weight of the links as a number of taxi flows along the roads, produced in general the highest damage in the system. Our results show that: (i) in order to model Beijing road complex networks response to nodes (intersections) failure, it is necessary to consider the weight of the links; (ii) to discover the best attack strategy, it is important to use nodes rank accounting links weight.

Configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks

DOEpatents

Archer, Charles J.; Inglett, Todd A.; Ratterman, Joseph D.; Smith, Brian E.

2010-03-02

Methods, apparatus, and products are disclosed for configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks, the compute nodes in the operational group connected together for data communications through a global combining network, that include: partitioning the compute nodes in the operational group into a plurality of non-overlapping subgroups; designating one compute node from each of the non-overlapping subgroups as a master node; and assigning, to the compute nodes in each of the non-overlapping subgroups, class routing instructions that organize the compute nodes in that non-overlapping subgroup as a collective network such that the master node is a physical root.

Evaluating nodes importance in complex network based on PageRank algorithm

NASA Astrophysics Data System (ADS)

Li, Kai; He, Yongfeng

2018-04-01

To evaluate the important nodes in the complex network, and aim at the problems existing in the traditional PageRank algorithm, we propose a modified PageRank algorithm. The algorithm has convergence for the evaluation of the importance of the suspended nodes and the nodes with a directed loop network. The simulation example shows the effectiveness of the modified algorithm for the evaluation of the complexity of the complex network nodes.

A Novel Cooperative Opportunistic Routing Scheme for Underwater Sensor Networks.

PubMed

Ghoreyshi, Seyed Mohammad; Shahrabi, Alireza; Boutaleb, Tuleen

2016-02-26

Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodes' collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance.

Development of climate data storage and processing model

NASA Astrophysics Data System (ADS)

Okladnikov, I. G.; Gordov, E. P.; Titov, A. G.

2016-11-01

We present a storage and processing model for climate datasets elaborated in the framework of a virtual research environment (VRE) for climate and environmental monitoring and analysis of the impact of climate change on the socio-economic processes on local and regional scales. The model is based on a «shared nothings» distributed computing architecture and assumes using a computing network where each computing node is independent and selfsufficient. Each node holds a dedicated software for the processing and visualization of geospatial data providing programming interfaces to communicate with the other nodes. The nodes are interconnected by a local network or the Internet and exchange data and control instructions via SSH connections and web services. Geospatial data is represented by collections of netCDF files stored in a hierarchy of directories in the framework of a file system. To speed up data reading and processing, three approaches are proposed: a precalculation of intermediate products, a distribution of data across multiple storage systems (with or without redundancy), and caching and reuse of the previously obtained products. For a fast search and retrieval of the required data, according to the data storage and processing model, a metadata database is developed. It contains descriptions of the space-time features of the datasets available for processing, their locations, as well as descriptions and run options of the software components for data analysis and visualization. The model and the metadata database together will provide a reliable technological basis for development of a high- performance virtual research environment for climatic and environmental monitoring.

Global tree network for computing structures enabling global processing operations

DOEpatents

Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

2010-01-19

A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

Identifying influential nodes in complex networks: A node information dimension approach

NASA Astrophysics Data System (ADS)

Bian, Tian; Deng, Yong

2018-04-01

In the field of complex networks, how to identify influential nodes is a significant issue in analyzing the structure of a network. In the existing method proposed to identify influential nodes based on the local dimension, the global structure information in complex networks is not taken into consideration. In this paper, a node information dimension is proposed by synthesizing the local dimensions at different topological distance scales. A case study of the Netscience network is used to illustrate the efficiency and practicability of the proposed method.

GFT centrality: A new node importance measure for complex networks

NASA Astrophysics Data System (ADS)

Singh, Rahul; Chakraborty, Abhishek; Manoj, B. S.

2017-12-01

Identifying central nodes is very crucial to design efficient communication networks or to recognize key individuals of a social network. In this paper, we introduce Graph Fourier Transform Centrality (GFT-C), a metric that incorporates local as well as global characteristics of a node, to quantify the importance of a node in a complex network. GFT-C of a reference node in a network is estimated from the GFT coefficients derived from the importance signal of the reference node. Our study reveals the superiority of GFT-C over traditional centralities such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and Google PageRank centrality, in the context of various arbitrary and real-world networks with different degree-degree correlations.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

PubMed

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

Asynchronous reference frame agreement in a quantum network

NASA Astrophysics Data System (ADS)

Islam, Tanvirul; Wehner, Stephanie

2016-03-01

An efficient implementation of many multiparty protocols for quantum networks requires that all the nodes in the network share a common reference frame. Establishing such a reference frame from scratch is especially challenging in an asynchronous network where network links might have arbitrary delays and the nodes do not share synchronised clocks. In this work, we study the problem of establishing a common reference frame in an asynchronous network of n nodes of which at most t are affected by arbitrary unknown error, and the identities of the faulty nodes are not known. We present a protocol that allows all the correctly functioning nodes to agree on a common reference frame as long as the network graph is complete and not more than t\\lt n/4 nodes are faulty. As the protocol is asynchronous, it can be used with some assumptions to synchronise clocks over a network. Also, the protocol has the appealing property that it allows any existing two-node asynchronous protocol for reference frame agreement to be lifted to a robust protocol for an asynchronous quantum network.

Automatic Network Fingerprinting through Single-Node Motifs

PubMed Central

Echtermeyer, Christoph; da Fontoura Costa, Luciano; Rodrigues, Francisco A.; Kaiser, Marcus

2011-01-01

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs—a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks. PMID:21297963

Strategies for synchronisation in an evolving telecommunications network

NASA Astrophysics Data System (ADS)

Avery, Rob

1992-06-01

The achievement of precise synchronization in the telecommunications environment is addressed. Transmitting the timing from node to node has been the inherent problem for all digital networks. Traditional network equipment used to transfer synchronization, such as digital switching ststems, adds impairments to the once traceable signal. As the synchronization signals are passed from node to node, they lose stability by passing through intervening clocks. Timing would be an integrated part of all new network and service deployments. New transmission methods, such as the Synchronous Digital Hierarchy (SDH), survivable network topologies and the issues that arise from them, necessitate a review of current network synchronization strategies. Challenges that face the network are itemized. A demonstration of why localized Primary Reference Clocks (PRC) in key nodes and the Synchronization Supply Unit (SSU) clock architecture of transit and local node clocks is a technically and economically viable solution to the issues facing network planners today is given.

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

High speed polling protocol for multiple node network with sequential flooding of a polling message and a poll-answering message

NASA Technical Reports Server (NTRS)

Marvit, Maclen (Inventor); Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs a remote node polling process performed by a master node by transmitting a polling message generically addressed to all remote nodes associated with the master node. Each remote node responds upon receipt of the generically addressed polling message by sequentially flooding the network with a poll-answering informational message and with the polling message.

Cross-Layer Resource Allocation for Wireless Visual Sensor Networks and Mobile Ad Hoc Networks

DTIC Science & Technology

2014-10-01

MMD), minimizes the maximum dis- tortion among all nodes of the network, promoting a rather unbiased treatment of the nodes. We employed the Particle...achieve the ideal tradeoff between the transmitted video quality and energy consumption. Each sensor node has a bit rate that can be used for both...Distortion (MMD), minimizes the maximum distortion among all nodes of the network, promoting a rather unbiased treatment of the nodes. For both criteria

Unified study of Quality of Service (QoS) in OPS/OBS networks

NASA Astrophysics Data System (ADS)

Hailu, Dawit Hadush; Lema, Gebrehiwet Gebrekrstos; Yekun, Ephrem Admasu; Kebede, Samrawit Haylu

2017-07-01

With the growth of Internet traffic, an inevitable use of optical networks provide a large bandwidth, fast data transmission rates and Quality of Service (QoS) support. Currently, Optical Burst Switched (OBS)/Optical Packet Switched (OPS) networks are under study as future solutions for addressing the increase demand of Internet traffic. However, due to their high blocking probability in the intermediate nodes they have been delayed in the industries. Packet loss in OBS/OPS networks is mainly occur due to contention. Hence, the contribution of this study is to analyze the file loss ratio (FLR), packet overhead and number of disjoint paths, and processing delay over Coded Packet Transport (CPT) scheme for OBS/OPS network using simulation. The simulations show that CPT scheme reduces the FLR in OBS/OPS network for the evaluated scenarios since the data packets are chopped off into blocks of the data packet for transmission over a network. Simulation results for secrecy and survivability are verified with the help of the analytical model to define the operational range of CPT scheme.

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

WDM Network and Multicasting Protocol Strategies

PubMed Central

Zaim, Abdul Halim

2014-01-01

Optical technology gains extensive attention and ever increasing improvement because of the huge amount of network traffic caused by the growing number of internet users and their rising demands. However, with wavelength division multiplexing (WDM), it is easier to take the advantage of optical networks and optical burst switching (OBS) and to construct WDM networks with low delay rates and better data transparency these technologies are the best choices. Furthermore, multicasting in WDM is an urgent solution for bandwidth-intensive applications. In the paper, a new multicasting protocol with OBS is proposed. The protocol depends on a leaf initiated structure. The network is composed of source, ingress switches, intermediate switches, edge switches, and client nodes. The performance of the protocol is examined with Just Enough Time (JET) and Just In Time (JIT) reservation protocols. Also, the paper involves most of the recent advances about WDM multicasting in optical networks. WDM multicasting in optical networks is given as three common subtitles: Broadcast and-select networks, wavelength-routed networks, and OBS networks. Also, in the paper, multicast routing protocols are briefly summarized and optical burst switched WDM networks are investigated with the proposed multicast schemes. PMID:24744683

A constraint optimization based virtual network mapping method

NASA Astrophysics Data System (ADS)

Li, Xiaoling; Guo, Changguo; Wang, Huaimin; Li, Zhendong; Yang, Zhiwen

2013-03-01

Virtual network mapping problem, maps different virtual networks onto the substrate network is an extremely challenging work. This paper proposes a constraint optimization based mapping method for solving virtual network mapping problem. This method divides the problem into two phases, node mapping phase and link mapping phase, which are all NP-hard problems. Node mapping algorithm and link mapping algorithm are proposed for solving node mapping phase and link mapping phase, respectively. Node mapping algorithm adopts the thinking of greedy algorithm, mainly considers two factors, available resources which are supplied by the nodes and distance between the nodes. Link mapping algorithm is based on the result of node mapping phase, adopts the thinking of distributed constraint optimization method, which can guarantee to obtain the optimal mapping with the minimum network cost. Finally, simulation experiments are used to validate the method, and results show that the method performs very well.

Study on the effect of sink moving trajectory on wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhong, Peijun; Ruan, Feng

2018-03-01

Wireless sensor networks are developing very fast in recent years, due to their wide potential applications. However there exists the so-called hot spot problem, namely the nodes close to static sink node tend to die earlier than other nodes since they have heavier burden to forward. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we make extensive experimental simulations for circular sensor network, with one mobile sink moving along different radius circumference. The whole network is divided into several clusters and there is one cluster head (CH) inside each cluster. The ordinary sensors communicate with CH and CHs construct a chain until the sink node. Simulation results show that the best network performance appears when sink moves along 0.25 R in terms of network lifetime.

Cascade phenomenon against subsequent failures in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liu, Zhi-Quan; He, Xuan; Ma, Jian-Feng

2018-06-01

Cascade phenomenon may lead to catastrophic disasters which extremely imperil the network safety or security in various complex systems such as communication networks, power grids, social networks and so on. In some flow-based networks, the load of failed nodes can be redistributed locally to their neighboring nodes to maximally preserve the traffic oscillations or large-scale cascading failures. However, in such local flow redistribution model, a small set of key nodes attacked subsequently can result in network collapse. Then it is a critical problem to effectively find the set of key nodes in the network. To our best knowledge, this work is the first to study this problem comprehensively. We first introduce the extra capacity for every node to put up with flow fluctuations from neighbors, and two extra capacity distributions including degree based distribution and average distribution are employed. Four heuristic key nodes discovering methods including High-Degree-First (HDF), Low-Degree-First (LDF), Random and Greedy Algorithms (GA) are presented. Extensive simulations are realized in both scale-free networks and random networks. The results show that the greedy algorithm can efficiently find the set of key nodes in both scale-free and random networks. Our work studies network robustness against cascading failures from a very novel perspective, and methods and results are very useful for network robustness evaluations and protections.

Improvement of the SEP protocol based on community structure of node degree

NASA Astrophysics Data System (ADS)

Li, Donglin; Wei, Suyuan

2017-05-01

Analyzing the Stable election protocol (SEP) in wireless sensor networks and aiming at the problem of inhomogeneous cluster-heads distribution and unreasonable cluster-heads selectivity and single hop transmission in the SEP, a SEP Protocol based on community structure of node degree (SEP-CSND) is proposed. In this algorithm, network node deployed by using grid deployment model, and the connection between nodes established by setting up the communication threshold. The community structure constructed by node degree, then cluster head is elected in the community structure. On the basis of SEP, the node's residual energy and node degree is added in cluster-heads election. The information is transmitted with mode of multiple hops between network nodes. The simulation experiments showed that compared to the classical LEACH and SEP, this algorithm balances the energy consumption of the entire network and significantly prolongs network lifetime.

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

PubMed Central

Jebaseeli Samuelraj, Ananthi; Jayapal, Sundararajan

2015-01-01

Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point. PMID:26366431

Effect of node attributes on the temporal dynamics of network structure

NASA Astrophysics Data System (ADS)

Momeni, Naghmeh; Fotouhi, Babak

2017-03-01

Many natural and social networks evolve in time and their structures are dynamic. In most networks, nodes are heterogeneous, and their roles in the evolution of structure differ. This paper focuses on the role of individual attributes on the temporal dynamics of network structure. We focus on a basic model for growing networks that incorporates node attributes (which we call "quality"), and we focus on the problem of forecasting the structural properties of the network in arbitrary times for an arbitrary initial network. That is, we address the following question: If we are given a certain initial network with given arbitrary structure and known node attributes, then how does the structure change in time as new nodes with given distribution of attributes join the network? We solve the model analytically and obtain the quality-degree joint distribution and degree correlations. We characterize the role of individual attributes in the position of individual nodes in the hierarchy of connections. We confirm the theoretical findings with Monte Carlo simulations.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

PubMed

Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

2015-01-01

Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

node2vec: Scalable Feature Learning for Networks

PubMed Central

Grover, Aditya; Leskovec, Jure

2016-01-01

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node’s network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks. PMID:27853626

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks.

PubMed

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-08

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

PubMed Central

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-01

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. PMID:29316702

Eradicating catastrophic collapse in interdependent networks via reinforced nodes

PubMed Central

Yuan, Xin; Hu, Yanqing; Havlin, Shlomo

2017-01-01

In interdependent networks, it is usually assumed, based on percolation theory, that nodes become nonfunctional if they lose connection to the network giant component. However, in reality, some nodes, equipped with alternative resources, together with their connected neighbors can still be functioning after disconnected from the giant component. Here, we propose and study a generalized percolation model that introduces a fraction of reinforced nodes in the interdependent networks that can function and support their neighborhood. We analyze, both analytically and via simulations, the order parameter—the functioning component—comprising both the giant component and smaller components that include at least one reinforced node. Remarkably, it is found that, for interdependent networks, we need to reinforce only a small fraction of nodes to prevent abrupt catastrophic collapses. Moreover, we find that the universal upper bound of this fraction is 0.1756 for two interdependent Erdős–Rényi (ER) networks: regular random (RR) networks and scale-free (SF) networks with large average degrees. We also generalize our theory to interdependent networks of networks (NONs). These findings might yield insight for designing resilient interdependent infrastructure networks. PMID:28289204

Lambda network having 2.sup.m-1 nodes in each of m stages with each node coupled to four other nodes for bidirectional routing of data packets between nodes

DOEpatents

Napolitano, Jr., Leonard M.

1995-01-01

The Lambda network is a single stage, packet-switched interprocessor communication network for a distributed memory, parallel processor computer. Its design arises from the desired network characteristics of minimizing mean and maximum packet transfer time, local routing, expandability, deadlock avoidance, and fault tolerance. The network is based on fixed degree nodes and has mean and maximum packet transfer distances where n is the number of processors. The routing method is detailed, as are methods for expandability, deadlock avoidance, and fault tolerance.

Measures of node centrality in mobile social networks

NASA Astrophysics Data System (ADS)

Gao, Zhenxiang; Shi, Yan; Chen, Shanzhi

2015-02-01

Mobile social networks exploit human mobility and consequent device-to-device contact to opportunistically create data paths over time. While links in mobile social networks are time-varied and strongly impacted by human mobility, discovering influential nodes is one of the important issues for efficient information propagation in mobile social networks. Although traditional centrality definitions give metrics to identify the nodes with central positions in static binary networks, they cannot effectively identify the influential nodes for information propagation in mobile social networks. In this paper, we address the problems of discovering the influential nodes in mobile social networks. We first use the temporal evolution graph model which can more accurately capture the topology dynamics of the mobile social network over time. Based on the model, we explore human social relations and mobility patterns to redefine three common centrality metrics: degree centrality, closeness centrality and betweenness centrality. We then employ empirical traces to evaluate the benefits of the proposed centrality metrics, and discuss the predictability of nodes' global centrality ranking by nodes' local centrality ranking. Results demonstrate the efficiency of the proposed centrality metrics.

Trust recovery model of Ad Hoc network based on identity authentication scheme

NASA Astrophysics Data System (ADS)

Liu, Jie; Huan, Shuiyuan

2017-05-01

Mobile Ad Hoc network trust model is widely used to solve mobile Ad Hoc network security issues. Aiming at the problem of reducing the network availability caused by the processing of malicious nodes and selfish nodes in mobile Ad Hoc network routing based on trust model, an authentication mechanism based on identity authentication mobile Ad Hoc network is proposed, which uses identity authentication to identify malicious nodes, And trust the recovery of selfish nodes in order to achieve the purpose of reducing network congestion and improving network quality. The simulation results show that the implementation of the mechanism can effectively improve the network availability and security.

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

2017-04-01

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

Multi-hop teleportation based on W state and EPR pairs

NASA Astrophysics Data System (ADS)

Hai-Tao, Zhan; Xu-Tao, Yu; Pei-Ying, Xiong; Zai-Chen, Zhang

2016-05-01

Multi-hop teleportation has significant value due to long-distance delivery of quantum information. Many studies about multi-hop teleportation are based on Bell pairs, partially entangled pairs or W state. The possibility of multi-hop teleportation constituted by partially entangled pairs relates to the number of nodes. The possibility of multi-hop teleportation constituted by double W states is after n-hop teleportation. In this paper, a multi-hop teleportation scheme based on W state and EPR pairs is presented and proved. The successful possibility of quantum information transmitted hop by hop through intermediate nodes is deduced. The possibility of successful transmission is after n-hop teleportation. Project supported by the National Natural Science Foundation of China (Grant No. 61571105), the Prospective Future Network Project of Jiangsu Province, China (Grant No. BY2013095-1-18), and the Independent Project of State Key Laboratory of Millimeter Waves, China (Grant No. Z201504).

Deterministic Multi-hop Controlled Teleportation of Arbitrary Single-Qubit State

NASA Astrophysics Data System (ADS)

Peng, Jia-yin; Bai, Ming-qiang; Mo, Zhi-wen

2017-10-01

Multi-hop teleportation is of great significance due to long-distance delivery of quantum information and wireless quantum communication networks. In existing protocols of multi-hop teleportation, the more nodes, the smaller the success probability. In this paper, fusing the ideas of multi-hop teleportation and controlled teleportation, we put forward a scheme for implementing multi-hop controlled teleportation of single-qubit state. A set of ingenious three-qubit non-maximally entangled states are constructed to serve as the quantum channels. The information is perfectly transmitted hop by hop through teleportation under the control of the supervisors. Unit success probability can be achieved independent of channel's entanglement degree and the number of intermediate nodes. Only Pauli operations, single-qubit rotation, Hadamard gate, controlled-NOT gate, Bell-state measurement and single-qubit measurement are used in our scheme, so this scheme is easily realized in physical experiment.

Growing optimal scale-free networks via likelihood

NASA Astrophysics Data System (ADS)

Small, Michael; Li, Yingying; Stemler, Thomas; Judd, Kevin

2015-04-01

Preferential attachment, by which new nodes attach to existing nodes with probability proportional to the existing nodes' degree, has become the standard growth model for scale-free networks, where the asymptotic probability of a node having degree k is proportional to k-γ. However, the motivation for this model is entirely ad hoc. We use exact likelihood arguments and show that the optimal way to build a scale-free network is to attach most new links to nodes of low degree. Curiously, this leads to a scale-free network with a single dominant hub: a starlike structure we call a superstar network. Asymptotically, the optimal strategy is to attach each new node to one of the nodes of degree k with probability proportional to 1/N +ζ (γ ) (k+1 ) γ (in a N node network): a stronger bias toward high degree nodes than exhibited by standard preferential attachment. Our algorithm generates optimally scale-free networks (the superstar networks) as well as randomly sampling the space of all scale-free networks with a given degree exponent γ . We generate viable realization with finite N for 1 ≪γ <2 as well as γ >2 . We observe an apparently discontinuous transition at γ ≈2 between so-called superstar networks and more treelike realizations. Gradually increasing γ further leads to reemergence of a superstar hub. To quantify these structural features, we derive a new analytic expression for the expected degree exponent of a pure preferential attachment process and introduce alternative measures of network entropy. Our approach is generic and can also be applied to an arbitrary degree distribution.

Locating multiple diffusion sources in time varying networks from sparse observations.

PubMed

Hu, Zhao-Long; Shen, Zhesi; Cao, Shinan; Podobnik, Boris; Yang, Huijie; Wang, Wen-Xu; Lai, Ying-Cheng

2018-02-08

Data based source localization in complex networks has a broad range of applications. Despite recent progress, locating multiple diffusion sources in time varying networks remains to be an outstanding problem. Bridging structural observability and sparse signal reconstruction theories, we develop a general framework to locate diffusion sources in time varying networks based solely on sparse data from a small set of messenger nodes. A general finding is that large degree nodes produce more valuable information than small degree nodes, a result that contrasts that for static networks. Choosing large degree nodes as the messengers, we find that sparse observations from a few such nodes are often sufficient for any number of diffusion sources to be located for a variety of model and empirical networks. Counterintuitively, sources in more rapidly varying networks can be identified more readily with fewer required messenger nodes.

Cascading failures in complex networks with community structure

NASA Astrophysics Data System (ADS)

Lin, Guoqiang; di, Zengru; Fan, Ying

2014-12-01

Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable. Understanding what will affect cascading failures and how to protect or attack networks with strong community structure is therefore of interest. In this paper, we have constructed scale-free Community Networks (SFCN) and Random Community Networks (RCN). We applied these networks, along with the Lancichinett-Fortunato-Radicchi (LFR) benchmark, to the cascading-failure scenario to explore their vulnerability to attack and the relationship between cascading failures and the degree distribution and community structure of a network. The numerical results show that when the networks are of a power-law distribution, a stronger community structure will result in the failure of fewer nodes. In addition, the initial removal of the node with the highest betweenness will not lead to the worst cascading, i.e. the largest avalanche size. The Betweenness Overflow (BOF), an index that we developed, is an effective indicator of this tendency. The RCN, however, display a different result. In addition, the avalanche size of each node can be adopted as an index to evaluate the importance of the node.

Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited

NASA Astrophysics Data System (ADS)

Lee, Youngseok; Mukherjee, Biswanath

2004-03-01

Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

A New Measure of Centrality for Brain Networks

PubMed Central

Joyce, Karen E.; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru

2010-01-01

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures. Degree identifies the most connected nodes, whereas betweenness centrality identifies those located on the most traveled paths. Eigenvector centrality considers nodes connected to other high degree nodes as highly central. In the work presented here, we propose a new centrality metric called leverage centrality that considers the extent of connectivity of a node relative to the connectivity of its neighbors. The leverage centrality of a node in a network is determined by the extent to which its immediate neighbors rely on that node for information. Although similar in concept, there are essential differences between eigenvector and leverage centrality that are discussed in this manuscript. Degree, betweenness, eigenvector, and leverage centrality were compared using functional brain networks generated from healthy volunteers. Functional cartography was also used to identify neighborhood hubs (nodes with high degree within a network neighborhood). Provincial hubs provide structure within the local community, and connector hubs mediate connections between multiple communities. Leverage proved to yield information that was not captured by degree, betweenness, or eigenvector centrality and was more accurate at identifying neighborhood hubs. We propose that this metric may be able to identify critical nodes that are highly influential within the network. PMID:20808943

Degree and wealth distribution in a network induced by wealth

NASA Astrophysics Data System (ADS)

Lee, Gyemin; Kim, Gwang Il

2007-09-01

A network induced by wealth is a social network model in which wealth induces individuals to participate as nodes, and every node in the network produces and accumulates wealth utilizing its links. More specifically, at every time step a new node is added to the network, and a link is created between one of the existing nodes and the new node. Innate wealth-producing ability is randomly assigned to every new node, and the node to be connected to the new node is chosen randomly, with odds proportional to the accumulated wealth of each existing node. Analyzing this network using the mean value and continuous flow approaches, we derive a relation between the conditional expectations of the degree and the accumulated wealth of each node. From this relation, we show that the degree distribution of the network induced by wealth is scale-free. We also show that the wealth distribution has a power-law tail and satisfies the 80/20 rule. We also show that, over the whole range, the cumulative wealth distribution exhibits the same topological characteristics as the wealth distributions of several networks based on the Bouchaud-Mèzard model, even though the mechanism for producing wealth is quite different in our model. Further, we show that the cumulative wealth distribution for the poor and middle class seems likely to follow by a log-normal distribution, while for the richest, the cumulative wealth distribution has a power-law behavior.

Multiplex PageRank.

PubMed

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Adaptive Connectivity Restoration from Node Failure(s) in Wireless Sensor Networks

PubMed Central

Wang, Huaiyuan; Ding, Xu; Huang, Cheng; Wu, Xiaobei

2016-01-01

Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA. PMID:27690030

Tracking trade transactions in water resource systems: A node-arc optimization formulation

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Huskova, Ivana; Harou, Julien J.

2013-05-01

We formulate and apply a multicommodity network flow node-arc optimization model capable of tracking trade transactions in complex water resource systems. The model uses a simple node to node network connectivity matrix and does not require preprocessing of all possible flow paths in the network. We compare the proposed node-arc formulation with an existing arc-path (flow path) formulation and explain the advantages and difficulties of both approaches. We verify the proposed formulation model on a hypothetical water distribution network. Results indicate the arc-path model solves the problem with fewer constraints, but the proposed formulation allows using a simple network connectivity matrix which simplifies modeling large or complex networks. The proposed algorithm allows converting existing node-arc hydroeconomic models that broadly represent water trading to ones that also track individual supplier-receiver relationships (trade transactions).

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

NASA Astrophysics Data System (ADS)

Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing

2018-03-01

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

Bluetooth-based wireless sensor networks

NASA Astrophysics Data System (ADS)

You, Ke; Liu, Rui Qiang

2007-11-01

In this work a Bluetooth-based wireless sensor network is proposed. In this bluetooth-based wireless sensor networks, information-driven star topology and energy-saved mode are used, through which a blue master node can control more than seven slave node, the energy of each sensor node is reduced and secure management of each sensor node is improved.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Effects of network node consolidation in optical access and aggregation networks on costs and power consumption

NASA Astrophysics Data System (ADS)

Lange, Christoph; Hülsermann, Ralf; Kosiankowski, Dirk; Geilhardt, Frank; Gladisch, Andreas

2010-01-01

The increasing demand for higher bit rates in access networks requires fiber deployment closer to the subscriber resulting in fiber-to-the-home (FTTH) access networks. Besides higher access bit rates optical access network infrastructure and related technologies enable the network operator to establish larger service areas resulting in a simplified network structure with a lower number of network nodes. By changing the network structure network operators want to benefit from a changed network cost structure by decreasing in short and mid term the upfront investments for network equipment due to concentration effects as well as by reducing the energy costs due to a higher energy efficiency of large network sites housing a high amount of network equipment. In long term also savings in operational expenditures (OpEx) due to the closing of central office (CO) sites are expected. In this paper different architectures for optical access networks basing on state-of-the-art technology are analyzed with respect to network installation costs and power consumption in the context of access node consolidation. Network planning and dimensioning results are calculated for a realistic network scenario of Germany. All node consolidation scenarios are compared against a gigabit capable passive optical network (GPON) based FTTH access network operated from the conventional CO sites. The results show that a moderate reduction of the number of access nodes may be beneficial since in that case the capital expenditures (CapEx) do not rise extraordinarily and savings in OpEx related to the access nodes are expected. The total power consumption does not change significantly with decreasing number of access nodes but clustering effects enable a more energyefficient network operation and optimized power purchase order quantities leading to benefits in energy costs.

Control range: a controllability-based index for node significance in directed networks

NASA Astrophysics Data System (ADS)

Wang, Bingbo; Gao, Lin; Gao, Yong

2012-04-01

While a large number of methods for module detection have been developed for undirected networks, it is difficult to adapt them to handle directed networks due to the lack of consensus criteria for measuring the node significance in a directed network. In this paper, we propose a novel structural index, the control range, motivated by recent studies on the structural controllability of large-scale directed networks. The control range of a node quantifies the size of the subnetwork that the node can effectively control. A related index, called the control range similarity, is also introduced to measure the structural similarity between two nodes. When applying the index of control range to several real-world and synthetic directed networks, it is observed that the control range of the nodes is mainly influenced by the network's degree distribution and that nodes with a low degree may have a high control range. We use the index of control range similarity to detect and analyze functional modules in glossary networks and the enzyme-centric network of homo sapiens. Our results, as compared with other approaches to module detection such as modularity optimization algorithm, dynamic algorithm and clique percolation method, indicate that the proposed indices are effective and practical in depicting structural and modular characteristics of sparse directed networks.

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005

Distributed Transforms for Efficient Data Gathering in Sensor Networks

NASA Technical Reports Server (NTRS)

Ortega, Antonio (Inventor); Shen, Godwin (Inventor); Narang, Sunil K. (Inventor); Perez-Trufero, Javier (Inventor)

2014-01-01

Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

Smoluchowski Equation for Networks: Merger Induced Intermittent Giant Node Formation and Degree Gap

NASA Astrophysics Data System (ADS)

Goto, Hayato; Viegas, Eduardo; Jensen, Henrik Jeldtoft; Takayasu, Hideki; Takayasu, Misako

2018-06-01

The dynamical phase diagram of a network undergoing annihilation, creation, and coagulation of nodes is found to exhibit two regimes controlled by the combined effect of preferential attachment for initiator and target nodes during coagulation and for link assignment to new nodes. The first regime exhibits smooth dynamics and power law degree distributions. In the second regime, giant degree nodes and gaps in the degree distribution are formed intermittently. Data for the Japanese firm network in 1994 and 2014 suggests that this network is moving towards the intermittent switching region.

Methods and systems for detecting abnormal digital traffic

DOEpatents

Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

2011-03-22

Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

Ultrasonographic detection of regional lymph node metastases in patients with intermediate or thick malignant melanoma.

PubMed

Brountzos, Elias N; Panagiotou, Irene E; Bafaloukos, Dimitrios I; Kelekis, Dimitrios A

2003-01-01

Careful monitoring of regional lymph nodes and early detection of metastases in malignant melanoma patients has an impact on their survival, since it may permit beneficial surgical therapy. Palpation is routinely used in clinical practice. The value of ultrasonography for routine follow-up of melanoma patients, still, is not generally accepted. The aim of our study was to assess the sensitivity and specificity of ultrasound and clinical examination respectively, in the detection of melanoma regional node metastases. Additionally, we evaluated whether early detection of metastases improved overall survival. One hundred and forty-eight melanoma patients with an intermediate or thick primary lesion were followed between January 1997 and May 2001. Clinical examination and concomitant regional lymph node ultrasonography were performed, every 3-4 months. If suspicious findings were identified, regional lymph node dissection was undertaken. Forty-four from the initial 148 patients relapsed with regional lymph nodal metastases. In 11 patients (25%) palpation failed to reveal the disease and metastases were depicted only by ultrasonography. In only 1 patient ultrasonography was false-negative. The sensitivity and specificity of palpation were 72.7 and 97% respectively, while those of ultrasonography were 97.7 (p<0.001) and 98% respectively. Ultrasonography was more sensitive in detecting lymph node metastases in the axilla (100%) and the groin (93.3%). When overall survival of patients presenting with local-regional recurrence was calculated--depending on the number of involved lymph nodes--a survival benefit (p<0.05) was found for patients with only one lymph node metastasis. In conclusion, ultrasonography is superior to clinical examination in the early detection of regional lymph node metastases from an intermediate or thick malignant melanoma and should be a part of those patients' surveillance.

Modular sensor network node

DOEpatents

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

Lambda network having 2{sup m{minus}1} nodes in each of m stages with each node coupled to four other nodes for bidirectional routing of data packets between nodes

DOEpatents

Napolitano, L.M. Jr.

1995-11-28

The Lambda network is a single stage, packet-switched interprocessor communication network for a distributed memory, parallel processor computer. Its design arises from the desired network characteristics of minimizing mean and maximum packet transfer time, local routing, expandability, deadlock avoidance, and fault tolerance. The network is based on fixed degree nodes and has mean and maximum packet transfer distances where n is the number of processors. The routing method is detailed, as are methods for expandability, deadlock avoidance, and fault tolerance. 14 figs.

Multicasting based optical inverse multiplexing in elastic optical network.

PubMed

Guo, Bingli; Xu, Yingying; Zhu, Paikun; Zhong, Yucheng; Chen, Yuanxiang; Li, Juhao; Chen, Zhangyuan; He, Yongqi

2014-06-16

Optical multicasting based inverse multiplexing (IM) is introduced in spectrum allocation of elastic optical network to resolve the spectrum fragmentation problem, where superchannels could be split and fit into several discrete spectrum blocks in the intermediate node. We experimentally demonstrate it with a 1-to-7 optical superchannel multicasting module and selecting/coupling components. Also, simulation results show that, comparing with several emerging spectrum defragmentation solutions (e.g., spectrum conversion, split spectrum), IM could reduce blocking performance significantly but without adding too much system complexity as split spectrum. On the other hand, service fairness for traffic with different granularity of these schemes is investigated for the first time and it shows that IM performs better than spectrum conversion and almost as well as split spectrum, especially for smaller size traffic under light traffic intensity.

A new model for programming software in body sensor networks.

PubMed

de A Barbosa, Talles M G; Sene, Iwens G; da Rocha, Adson F; de O Nascimento, Francisco A A; Carvalho, Joao L A; Carvalho, Hervaldo S

2007-01-01

A Body Sensor Network (BSN) must be designed to work autonomously. On the other hand, BSNs need mechanisms that allow changes in their behavior in order to become a clinically useful tool. The purpose of this paper is to present a new programming model that will be useful for programming BSN sensor nodes. This model is based on an intelligent intermediate-level compiler. The main purpose of the proposed compiler is to increase the efficiency in system use, and to increase the lifetime of the application, considering its requirements, hardware possibilities and specialist knowledge. With this model, it is possible to maintain the autonomous operation capability of the BSN and still offer tools that allow users with little grasp on programming techniques to program these systems.

Compressed sensing based missing nodes prediction in temporal communication network

NASA Astrophysics Data System (ADS)

Cheng, Guangquan; Ma, Yang; Liu, Zhong; Xie, Fuli

2018-02-01

The reconstruction of complex network topology is of great theoretical and practical significance. Most research so far focuses on the prediction of missing links. There are many mature algorithms for link prediction which have achieved good results, but research on the prediction of missing nodes has just begun. In this paper, we propose an algorithm for missing node prediction in complex networks. We detect the position of missing nodes based on their neighbor nodes under the theory of compressed sensing, and extend the algorithm to the case of multiple missing nodes using spectral clustering. Experiments on real public network datasets and simulated datasets show that our algorithm can detect the locations of hidden nodes effectively with high precision.

Preferential attachment in evolutionary earthquake networks

NASA Astrophysics Data System (ADS)

Rezaei, Soghra; Moghaddasi, Hanieh; Darooneh, Amir Hossein

2018-04-01

Earthquakes as spatio-temporal complex systems have been recently studied using complex network theory. Seismic networks are dynamical networks due to addition of new seismic events over time leading to establishing new nodes and links to the network. Here we have constructed Iran and Italy seismic networks based on Hybrid Model and testified the preferential attachment hypothesis for the connection of new nodes which states that it is more probable for newly added nodes to join the highly connected nodes comparing to the less connected ones. We showed that the preferential attachment is present in the case of earthquakes network and the attachment rate has a linear relationship with node degree. We have also found the seismic passive points, the most probable points to be influenced by other seismic places, using their preferential attachment values.

A Very Large Area Network (VLAN) knowledge-base applied to space communication problems

NASA Technical Reports Server (NTRS)

Zander, Carol S.

1988-01-01

This paper first describes a hierarchical model for very large area networks (VLAN). Space communication problems whose solution could profit by the model are discussed and then an enhanced version of this model incorporating the knowledge needed for the missile detection-destruction problem is presented. A satellite network or VLAN is a network which includes at least one satellite. Due to the complexity, a compromise between fully centralized and fully distributed network management has been adopted. Network nodes are assigned to a physically localized group, called a partition. Partitions consist of groups of cell nodes with one cell node acting as the organizer or master, called the Group Master (GM). Coordinating the group masters is a Partition Master (PM). Knowledge is also distributed hierarchically existing in at least two nodes. Each satellite node has a back-up earth node. Knowledge must be distributed in such a way so as to minimize information loss when a node fails. Thus the model is hierarchical both physically and informationally.

Array Processing in the Cloud: the rasdaman Approach

NASA Astrophysics Data System (ADS)

Merticariu, Vlad; Dumitru, Alex

2015-04-01

The multi-dimensional array data model is gaining more and more attention when dealing with Big Data challenges in a variety of domains such as climate simulations, geographic information systems, medical imaging or astronomical observations. Solutions provided by classical Big Data tools such as Key-Value Stores and MapReduce, as well as traditional relational databases, proved to be limited in domains associated with multi-dimensional data. This problem has been addressed by the field of array databases, in which systems provide database services for raster data, without imposing limitations on the number of dimensions that a dataset can have. Examples of datasets commonly handled by array databases include 1-dimensional sensor data, 2-D satellite imagery, 3-D x/y/t image time series as well as x/y/z geophysical voxel data, and 4-D x/y/z/t weather data. And this can grow as large as simulations of the whole universe when it comes to astrophysics. rasdaman is a well established array database, which implements many optimizations for dealing with large data volumes and operation complexity. Among those, the latest one is intra-query parallelization support: a network of machines collaborate for answering a single array database query, by dividing it into independent sub-queries sent to different servers. This enables massive processing speed-ups, which promise solutions to research challenges on multi-Petabyte data cubes. There are several correlated factors which influence the speedup that intra-query parallelisation brings: the number of servers, the capabilities of each server, the quality of the network, the availability of the data to the server that needs it in order to compute the result and many more. In the effort of adapting the engine to cloud processing patterns, two main components have been identified: one that handles communication and gathers information about the arrays sitting on every server, and a processing unit responsible with dividing work among available nodes and executing operations on local data. The federation daemon collects and stores statistics from the other network nodes and provides real time updates about local changes. Information exchanged includes available datasets, CPU load and memory usage per host. The processing component is represented by the rasdaman server. Using information from the federation daemon it breaks queries into subqueries to be executed on peer nodes, ships them, and assembles the intermediate results. Thus, we define a rasdaman network node as a pair of a federation daemon and a rasdaman server. Any node can receive a query and will subsequently act as this query's dispatcher, so all peers are at the same level and there is no single point of failure. Should a node become inaccessible then the peers will recognize this and will not any longer consider this peer for distribution. Conversely, a peer at any time can join the network. To assess the feasibility of our approach, we deployed a rasdaman network in the Amazon Elastic Cloud environment on 1001 nodes, and observed that this feature can greatly increase the performance and scalability of the system, offering a large throughput of processed data.

Exploring the evolution of node neighborhoods in Dynamic Networks

NASA Astrophysics Data System (ADS)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

I/O routing in a multidimensional torus network

DOEpatents

Chen, Dong; Eisley, Noel A.; Heidelberger, Philip

2017-02-07

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

I/O routing in a multidimensional torus network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Eisley, Noel A.; Heidelberger, Philip

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destinationmore » address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.« less

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Simultaneous energy harvesting and information processing in wireless multiple relays with multiple antennas

NASA Astrophysics Data System (ADS)

Albaaj, Azhar; Makki, S. Vahab A.; Alabkhat, Qassem; Zahedi, Abdulhamid

2017-07-01

Wireless networks suffer from battery discharging specially in cooperative communications when multiple relays have an important role but they are energy constrained. To overcome this problem, energy harvesting from radio frequency signals is applied to charge the node battery. These intermediate nodes have the ability to harvest energy from the source signal and use the energy harvested to transmit information to the destination. In fact, the node tries to harvest energy and then transmit the data to destination. Division of energy harvesting and data transmission can be done in two algorithms: time-switching-based relaying protocol and power-splitting-based relaying protocol. These two algorithms also can be applied in delay-limited and delay-tolerant transmission systems. The previous works have assumed a single relay for energy harvesting, but in this article, the proposed method is concentrated on improving the outage probability and throughput by using multiple antennas in each relay node instead of using single antenna. According to our simulation results, when using multi-antenna relays, ability of energy harvesting is increased and thus system performance will be improved to great extent. Maximum ratio combining scheme has been used when the destination chooses the best signal of relays and antennas satisfying the required signal-to-noise ratio.

Complex networks repair strategies: Dynamic models

NASA Astrophysics Data System (ADS)

Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang

2017-09-01

Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree 〈 k 〉 and enhances network invulnerability.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

Infectious disease control using contact tracing in random and scale-free networks

PubMed Central

Kiss, Istvan Z; Green, Darren M; Kao, Rowland R

2005-01-01

Contact tracing aims to identify and isolate individuals that have been in contact with infectious individuals. The efficacy of contact tracing and the hierarchy of traced nodes—nodes with higher degree traced first—is investigated and compared on random and scale-free (SF) networks with the same number of nodes N and average connection K. For values of the transmission rate larger than a threshold, the final epidemic size on SF networks is smaller than that on corresponding random networks. While in random networks new infectious and traced nodes from all classes have similar average degrees, in SF networks the average degree of nodes that are in more advanced stages of the disease is higher at any given time. On SF networks tracing removes possible sources of infection with high average degree. However a higher tracing effort is required to control the epidemic than on corresponding random networks due to the high initial velocity of spread towards the highly connected nodes. An increased latency period fails to significantly improve contact tracing efficacy. Contact tracing has a limited effect if the removal rate of susceptible nodes is relatively high, due to the fast local depletion of susceptible nodes. PMID:16849217

A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks

PubMed Central

Lloret, Jaime; Garcia, Miguel; Bri, Diana; Diaz, Juan R.

2009-01-01

A wireless sensor network is a self-configuring network of mobile nodes connected by wireless links where the nodes have limited capacity and energy. In many cases, the application environment requires the design of an exclusive network topology for a particular case. Cluster-based network developments and proposals in existence have been designed to build a network for just one type of node, where all nodes can communicate with any other nodes in their coverage area. Let us suppose a set of clusters of sensor nodes where each cluster is formed by different types of nodes (e.g., they could be classified by the sensed parameter using different transmitting interfaces, by the node profile or by the type of device: laptops, PDAs, sensor etc.) and exclusive networks, as virtual networks, are needed with the same type of sensed data, or the same type of devices, or even the same type of profiles. In this paper, we propose an algorithm that is able to structure the topology of different wireless sensor networks to coexist in the same environment. It allows control and management of the topology of each network. The architecture operation and the protocol messages will be described. Measurements from a real test-bench will show that the designed protocol has low bandwidth consumption and also demonstrates the viability and the scalability of the proposed architecture. Our ccluster-based algorithm is compared with other algorithms reported in the literature in terms of architecture and protocol measurements. PMID:22303185

High speed polling protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs a remote node polling process performed by a master node by transmitting a polling message generically addressed to all remote nodes associated with the master node. Each remote node responds upon receipt of the generically addressed polling message by transmitting a poll-answering informational message and by relaying the polling message to other adjacent remote nodes.

Improved Efficient Routing Strategy on Scale-Free Networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liang, Man-Gui

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

Identifying and characterizing key nodes among communities based on electrical-circuit networks.

PubMed

Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying

2014-01-01

Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.

Dispatching packets on a global combining network of a parallel computer

DOEpatents

Almasi, Gheorghe [Ardsley, NY; Archer, Charles J [Rochester, MN

2011-07-19

Methods, apparatus, and products are disclosed for dispatching packets on a global combining network of a parallel computer comprising a plurality of nodes connected for data communications using the network capable of performing collective operations and point to point operations that include: receiving, by an origin system messaging module on an origin node from an origin application messaging module on the origin node, a storage identifier and an operation identifier, the storage identifier specifying storage containing an application message for transmission to a target node, and the operation identifier specifying a message passing operation; packetizing, by the origin system messaging module, the application message into network packets for transmission to the target node, each network packet specifying the operation identifier and an operation type for the message passing operation specified by the operation identifier; and transmitting, by the origin system messaging module, the network packets to the target node.

In-network Coding for Resilient Sensor Data Storage and Efficient Data Mule Collection

NASA Astrophysics Data System (ADS)

Albano, Michele; Gao, Jie

In a sensor network of n nodes in which k of them have sensed interesting data, we perform in-network erasure coding such that each node stores a linear combination of all the network data with random coefficients. This scheme greatly improves data resilience to node failures: as long as there are k nodes that survive an attack, all the data produced in the sensor network can be recovered with high probability. The in-network coding storage scheme also improves data collection rate by mobile mules and allows for easy scheduling of data mules.

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes

PubMed Central

Su, Ri-Qi; Wang, Wen-Xu; Wang, Xiao; Lai, Ying-Cheng

2016-01-01

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified. PMID:26909187

Optimization of robustness of interdependent network controllability by redundant design

PubMed Central

2018-01-01

Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy) or DBS (degree based strategy) for node backup and HDF(high degree first) for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability. PMID:29438426

Distribution of shortest path lengths in a class of node duplication network models

NASA Astrophysics Data System (ADS)

Steinbock, Chanania; Biham, Ofer; Katzav, Eytan

2017-09-01

We present analytical results for the distribution of shortest path lengths (DSPL) in a network growth model which evolves by node duplication (ND). The model captures essential properties of the structure and growth dynamics of social networks, acquaintance networks, and scientific citation networks, where duplication mechanisms play a major role. Starting from an initial seed network, at each time step a random node, referred to as a mother node, is selected for duplication. Its daughter node is added to the network, forming a link to the mother node, and with probability p to each one of its neighbors. The degree distribution of the resulting network turns out to follow a power-law distribution, thus the ND network is a scale-free network. To calculate the DSPL we derive a master equation for the time evolution of the probability Pt(L =ℓ ) , ℓ =1 ,2 ,⋯ , where L is the distance between a pair of nodes and t is the time. Finding an exact analytical solution of the master equation, we obtain a closed form expression for Pt(L =ℓ ) . The mean distance 〈L〉 t and the diameter Δt are found to scale like lnt , namely, the ND network is a small-world network. The variance of the DSPL is also found to scale like lnt . Interestingly, the mean distance and the diameter exhibit properties of a small-world network, rather than the ultrasmall-world network behavior observed in other scale-free networks, in which 〈L〉 t˜lnlnt .

Continuum Modeling and Control of Large Nonuniform Wireless Networks via Nonlinear Partial Differential Equations

DOE PAGES

Zhang, Yang; Chong, Edwin K. P.; Hannig, Jan; ...

2013-01-01

We inmore » troduce a continuum modeling method to approximate a class of large wireless networks by nonlinear partial differential equations (PDEs). This method is based on the convergence of a sequence of underlying Markov chains of the network indexed by N , the number of nodes in the network. As N goes to infinity, the sequence converges to a continuum limit, which is the solution of a certain nonlinear PDE. We first describe PDE models for networks with uniformly located nodes and then generalize to networks with nonuniformly located, and possibly mobile, nodes. Based on the PDE models, we develop a method to control the transmissions in nonuniform networks so that the continuum limit is invariant under perturbations in node locations. This enables the networks to maintain stable global characteristics in the presence of varying node locations.« less

Modeling Citation Networks Based on Vigorousness and Dormancy

NASA Astrophysics Data System (ADS)

Wang, Xue-Wen; Zhang, Li-Jie; Yang, Guo-Hong; Xu, Xin-Jian

2013-08-01

In citation networks, the activity of papers usually decreases with age and dormant papers may be discovered and become fashionable again. To model this phenomenon, a competition mechanism is suggested which incorporates two factors: vigorousness and dormancy. Based on this idea, a citation network model is proposed, in which a node has two discrete stage: vigorous and dormant. Vigorous nodes can be deactivated and dormant nodes may be activated and become vigorous. The evolution of the network couples addition of new nodes and state transitions of old ones. Both analytical calculation and numerical simulation show that the degree distribution of nodes in generated networks displays a good right-skewed behavior. Particularly, scale-free networks are obtained as the deactivated vertex is target selected and exponential networks are realized for the random-selected case. Moreover, the measurement of four real-world citation networks achieves a good agreement with the stochastic model.

Generalised power graph compression reveals dominant relationship patterns in complex networks

PubMed Central

Ahnert, Sebastian E.

2014-01-01

We introduce a framework for the discovery of dominant relationship patterns in complex networks, by compressing the networks into power graphs with overlapping power nodes. When paired with enrichment analysis of node classification terms, the most compressible sets of edges provide a highly informative sketch of the dominant relationship patterns that define the network. In addition, this procedure also gives rise to a novel, link-based definition of overlapping node communities in which nodes are defined by their relationships with sets of other nodes, rather than through connections within the community. We show that this completely general approach can be applied to undirected, directed, and bipartite networks, yielding valuable insights into the large-scale structure of real-world networks, including social networks and food webs. Our approach therefore provides a novel way in which network architecture can be studied, defined and classified. PMID:24663099

SOUNET: Self-Organized Underwater Wireless Sensor Network.

PubMed

Kim, Hee-Won; Cho, Ho-Shin

2017-02-02

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

SOUNET: Self-Organized Underwater Wireless Sensor Network

PubMed Central

Kim, Hee-won; Cho, Ho-Shin

2017-01-01

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the time-varying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. PMID:28157164

Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows.

PubMed

Moussawi, A; Derzsy, N; Lin, X; Szymanski, B K; Korniss, G

2017-09-15

Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failures. We introduce a stochastic method for optimal heterogeneous distribution of resources (node capacities) subject to a fixed total cost. Additionally, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades using various real-world node-attack and node-failure scenarios. We show that failure mitigation through increased node protection can be effectively achieved against single-node failures. However, mitigating against multiple node failures is much more difficult due to the combinatorial increase in possible sets of initially failing nodes. We analyze the robustness of the system with increasing protection, and find that a critical tolerance exists at which the system undergoes a phase transition, and above which the network almost completely survives an attack. Moreover, we show that cascade-size distributions measured in this region exhibit a power-law decay. Finally, we find a strong correlation between cascade sizes induced by individual nodes and sets of nodes. We also show that network topology alone is a weak predictor in determining the progression of cascading failures.

Recovery time after localized perturbations in complex dynamical networks

NASA Astrophysics Data System (ADS)

Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed concept.

Distributed Dynamic Host Configuration Protocol (D2HCP)

PubMed Central

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment. PMID:22163856

Distributed Dynamic Host Configuration Protocol (D2HCP).

PubMed

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

PubMed

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-07-14

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

PubMed Central

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-01-01

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

An Algorithm for Critical Nodes Problem in Social Networks Based on Owen Value

PubMed Central

Wang, Xue-Guang

2014-01-01

Discovering critical nodes in social networks has many important applications. For finding out the critical nodes and considering the widespread community structure in social networks, we obtain each node's marginal contribution by Owen value. And then we can give a method for the solution of the critical node problem. We validate the feasibility and effectiveness of our method on two synthetic datasets and six real datasets. At the same time, the result obtained by using our method to analyze the terrorist network is in line with the actual situation. PMID:25006592

Protocol for communications in potentially noisy environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, Gerlad M.; Farrow, Jeffrey

2016-02-09

A communications protocol that is designed for transmission of data in networks that are subjected to harsh conditions is described herein. A network includes a plurality of devices, where the devices comprise respective nodes. The nodes are in communication with one another by way of a central network hub. The protocol causes the nodes to transmit data over a network bus at different data rates depending upon whether the nodes are operating normally or an arbitration procedure has been invoked.

Disruptions of brain structural network in end-stage renal disease patients with long-term hemodialysis and normal-appearing brain tissues.

PubMed

Chou, Ming-Chung; Ko, Chih-Hung; Chang, Jer-Ming; Hsieh, Tsyh-Jyi

2018-05-04

End-stage renal disease (ESRD) patients on hemodialysis were demonstrated to exhibit silent and invisible white-matter alterations which would likely lead to disruptions of brain structural networks. Therefore, the purpose of this study was to investigate the disruptions of brain structural network in ESRD patients. Thiry-three ESRD patients with normal-appearing brain tissues and 29 age- and gender-matched healthy controls were enrolled in this study and underwent both cognitive ability screening instrument (CASI) assessment and diffusion tensor imaging (DTI) acquisition. Brain structural connectivity network was constructed using probabilistic tractography with automatic anatomical labeling template. Graph-theory analysis was performed to detect the alterations of node-strength, node-degree, node-local efficiency, and node-clustering coefficient in ESRD patients. Correlational analysis was performed to understand the relationship between network measures, CASI score, and dialysis duration. Structural connectivity, node-strength, node-degree, and node-local efficiency were significantly decreased, whereas node-clustering coefficient was significantly increased in ESRD patients as compared with healthy controls. The disrupted local structural networks were generally associated with common neurological complications of ESRD patients, but the correlational analysis did not reveal significant correlation between network measures, CASI score, and dialysis duration. Graph-theory analysis was helpful to investigate disruptions of brain structural network in ESRD patients with normal-appearing brain tissues. Copyright © 2018. Published by Elsevier Masson SAS.

Linking Essential Tremor to the Cerebellum: Physiological Evidence.

PubMed

Filip, Pavel; Lungu, Ovidiu V; Manto, Mario-Ubaldo; Bareš, Martin

2016-12-01

Essential tremor (ET), clinically characterized by postural and kinetic tremors, predominantly in the upper extremities, originates from pathological activity in the dynamic oscillatory network comprising the majority of nodes in the central motor network. Evidence indicates dysfunction in the thalamus, the olivocerebellar loops, and intermittent cortical engagement. Pathology of the cerebellum, a structure with architecture intrinsically predisposed to oscillatory activity, has also been implicated in ET as shown by clinical, neuroimaging, and pathological studies. Despite electrophysiological studies assessing cerebellar impairment in ET being scarce, their impact is tangible, as summarized in this review. The electromyography-magnetoencephalography combination provided the first direct evidence of pathological alteration in cortico-subcortical communication, with a significant emphasis on the cerebellum. Furthermore, complex electromyography studies showed disruptions in the timing of agonist and antagonist muscle activation, a process generally attributed to the cerebellum. Evidence pointing to cerebellar engagement in ET has also been found in electrooculography measurements, cerebellar repetitive transcranial magnetic stimulation studies, and, indirectly, in complex analyses of the activity of the ventral intermediate thalamic nucleus (an area primarily receiving inputs from the cerebellum), which is also used in the advanced treatment of ET. In summary, further progress in therapy will require comprehensive electrophysiological and physiological analyses to elucidate the precise mechanisms leading to disease symptoms. The cerebellum, as a major node of this dynamic oscillatory network, requires further study to aid this endeavor.

Trust transitivity in social networks.

PubMed

Richters, Oliver; Peixoto, Tiago P

2011-04-05

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected "fringe" nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its "fringe" peers.

Trust Transitivity in Social Networks

PubMed Central

Richters, Oliver; Peixoto, Tiago P.

2011-01-01

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected “fringe” nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its “fringe” peers. PMID:21483683

Matching-centrality decomposition and the forecasting of new links in networks.

PubMed

Rohr, Rudolf P; Naisbit, Russell E; Mazza, Christian; Bersier, Louis-Félix

2016-02-10

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. © 2016 The Author(s).

Matching–centrality decomposition and the forecasting of new links in networks

PubMed Central

Rohr, Rudolf P.; Naisbit, Russell E.; Mazza, Christian; Bersier, Louis-Félix

2016-01-01

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. PMID:26842568

Identifying key nodes in multilayer networks based on tensor decomposition.

PubMed

Wang, Dingjie; Wang, Haitao; Zou, Xiufen

2017-06-01

The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.

Identifying key nodes in multilayer networks based on tensor decomposition

NASA Astrophysics Data System (ADS)

Wang, Dingjie; Wang, Haitao; Zou, Xiufen

2017-06-01

The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.

Core-periphery structure requires something else in the network

NASA Astrophysics Data System (ADS)

Kojaku, Sadamori; Masuda, Naoki

2018-04-01

A network with core-periphery structure consists of core nodes that are densely interconnected. In contrast to a community structure, which is a different meso-scale structure of networks, core nodes can be connected to peripheral nodes and peripheral nodes are not densely interconnected. Although core-periphery structure sounds reasonable, we argue that it is merely accounted for by heterogeneous degree distributions, if one partitions a network into a single core block and a single periphery block, which the famous Borgatti–Everett algorithm and many succeeding algorithms assume. In other words, there is a strong tendency that high-degree and low-degree nodes are judged to be core and peripheral nodes, respectively. To discuss core-periphery structure beyond the expectation of the node’s degree (as described by the configuration model), we propose that one needs to assume at least one block of nodes apart from the focal core-periphery structure, such as a different core-periphery pair, community or nodes not belonging to any meso-scale structure. We propose a scalable algorithm to detect pairs of core and periphery in networks, controlling for the effect of the node’s degree. We illustrate our algorithm using various empirical networks.

High Speed All-Optical Data Distribution Network

NASA Astrophysics Data System (ADS)

Braun, Steve; Hodara, Henri

2017-11-01

This article describes the performance and capabilities of an all-optical network featuring low latency, high speed file transfer between serially connected optical nodes. A basic component of the network is a network interface card (NIC) implemented through a unique planar lightwave circuit (PLC) that performs add/drop data and optical signal amplification. The network uses a linear bus topology with nodes in a "T" configuration, as described in the text. The signal is sent optically (hence, no latency) to all nodes via wavelength division multiplexing (WDM), with each node receiver tuned to wavelength of choice via an optical de-multiplexer. Each "T" node routes a portion of the signal to/from the bus through optical couplers, embedded in the network interface card (NIC), to each of the 1 through n computers.

Smart-Home Architecture Based on Bluetooth mesh Technology

NASA Astrophysics Data System (ADS)

Wan, Qing; Liu, Jianghua

2018-03-01

This paper describes the smart home network system based on Nordic nrf52832 device. Nrf52832 is new generation RF SOC device focus on sensor monitor and low power Bluetooth connection applications. In this smart home system, we set up a self-organizing network system which consists of one control node and a lot of monitor nodes. The control node manages the whole network works; the monitor nodes collect the sensor information such as light intensity, temperature, humidity, PM2.5, etc. Then update to the control node by Bluetooth mesh network. The design results show that the Bluetooth mesh wireless network system is flexible and construction cost is low, which is suitable for the communication characteristics of a smart home network. We believe it will be wildly used in the future.

Using the OASES-A to illustrate how network analysis can be applied to understand the experience of stuttering.

PubMed

Siew, Cynthia S Q; Pelczarski, Kristin M; Yaruss, J Scott; Vitevitch, Michael S

Network science uses mathematical and computational techniques to examine how individual entities in a system, represented by nodes, interact, as represented by connections between nodes. This approach has been used by Cramer et al. (2010) to make "symptom networks" to examine various psychological disorders. In the present analysis we examined a network created from the items in the Overall Assessment of the Speaker's Experience of Stuttering-Adult (OASES-A), a commonly used measure for evaluating adverse impact in the lives of people who stutter. The items of the OASES-A were represented as nodes in the network. Connections between nodes were placed if responses to those two items in the OASES-A had a correlation coefficient greater than ±0.5. Several network analyses revealed which nodes were "important" in the network. Several centrally located nodes and "key players" in the network were identified. A community detection analysis found groupings of nodes that differed slightly from the subheadings of the OASES-A. Centrally located nodes and "key players" in the network may help clinicians prioritize treatment. The different community structure found for people who stutter suggests that the way people who stutter view stuttering may differ from the way that scientists and clinicians view stuttering. Finally, the present analyses illustrate how the network approach might be applied to other speech, language, and hearing disorders to better understand how those disorders are experienced and to provide insights for their treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid identifying high-influence nodes in complex networks

NASA Astrophysics Data System (ADS)

Song, Bo; Jiang, Guo-Ping; Song, Yu-Rong; Xia, Ling-Ling

2015-10-01

A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method (RIM) to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered (SIR) model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness, and eigenvector centrality methods. Project supported by the National Natural Science Foundation of China (Grant Nos. 61374180 and 61373136), the Ministry of Education Research in the Humanities and Social Sciences Planning Fund Project, China (Grant No. 12YJAZH120), and the Six Projects Sponsoring Talent Summits of Jiangsu Province, China (Grant No. RLD201212).

Towards a Methodology for Validation of Centrality Measures in Complex Networks

PubMed Central

2014-01-01

Background Living systems are associated with Social networks — networks made up of nodes, some of which may be more important in various aspects as compared to others. While different quantitative measures labeled as “centralities” have previously been used in the network analysis community to find out influential nodes in a network, it is debatable how valid the centrality measures actually are. In other words, the research question that remains unanswered is: how exactly do these measures perform in the real world? So, as an example, if a centrality of a particular node identifies it to be important, is the node actually important? Purpose The goal of this paper is not just to perform a traditional social network analysis but rather to evaluate different centrality measures by conducting an empirical study analyzing exactly how do network centralities correlate with data from published multidisciplinary network data sets. Method We take standard published network data sets while using a random network to establish a baseline. These data sets included the Zachary's Karate Club network, dolphin social network and a neural network of nematode Caenorhabditis elegans. Each of the data sets was analyzed in terms of different centrality measures and compared with existing knowledge from associated published articles to review the role of each centrality measure in the determination of influential nodes. Results Our empirical analysis demonstrates that in the chosen network data sets, nodes which had a high Closeness Centrality also had a high Eccentricity Centrality. Likewise high Degree Centrality also correlated closely with a high Eigenvector Centrality. Whereas Betweenness Centrality varied according to network topology and did not demonstrate any noticeable pattern. In terms of identification of key nodes, we discovered that as compared with other centrality measures, Eigenvector and Eccentricity Centralities were better able to identify important nodes. PMID:24709999

Implementing direct, spatially isolated problems on transputer networks

NASA Technical Reports Server (NTRS)

Ellis, Graham K.

1988-01-01

Parametric studies were performed on transputer networks of up to 40 processors to determine how to implement and maximize the performance of the solution of problems where no processor-to-processor data transfer is required for the problem solution (spatially isolated). Two types of problems are investigated a computationally intensive problem where the solution required the transmission of 160 bytes of data through the parallel network, and a communication intensive example that required the transmission of 3 Mbytes of data through the network. This data consists of solutions being sent back to the host processor and not intermediate results for another processor to work on. Studies were performed on both integer and floating-point transputers. The latter features an on-chip floating-point math unit and offers approximately an order of magnitude performance increase over the integer transputer on real valued computations. The results indicate that a minimum amount of work is required on each node per communication to achieve high network speedups (efficiencies). The floating-point processor requires approximately an order of magnitude more work per communication than the integer processor because of the floating-point unit's increased computing capacity.

Effects of maximum node degree on computer virus spreading in scale-free networks

NASA Astrophysics Data System (ADS)

Bamaarouf, O.; Ould Baba, A.; Lamzabi, S.; Rachadi, A.; Ez-Zahraouy, H.

2017-10-01

The increase of the use of the Internet networks favors the spread of viruses. In this paper, we studied the spread of viruses in the scale-free network with different topologies based on the Susceptible-Infected-External (SIE) model. It is found that the network structure influences the virus spreading. We have shown also that the nodes of high degree are more susceptible to infection than others. Furthermore, we have determined a critical maximum value of node degree (Kc), below which the network is more resistible and the computer virus cannot expand into the whole network. The influence of network size is also studied. We found that the network with low size is more effective to reduce the proportion of infected nodes.

Global interrupt and barrier networks

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

2008-10-28

A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

A local immunization strategy for networks with overlapping community structure

NASA Astrophysics Data System (ADS)

Taghavian, Fatemeh; Salehi, Mostafa; Teimouri, Mehdi

2017-02-01

Since full coverage treatment is not feasible due to limited resources, we need to utilize an immunization strategy to effectively distribute the available vaccines. On the other hand, the structure of contact network among people has a significant impact on epidemics of infectious diseases (such as SARS and influenza) in a population. Therefore, network-based immunization strategies aim to reduce the spreading rate by removing the vaccinated nodes from contact network. Such strategies try to identify more important nodes in epidemics spreading over a network. In this paper, we address the effect of overlapping nodes among communities on epidemics spreading. The proposed strategy is an optimized random-walk based selection of these nodes. The whole process is local, i.e. it requires contact network information in the level of nodes. Thus, it is applicable to large-scale and unknown networks in which the global methods usually are unrealizable. Our simulation results on different synthetic and real networks show that the proposed method outperforms the existing local methods in most cases. In particular, for networks with strong community structures, high overlapping membership of nodes or small size communities, the proposed method shows better performance.

An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

PubMed

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-08-18

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

PubMed Central

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-01-01

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption. PMID:25196015

Quantitative methods of identifying the key nodes in the illegal wildlife trade network

PubMed Central

Patel, Nikkita Gunvant; Rorres, Chris; Joly, Damien O.; Brownstein, John S.; Boston, Ray; Levy, Michael Z.; Smith, Gary

2015-01-01

Innovative approaches are needed to combat the illegal trade in wildlife. Here, we used network analysis and a new database, HealthMap Wildlife Trade, to identify the key nodes (countries) that support the illegal wildlife trade. We identified key exporters and importers from the number of shipments a country sent and received and from the number of connections a country had to other countries over a given time period. We used flow betweenness centrality measurements to identify key intermediary countries. We found the set of nodes whose removal from the network would cause the maximum disruption to the network. Selecting six nodes would fragment 89.5% of the network for elephants, 92.3% for rhinoceros, and 98.1% for tigers. We then found sets of nodes that would best disseminate an educational message via direct connections through the network. We would need to select 18 nodes to reach 100% of the elephant trade network, 16 nodes for rhinoceros, and 10 for tigers. Although the choice of locations for interventions should be customized for the animal and the goal of the intervention, China was the most frequently selected country for network fragmentation and information dissemination. Identification of key countries will help strategize illegal wildlife trade interventions. PMID:26080413

Locating hardware faults in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-01-12

Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.

Method and apparatus for eliminating unsuccessful tries in a search tree

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward (Inventor); Madan, Herb S. (Inventor)

1991-01-01

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parameterized centrality metric for network analysis

NASA Astrophysics Data System (ADS)

Ghosh, Rumi; Lerman, Kristina

2011-06-01

A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [P. Bonacich, Am. J. Sociol.0002-960210.1086/228631 92, 1170 (1987)], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, for example, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. Studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed metric to several benchmark networks and show that it leads to better insights into network structure than alternative metrics.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

New Scheduling Algorithms for Agile All-Photonic Networks

NASA Astrophysics Data System (ADS)

Mehri, Mohammad Saleh; Ghaffarpour Rahbar, Akbar

2017-12-01

An optical overlaid star network is a class of agile all-photonic networks that consists of one or more core node(s) at the center of the star network and a number of edge nodes around the core node. In this architecture, a core node may use a scheduling algorithm for transmission of traffic through the network. A core node is responsible for scheduling optical packets that arrive from edge nodes and switching them toward their destinations. Nowadays, most edge nodes use virtual output queue (VOQ) architecture for buffering client packets to achieve high throughput. This paper presents two efficient scheduling algorithms called discretionary iterative matching (DIM) and adaptive DIM. These schedulers find maximum matching in a small number of iterations and provide high throughput and incur low delay. The number of arbiters in these schedulers and the number of messages exchanged between inputs and outputs of a core node are reduced. We show that DIM and adaptive DIM can provide better performance in comparison with iterative round-robin matching with SLIP (iSLIP). SLIP means the act of sliding for a short distance to select one of the requested connections based on the scheduling algorithm.

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

PubMed Central

Kim, Sang-Ha

2017-01-01

Face routing has been adopted in wireless sensor networks (WSNs) where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency. PMID:29053623

Low-Latency and Energy-Efficient Data Preservation Mechanism in Low-Duty-Cycle Sensor Networks.

PubMed

Jiang, Chan; Li, Tao-Shen; Liang, Jun-Bin; Wu, Heng

2017-05-06

Similar to traditional wireless sensor networks (WSN), the nodes only have limited memory and energy in low-duty-cycle sensor networks (LDC-WSN). However, different from WSN, the nodes in LDC-WSN often sleep most of their time to preserve their energies. The sleeping feature causes serious data transmission delay. However, each source node that has sensed data needs to quickly disseminate its data to other nodes in the network for redundant storage. Otherwise, data would be lost due to its source node possibly being destroyed by outer forces in a harsh environment. The quick dissemination requirement produces a contradiction with the sleeping delay in the network. How to quickly disseminate all the source data to all the nodes with limited memory in the network for effective preservation is a challenging issue. In this paper, a low-latency and energy-efficient data preservation mechanism in LDC-WSN is proposed. The mechanism is totally distributed. The data can be disseminated to the network with low latency by using a revised probabilistic broadcasting mechanism, and then stored by the nodes with LT (Luby Transform) codes, which are a famous rateless erasure code. After the process of data dissemination and storage completes, some nodes may die due to being destroyed by outer forces. If a mobile sink enters the network at any time and from any place to collect the data, it can recover all of the source data by visiting a small portion of survived nodes in the network. Theoretical analyses and simulation results show that our mechanism outperforms existing mechanisms in the performances of data dissemination delay and energy efficiency.

Complex network construction based on user group attention sequence

NASA Astrophysics Data System (ADS)

Zhang, Gaowei; Xu, Lingyu; Wang, Lei

2018-04-01

In the traditional complex network construction, it is often to use the similarity between nodes, build the weight of the network, and finally build the network. However, this approach tends to focus only on the coupling between nodes, while ignoring the information transfer between nodes and the transfer of directionality. In the network public opinion space, based on the set of stock series that the network groups pay attention to within a certain period of time, we vectorize the different stocks and build a complex network.

A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the practical strategic utility of TCOA to incorporate prior drug information into potential drug-target forecasts. Thus applicably, our method paves a novel and efficient way to identify the drug targets for leading the phenotype transitions of underlying biological networks.

PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

NASA Astrophysics Data System (ADS)

Cam, Hasan

2012-06-01

As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

Fermi-Dirac statistics and traffic in complex networks.

PubMed

de Moura, Alessandro P S

2005-06-01

We propose an idealized model for traffic in a network, in which many particles move randomly from node to node, following the network's links, and it is assumed that at most one particle can occupy any given node. This is intended to mimic the finite forwarding capacity of nodes in communication networks, thereby allowing the possibility of congestion and jamming phenomena. We show that the particles behave like free fermions, with appropriately defined energy-level structure and temperature. The statistical properties of this system are thus given by the corresponding Fermi-Dirac distribution. We use this to obtain analytical expressions for dynamical quantities of interest, such as the mean occupation of each node and the transport efficiency, for different network topologies and particle densities. We show that the subnetwork of free nodes always fragments into small isolated clusters for a sufficiently large number of particles, implying a communication breakdown at some density for all network topologies. These results are compared to direct simulations.

Locating influential nodes in complex networks

PubMed Central

Malliaros, Fragkiskos D.; Rossi, Maria-Evgenia G.; Vazirgiannis, Michalis

2016-01-01

Understanding and controlling spreading processes in networks is an important topic with many diverse applications, including information dissemination, disease propagation and viral marketing. It is of crucial importance to identify which entities act as influential spreaders that can propagate information to a large portion of the network, in order to ensure efficient information diffusion, optimize available resources or even control the spreading. In this work, we capitalize on the properties of the K-truss decomposition, a triangle-based extension of the core decomposition of graphs, to locate individual influential nodes. Our analysis on real networks indicates that the nodes belonging to the maximal K-truss subgraph show better spreading behavior compared to previously used importance criteria, including node degree and k-core index, leading to faster and wider epidemic spreading. We further show that nodes belonging to such dense subgraphs, dominate the small set of nodes that achieve the optimal spreading in the network. PMID:26776455

Data Delivery Method Based on Neighbor Nodes' Information in a Mobile Ad Hoc Network

PubMed Central

Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

2014-01-01

This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow. PMID:24672371

Data delivery method based on neighbor nodes' information in a mobile ad hoc network.

PubMed

Kashihara, Shigeru; Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

2014-01-01

This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

Electronic Resources for Security Related Information, CIAC-2307 R.1

DTIC Science & Technology

1994-12-01

administrators NETwork - Statistics about the network NODEntry node1 <node2 <…>> - BITEARN NODES entry for the specified node(s) NODEntry node1 / abc */xyz...Just the “:xyz.” tag and all tags whose name starts with “ abc ” PATHs snode node1 <node2 <…>> - BITNET path between “snode” and the specified node(s...protect their data and sytems . The mention of vendors or product names does not imply criticism or endorsement by the National Institute of Standards

A Family of Algorithms for Computing Consensus about Node State from Network Data

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2013-01-01

Biological and social networks are composed of heterogeneous nodes that contribute differentially to network structure and function. A number of algorithms have been developed to measure this variation. These algorithms have proven useful for applications that require assigning scores to individual nodes–from ranking websites to determining critical species in ecosystems–yet the mechanistic basis for why they produce good rankings remains poorly understood. We show that a unifying property of these algorithms is that they quantify consensus in the network about a node's state or capacity to perform a function. The algorithms capture consensus by either taking into account the number of a target node's direct connections, and, when the edges are weighted, the uniformity of its weighted in-degree distribution (breadth), or by measuring net flow into a target node (depth). Using data from communication, social, and biological networks we find that that how an algorithm measures consensus–through breadth or depth– impacts its ability to correctly score nodes. We also observe variation in sensitivity to source biases in interaction/adjacency matrices: errors arising from systematic error at the node level or direct manipulation of network connectivity by nodes. Our results indicate that the breadth algorithms, which are derived from information theory, correctly score nodes (assessed using independent data) and are robust to errors. However, in cases where nodes “form opinions” about other nodes using indirect information, like reputation, depth algorithms, like Eigenvector Centrality, are required. One caveat is that Eigenvector Centrality is not robust to error unless the network is transitive or assortative. In these cases the network structure allows the depth algorithms to effectively capture breadth as well as depth. Finally, we discuss the algorithms' cognitive and computational demands. This is an important consideration in systems in which individuals use the collective opinions of others to make decisions. PMID:23874167

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

PubMed Central

Mahjoub, Reem K.; Elleithy, Khaled

2017-01-01

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation. PMID:28420102

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

PubMed

Mahjoub, Reem K; Elleithy, Khaled

2017-04-14

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

Small worlds in space: Synchronization, spatial and relational modularity

NASA Astrophysics Data System (ADS)

Brede, M.

2010-06-01

In this letter we investigate networks that have been optimized to realize a trade-off between enhanced synchronization and cost of wire to connect the nodes in space. Analyzing the evolved arrangement of nodes in space and their corresponding network topology, a class of small-world networks characterized by spatial and network modularity is found. More precisely, for low cost of wire optimal configurations are characterized by a division of nodes into two spatial groups with maximum distance from each other, whereas network modularity is low. For high cost of wire, the nodes organize into several distinct groups in space that correspond to network modules connected on a ring. In between, spatially and relationally modular small-world networks are found.

Ranking the spreading ability of nodes in network core

NASA Astrophysics Data System (ADS)

Tong, Xiao-Lei; Liu, Jian-Guo; Wang, Jiang-Pan; Guo, Qiang; Ni, Jing

2015-11-01

Ranking nodes by their spreading ability in complex networks is of vital significance to better understand the network structure and more efficiently spread information. The k-shell decomposition method could identify the most influential nodes, namely network core, with the same ks values regardless to their different spreading influence. In this paper, we present an improved method based on the k-shell decomposition method and closeness centrality (CC) to rank the node spreading influence of the network core. Experiment results on the data from the scientific collaboration network and U.S. aviation network show that the accuracy of the presented method could be increased by 31% and 45% than the one obtained by the degree k, 32% and 31% than the one by the betweenness.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Collective network for computer structures

DOEpatents

Blumrich, Matthias A; Coteus, Paul W; Chen, Dong; Gara, Alan; Giampapa, Mark E; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E; Steinmacher-Burow, Burkhard D; Vranas, Pavlos M

2014-01-07

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

Collective network for computer structures

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

2011-08-16

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

Enhancing the Reliability of Head Nodes in Underwater Sensor Networks

PubMed Central

Min, Hong; Cho, Yookun; Heo, Junyoung

2012-01-01

Underwater environments are quite different from terrestrial environments in terms of the communication media and operating conditions associated with those environments. In underwater sensor networks, the probability of node failure is high because sensor nodes are deployed in harsher environments than ground-based networks. The sensor nodes are surrounded by salt water and moved around by waves and currents. Many studies have focused on underwater communication environments in an effort to improve the data transmission throughput. In this paper, we present a checkpointing scheme for the head nodes to quickly recover from a head node failure. Experimental results show that the proposed scheme enhances the reliability of the networks and makes them more efficient in terms of energy consumption and the recovery latency compared to the previous scheme without checkpointing. PMID:22438707

Design of nodes for embedded and ultra low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Xu, Jun; You, Bo; Cui, Juan; Ma, Jing; Li, Xin

2008-10-01

Sensor network integrates sensor technology, MEMS (Micro-Electro-Mechanical system) technology, embedded computing, wireless communication technology and distributed information management technology. It is of great value to use it where human is quite difficult to reach. Power consumption and size are the most important consideration when nodes are designed for distributed WSN (wireless sensor networks). Consequently, it is of great importance to decrease the size of a node, reduce its power consumption and extend its life in network. WSN nodes have been designed using JN5121-Z01-M01 module produced by jennic company and IEEE 802.15.4/ZigBee technology. Its new features include support for CPU sleep modes and a long-term ultra low power sleep mode for the entire node. In low power configuration the node resembles existing small low power nodes. An embedded temperature sensor node has been developed to verify and explore our architecture. The experiment results indicate that the WSN has the characteristic of high reliability, good stability and ultra low power consumption.

Dynamic node immunization for restraint of harmful information diffusion in social networks

NASA Astrophysics Data System (ADS)

Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

2018-08-01

To restrain the spread of harmful information is crucial for the healthy and sustainable development of social networks. We address the problem of restraining the spread of harmful information by immunizing nodes in the networks. Previous works have developed methods based on the network topology or studied how to immunize nodes in the presence of initial infected nodes. These static methods, in which nodes are immunized at once, may have poor performance in the certain situation due to the dynamics of diffusion. To tackle this problem, we introduce a new dynamic immunization problem of immunizing nodes during the process of the diffusion in this paper. We formulate the problem and propose a novel heuristic algorithm by dealing with two sub-problems: (1) how to select a node to achieve the best immunization effect at the present time? (2) whether the selected node should be immunized right now? Finally, we demonstrate the effectiveness of our algorithm through extensive experiments on various real datasets.

BridgeRank: A novel fast centrality measure based on local structure of the network

NASA Astrophysics Data System (ADS)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

Critical Node Location in De Bruijn Networks

DTIC Science & Technology

2016-10-01

transmitter tower, node 0000. Let us say we broadcast a signal at four discrete and incrementally higher power levels, 1 - 4. After each transmission , we...When deploying a wireless network, some highly desirable properties are (a) many short paths between any two nodes, and (b) relatively few edges. One...minimal. To deal with this problem, we propose the use of a special network structure - de Bruijn networks. When deploying a wireless network, some

Information loss method to measure node similarity in networks

NASA Astrophysics Data System (ADS)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Densification and structural transitions in networks that grow by node copying

NASA Astrophysics Data System (ADS)

Bhat, U.; Krapivsky, P. L.; Lambiotte, R.; Redner, S.

2016-12-01

We introduce a growing network model, the copying model, in which a new node attaches to a randomly selected target node and, in addition, independently to each of the neighbors of the target with copying probability p . When p <1/2 , this algorithm generates sparse networks, in which the average node degree is finite. A power-law degree distribution also arises, with a nonuniversal exponent whose value is determined by a transcendental equation in p . In the sparse regime, the network is "normal," e.g., the relative fluctuations in the number of links are asymptotically negligible. For p ≥1/2 , the emergent networks are dense (the average degree increases with the number of nodes N ), and they exhibit intriguing structural behaviors. In particular, the N dependence of the number of m cliques (complete subgraphs of m nodes) undergoes m -1 transitions from normal to progressively more anomalous behavior at an m -dependent critical values of p . Different realizations of the network, which start from the same initial state, exhibit macroscopic fluctuations in the thermodynamic limit: absence of self-averaging. When linking to second neighbors of the target node can occur, the number of links asymptotically grows as N2 as N →∞ , so that the network is effectively complete as N →∞ .

Weak signal transmission in complex networks and its application in detecting connectivity.

PubMed

Liang, Xiaoming; Liu, Zonghua; Li, Baowen

2009-10-01

We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

A data management proposal to connect in a hierarchical way nodes of the Spanish Long Term Ecological Research (LTER) network

NASA Astrophysics Data System (ADS)

Fuentes, Daniel; Pérez-Luque, Antonio J.; Bonet García, Francisco J.; Moreno-LLorca, Ricardo A.; Sánchez-Cano, Francisco M.; Suárez-Muñoz, María

2017-04-01

The Long Term Ecological Research (LTER) network aims to provide the scientific community, policy makers, and society with the knowledge and predictive understanding necessary to conserve, protect, and manage the ecosystems. LTER is organized into networks ranging from the global to national scale. In the top of network, the International Long Term Ecological Research (ILTER) Network coordinates among ecological researchers and LTER research networks at local, regional and global scales. In Spain, the Spanish Long Term Ecological Research (LTER-Spain) network was built to foster the collaboration and coordination between longest-lived ecological researchers and networks on a local scale. Currently composed by nine nodes, this network facilitates the data exchange, documentation and preservation encouraging the development of cross-disciplinary works. However, most nodes have no specific information systems, tools or qualified personnel to manage their data for continued conservation and there are no harmonized methodologies for long-term monitoring protocols. Hence, the main challenge is to place the nodes in its correct position in the network, providing the best tools that allow them to manage their data autonomously and make it easier for them to access information and knowledge in the network. This work proposes a connected structure composed by four LTER nodes located in southern Spain. The structure is built considering hierarchical approach: nodes that create information which is documented using metadata standards (such as Ecological Metadata Language, EML); and others nodes that gather metadata and information. We also take into account the capacity of each node to manage their own data and the premise that the data and metadata must be maintained where it is generated. The current state of the nodes is a follows: two of them have their own information management system (Sierra Nevada-Granada and Doñana Long-Term Socio-ecological Research Platform) and another has no infrastructure to maintain their data (The Arid Iberian South East LTSER Platform). The last one (Environmental Information Network of Andalusia-REDIAM) acts as the coordinator, providing physical and logical support to other nodes and also gathers and distributes the information "uphill" to the rest of the network (LTER Europe and ILTER). The development of the network has been divided in three stages. First, existing resources and data management requirements are identified in each node. Second, the necessary software tools and interoperable standards to manage and exchange the data have been selected, installed and configured in each participant. Finally, once the network has been set up completely, it is expected to expand it all over Spain with new nodes and its connection to others LTER and similar networks. This research has been funded by ADAPTAMED (Protection of key ecosystem services by adaptive management of Climate Change endangered Mediterranean socioecosystems) Life EU project, Sierra Nevada Global Change Observatory (LTER-site) and eLTER (Integrated European Long Term Ecosystem & Socio-Ecological Research Infrastructure).

Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks

PubMed Central

Castet, Jean-Francois; Saleh, Joseph H.

2013-01-01

This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the results highlight the importance of the reliability of the wireless links between spacecraft (nodes) to enable any survivability improvements for space-based networks. PMID:23599835

Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks.

PubMed

Castet, Jean-Francois; Saleh, Joseph H

2013-01-01

This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the results highlight the importance of the reliability of the wireless links between spacecraft (nodes) to enable any survivability improvements for space-based networks.

Dynamical Response of Networks Under External Perturbations: Exact Results

NASA Astrophysics Data System (ADS)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

Pseudo-random dynamic address configuration (PRDAC) algorithm for mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Wu, Shaochuan; Tan, Xuezhi

2007-11-01

By analyzing all kinds of address configuration algorithms, this paper provides a new pseudo-random dynamic address configuration (PRDAC) algorithm for mobile ad hoc networks. Based on PRDAC, the first node that initials this network randomly chooses a nonlinear shift register that can generates an m-sequence. When another node joins this network, the initial node will act as an IP address configuration sever to compute an IP address according to this nonlinear shift register, and then allocates this address and tell the generator polynomial of this shift register to this new node. By this means, when other node joins this network, any node that has obtained an IP address can act as a server to allocate address to this new node. PRDAC can also efficiently avoid IP conflicts and deal with network partition and merge as same as prophet address (PA) allocation and dynamic configuration and distribution protocol (DCDP). Furthermore, PRDAC has less algorithm complexity, less computational complexity and more sufficient assumption than PA. In addition, PRDAC radically avoids address conflicts and maximizes the utilization rate of IP addresses. Analysis and simulation results show that PRDAC has rapid convergence, low overhead and immune from topological structures.

DCS-Neural-Network Program for Aircraft Control and Testing

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

2006-01-01

A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from wind-tunnel test data and computing real-time stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

Predicting Node Degree Centrality with the Node Prominence Profile

PubMed Central

Yang, Yang; Dong, Yuxiao; Chawla, Nitesh V.

2014-01-01

Centrality of a node measures its relative importance within a network. There are a number of applications of centrality, including inferring the influence or success of an individual in a social network, and the resulting social network dynamics. While we can compute the centrality of any node in a given network snapshot, a number of applications are also interested in knowing the potential importance of an individual in the future. However, current centrality is not necessarily an effective predictor of future centrality. While there are different measures of centrality, we focus on degree centrality in this paper. We develop a method that reconciles preferential attachment and triadic closure to capture a node's prominence profile. We show that the proposed node prominence profile method is an effective predictor of degree centrality. Notably, our analysis reveals that individuals in the early stage of evolution display a distinctive and robust signature in degree centrality trend, adequately predicted by their prominence profile. We evaluate our work across four real-world social networks. Our findings have important implications for the applications that require prediction of a node's future degree centrality, as well as the study of social network dynamics. PMID:25429797

Improved Iterative Decoding of Network-Channel Codes for Multiple-Access Relay Channel.

PubMed

Majumder, Saikat; Verma, Shrish

2015-01-01

Cooperative communication using relay nodes is one of the most effective means of exploiting space diversity for low cost nodes in wireless network. In cooperative communication, users, besides communicating their own information, also relay the information of other users. In this paper we investigate a scheme where cooperation is achieved using a common relay node which performs network coding to provide space diversity for two information nodes transmitting to a base station. We propose a scheme which uses Reed-Solomon error correcting code for encoding the information bit at the user nodes and convolutional code as network code, instead of XOR based network coding. Based on this encoder, we propose iterative soft decoding of joint network-channel code by treating it as a concatenated Reed-Solomon convolutional code. Simulation results show significant improvement in performance compared to existing scheme based on compound codes.

A Mobile Sensor Network System for Monitoring of Unfriendly Environments.

PubMed

Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo

2008-11-14

Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.

Multi-petascale highly efficient parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Lymph Node Size on Computed Tomography Images Is a Predictive Indicator for Lymph Node Metastasis in Patients with Colorectal Neuroendocrine Tumors.

PubMed

Tanaka, Toshiaki; Nozawa, Hiroaki; Kawai, Kazushige; Hata, Keisuke; Kiyomatsu, Tomomichi; Nishikawa, Takeshi; Otani, Kensuke; Sasaki, Kazuhito; Murono, Koji; Watanabe, Toshiaki

2017-01-01

Colorectal neuroendocrine tumors (NET) are a rare manifestation of colorectal neoplasia, requiring for radical dissection of the regional lymph nodes along with colorectal resection similar to that required for colorectal cancer. However, thus far, no reports have described the ability of computed tomography (CT) to predict lymph node involvement. In this study, we revealed the prediction rate of lymph node metastasis using contrast-enhanced CT. A total of 21 patients with colorectal NET undergoing colorectal resection were recruited from January 2010 to June 2016. We compared the CT findings between samples with or without pathologically proven lymph node metastasis, in each field (pericolic/perirectal and intermediate nodes). Within the pericolic/perirectal field, any lymph node larger than 5 mm in the CT images was a predictive indicator of lymph node metastasis with a sensitivity, specificity, and area under ROC curve (AUC) of 66.7%, 87.5%, and 0.844, respectively. Within the intermediate field, any visible lymph node on the CT was a predictive indicator of lymph node metastasis with a sensitivity, specificity, and AUC of 100%, 76.4%, and 0.890, respectively. In addition, when we observed lymph nodes larger than 3 mm on the CT images, the sensitivity and specificity were 100% and 82.4%, respectively, with an AUC of 0.8971. CT images provide predictive information for lymph node metastasis with a high rate of accuracy. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks.

PubMed

Jiang, Peng; Xu, Yiming; Liu, Jun

2017-01-19

For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes' being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network's best service quality and lifetime.

An Energy Efficient Simultaneous-Node Repositioning Algorithm for Mobile Sensor Networks

PubMed Central

Hasbullah, Halabi; Nazir, Babar; Khan, Imran Ali

2014-01-01

Recently, wireless sensor network (WSN) applications have seen an increase in interest. In search and rescue, battlefield reconnaissance, and some other such applications, so that a survey of the area of interest can be made collectively, a set of mobile nodes is deployed. Keeping the network nodes connected is vital for WSNs to be effective. The provision of connectivity can be made at the time of startup and can be maintained by carefully coordinating the nodes when they move. However, if a node suddenly fails, the network could be partitioned to cause communication problems. Recently, several methods that use the relocation of nodes for connectivity restoration have been proposed. However, these methods have the tendency to not consider the potential coverage loss in some locations. This paper addresses the concerns of both connectivity and coverage in an integrated way so that this gap can be filled. A novel algorithm for simultaneous-node repositioning is introduced. In this approach, each neighbour of the failed node, one by one, moves in for a certain amount of time to take the place of the failed node, after which it returns to its original location in the network. The effectiveness of this algorithm has been verified by the simulation results. PMID:25152924

Learning about knowledge: A complex network approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fontoura Costa, Luciano da

2006-08-15

An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchicalmore » networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabasi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges.« less

Joint estimation of preferential attachment and node fitness in growing complex networks

NASA Astrophysics Data System (ADS)

Pham, Thong; Sheridan, Paul; Shimodaira, Hidetoshi

2016-09-01

Complex network growth across diverse fields of science is hypothesized to be driven in the main by a combination of preferential attachment and node fitness processes. For measuring the respective influences of these processes, previous approaches make strong and untested assumptions on the functional forms of either the preferential attachment function or fitness function or both. We introduce a Bayesian statistical method called PAFit to estimate preferential attachment and node fitness without imposing such functional constraints that works by maximizing a log-likelihood function with suitably added regularization terms. We use PAFit to investigate the interplay between preferential attachment and node fitness processes in a Facebook wall-post network. While we uncover evidence for both preferential attachment and node fitness, thus validating the hypothesis that these processes together drive complex network evolution, we also find that node fitness plays the bigger role in determining the degree of a node. This is the first validation of its kind on real-world network data. But surprisingly the rate of preferential attachment is found to deviate from the conventional log-linear form when node fitness is taken into account. The proposed method is implemented in the R package PAFit.

Joint estimation of preferential attachment and node fitness in growing complex networks

PubMed Central

Pham, Thong; Sheridan, Paul; Shimodaira, Hidetoshi

2016-01-01

Complex network growth across diverse fields of science is hypothesized to be driven in the main by a combination of preferential attachment and node fitness processes. For measuring the respective influences of these processes, previous approaches make strong and untested assumptions on the functional forms of either the preferential attachment function or fitness function or both. We introduce a Bayesian statistical method called PAFit to estimate preferential attachment and node fitness without imposing such functional constraints that works by maximizing a log-likelihood function with suitably added regularization terms. We use PAFit to investigate the interplay between preferential attachment and node fitness processes in a Facebook wall-post network. While we uncover evidence for both preferential attachment and node fitness, thus validating the hypothesis that these processes together drive complex network evolution, we also find that node fitness plays the bigger role in determining the degree of a node. This is the first validation of its kind on real-world network data. But surprisingly the rate of preferential attachment is found to deviate from the conventional log-linear form when node fitness is taken into account. The proposed method is implemented in the R package PAFit. PMID:27601314

A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses.

PubMed

Moyen, N; Ahmed, G; Gupta, S; Tenzin, T; Khan, R; Khan, T; Debnath, N; Yamage, M; Pfeiffer, D U; Fournie, G

2018-01-12

Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it. Poultry trading practices varied according to the size of the LBMs and to the type of poultry traded. Industrial broiler chickens, the most commonly traded poultry, were generally sold in LBMs close to their production areas, whereas ducks and backyard chickens were moved over longer distances, and their transport involved several intermediates. The poultry trading network composed of 445 nodes (73.2% were LBMs) was highly connected and disassortative. However, the removal of only 5.6% of the nodes (25 LBMs with the highest betweenness scores), reduced the network's connectedness, and the maximum size of output and input domains by more than 50%. Poultry types need to be discriminated in order to understand the way in which poultry trading networks are shaped, and the level of risk of disease spread that these networks may promote. Knowledge of the network structure could be used to target control and surveillance interventions to a small number of LBMs.

ORA User’s Guide 2012

DTIC Science & Technology

2012-06-11

places, resources, knowledge sets or other common Node Classes*. 285 This example will use the Stargate dataset (SG-1). This dataset is included...create a new Meta-Network. Below is the NodeSet for Stargate with the original 16 node NodeSet. 376 From the main menu select, Actions > Add...measures by simply gauging their size visually and intuitively. First, visualize one of your networks. Below is the Stargate agent x event network to

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

PubMed

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction: Metabolic networks (72.3%), Parasite-Host networks (93.3%), CoCoMac brain cortex co-activation network (89.6%), NW Spain fasciolosis spreading network (97.2%), Spanish financial law network (89.9%) and World trade network for Intelligent & Active Food Packaging (92.8%). In order to seek these models, we studied an average of 55,388 pairs of nodes in each model and a total of 332,326 pairs of nodes in all models. Finally, this method was used to solve a more complicated problem. A model was developed to score the connectivity quality in the Drug-Target network of US FDA approved drugs. In this last model the θ(k) values were calculated for three types of molecular networks representing different levels of organization: drug molecular graphs (atom-atom bonds), protein residue networks (amino acid interactions), and drug-target network (compound-protein binding). The overall accuracy of this model was 76.3%. This work opens a new door to the computational reevaluation of network connectivity quality (collation) for complex systems in molecular, biomedical, technological, and legal-social sciences as well as in world trade and industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

An Optimized Hidden Node Detection Paradigm for Improving the Coverage and Network Efficiency in Wireless Multimedia Sensor Networks.

PubMed

Alanazi, Adwan; Elleithy, Khaled

2016-09-07

Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node- continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Greedy data transportation scheme with hard packet deadlines for wireless ad hoc networks.

PubMed

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services.

Greedy Data Transportation Scheme with Hard Packet Deadlines for Wireless Ad Hoc Networks

PubMed Central

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services. PMID:25258736

The optimal community detection of software based on complex networks

NASA Astrophysics Data System (ADS)

Huang, Guoyan; Zhang, Peng; Zhang, Bing; Yin, Tengteng; Ren, Jiadong

2016-02-01

The community structure is important for software in terms of understanding the design patterns, controlling the development and the maintenance process. In order to detect the optimal community structure in the software network, a method Optimal Partition Software Network (OPSN) is proposed based on the dependency relationship among the software functions. First, by analyzing the information of multiple execution traces of one software, we construct Software Execution Dependency Network (SEDN). Second, based on the relationship among the function nodes in the network, we define Fault Accumulation (FA) to measure the importance of the function node and sort the nodes with measure results. Third, we select the top K(K=1,2,…) nodes as the core of the primal communities (only exist one core node). By comparing the dependency relationships between each node and the K communities, we put the node into the existing community which has the most close relationship. Finally, we calculate the modularity with different initial K to obtain the optimal division. With experiments, the method OPSN is verified to be efficient to detect the optimal community in various softwares.

Exact sampling of graphs with prescribed degree correlations

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Del Genio, Charo I.; Erdős, Péter L.; Miklós, István; Toroczkai, Zoltán

2015-08-01

Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree and conversely, in biological and technological networks, high-degree nodes tend to be linked with low-degree nodes. Degree correlations also affect the dynamics of processes supported by a network structure, such as the spread of opinions or epidemics. The proper modelling of these systems, i.e., without uncontrolled biases, requires the sampling of networks with a specified set of constraints. We present a solution to the sampling problem when the constraints imposed are the degree correlations. In particular, we develop an exact method to construct and sample graphs with a specified joint-degree matrix, which is a matrix providing the number of edges between all the sets of nodes of a given degree, for all degrees, thus completely specifying all pairwise degree correlations, and additionally, the degree sequence itself. Our algorithm always produces independent samples without backtracking. The complexity of the graph construction algorithm is {O}({NM}) where N is the number of nodes and M is the number of edges.

Complex networks under dynamic repair model

NASA Astrophysics Data System (ADS)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Diffusion in Colocation Contact Networks: The Impact of Nodal Spatiotemporal Dynamics.

PubMed

Thomas, Bryce; Jurdak, Raja; Zhao, Kun; Atkinson, Ian

2016-01-01

Temporal contact networks are studied to understand dynamic spreading phenomena such as communicable diseases or information dissemination. To establish how spatiotemporal dynamics of nodes impact spreading potential in colocation contact networks, we propose "inducement-shuffling" null models which break one or more correlations between times, locations and nodes. By reconfiguring the time and/or location of each node's presence in the network, these models induce alternative sets of colocation events giving rise to contact networks with varying spreading potential. This enables second-order causal reasoning about how correlations in nodes' spatiotemporal preferences not only lead to a given contact network but ultimately influence the network's spreading potential. We find the correlation between nodes and times to be the greatest impediment to spreading, while the correlation between times and locations slightly catalyzes spreading. Under each of the presented null models we measure both the number of contacts and infection prevalence as a function of time, with the surprising finding that the two have no direct causality.

Hiding Critical Targets in Smart Grid Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bao, Wei; Li, Qinghua

With the integration of advanced communication technologies, the power grid is expected to greatly enhance efficiency and reliability of future power systems. However, since most electrical devices in power grid substations are connected via communication networks, cyber security of these communication networks becomes a critical issue. Real-World incidents such as Stuxnet have shown the feasibility of compromising a device in the power grid network to further launch more sophisticated attacks. To deal with security attacks of this spirit, this paper aims to hide critical targets from compromised internal nodes and hence protect them from further attacks launched by those compromisedmore » nodes. In particular, we consider substation networks and propose to add carefully-controlled dummy traffic to a substation network to make critical target nodes indistinguishable from other nodes in network traffic patterns. This paper describes the design and evaluation of such a scheme. Evaluations show that the scheme can effectively protect critical nodes with acceptable communication cost.« less

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

Finding influential nodes for integration in brain networks using optimal percolation theory.

PubMed

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Link failure detection in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Megerian, Mark G.; Smith, Brian E.

2010-11-09

Methods, apparatus, and products are disclosed for link failure detection in a parallel computer including compute nodes connected in a rectangular mesh network, each pair of adjacent compute nodes in the rectangular mesh network connected together using a pair of links, that includes: assigning each compute node to either a first group or a second group such that adjacent compute nodes in the rectangular mesh network are assigned to different groups; sending, by each of the compute nodes assigned to the first group, a first test message to each adjacent compute node assigned to the second group; determining, by each of the compute nodes assigned to the second group, whether the first test message was received from each adjacent compute node assigned to the first group; and notifying a user, by each of the compute nodes assigned to the second group, whether the first test message was received.

Target Control in Logical Models Using the Domain of Influence of Nodes.

PubMed

Yang, Gang; Gómez Tejeda Zañudo, Jorge; Albert, Réka

2018-01-01

Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control and its special case of target control, is a promising avenue toward developing disease therapies. In target control it is assumed that a small subset of nodes is most relevant to the system's state and the goal is to drive the target nodes into their desired states. An example of target control would be driving a cell to commit to apoptosis (programmed cell death). From the experimental perspective, gene knockout, pharmacological inhibition of proteins, and providing sustained external signals are among practical intervention techniques. We identify methodologies to use the stabilizing effect of sustained interventions for target control in Boolean network models of biomolecular networks. Specifically, we define the domain of influence (DOI) of a node (in a certain state) to be the nodes (and their corresponding states) that will be ultimately stabilized by the sustained state of this node regardless of the initial state of the system. We also define the related concept of the logical domain of influence (LDOI) of a node, and develop an algorithm for its identification using an auxiliary network that incorporates the regulatory logic. This way a solution to the target control problem is a set of nodes whose DOI can cover the desired target node states. We perform greedy randomized adaptive search in node state space to find such solutions. We apply our strategy to in silico biological network models of real systems to demonstrate its effectiveness.

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

PubMed Central

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

PubMed

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

Extreme events and event size fluctuations in biased random walks on networks.

PubMed

Kishore, Vimal; Santhanam, M S; Amritkar, R E

2012-05-01

Random walk on discrete lattice models is important to understand various types of transport processes. The extreme events, defined as exceedences of the flux of walkers above a prescribed threshold, have been studied recently in the context of complex networks. This was motivated by the occurrence of rare events such as traffic jams, floods, and power blackouts which take place on networks. In this work, we study extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology. The walkers preferentially choose to hop toward the hubs or small degree nodes. In this setting, we show that extremely large fluctuations in event sizes are possible on small degree nodes when the walkers are biased toward the hubs. In particular, we obtain the distribution of event sizes on the network. Further, the probability for the occurrence of extreme events on any node in the network depends on its "generalized strength," a measure of the ability of a node to attract walkers. The generalized strength is a function of the degree of the node and that of its nearest neighbors. We obtain analytical and simulation results for the probability of occurrence of extreme events on the nodes of a network using a generalized random walk model. The result reveals that the nodes with a larger value of generalized strength, on average, display lower probability for the occurrence of extreme events compared to the nodes with lower values of generalized strength.

Efficient Deployment of Key Nodes for Optimal Coverage of Industrial Mobile Wireless Networks

PubMed Central

Li, Xiaomin; Li, Di; Dong, Zhijie; Hu, Yage; Liu, Chengliang

2018-01-01

In recent years, industrial wireless networks (IWNs) have been transformed by the introduction of mobile nodes, and they now offer increased extensibility, mobility, and flexibility. Nevertheless, mobile nodes pose efficiency and reliability challenges. Efficient node deployment and management of channel interference directly affect network system performance, particularly for key node placement in clustered wireless networks. This study analyzes this system model, considering both industrial properties of wireless networks and their mobility. Then, static and mobile node coverage problems are unified and simplified to target coverage problems. We propose a novel strategy for the deployment of clustered heads in grouped industrial mobile wireless networks (IMWNs) based on the improved maximal clique model and the iterative computation of new candidate cluster head positions. The maximal cliques are obtained via a double-layer Tabu search. Each cluster head updates its new position via an improved virtual force while moving with full coverage to find the minimal inter-cluster interference. Finally, we develop a simulation environment. The simulation results, based on a performance comparison, show the efficacy of the proposed strategies and their superiority over current approaches. PMID:29439439

Node Survival in Networks under Correlated Attacks

PubMed Central

Hao, Yan; Armbruster, Dieter; Hütt, Marc-Thorsten

2015-01-01

We study the interplay between correlations, dynamics, and networks for repeated attacks on a socio-economic network. As a model system we consider an insurance scheme against disasters that randomly hit nodes, where a node in need receives support from its network neighbors. The model is motivated by gift giving among the Maasai called Osotua. Survival of nodes under different disaster scenarios (uncorrelated, spatially, temporally and spatio-temporally correlated) and for different network architectures are studied with agent-based numerical simulations. We find that the survival rate of a node depends dramatically on the type of correlation of the disasters: Spatially and spatio-temporally correlated disasters increase the survival rate; purely temporally correlated disasters decrease it. The type of correlation also leads to strong inequality among the surviving nodes. We introduce the concept of disaster masking to explain some of the results of our simulations. We also analyze the subsets of the networks that were activated to provide support after fifty years of random disasters. They show qualitative differences for the different disaster scenarios measured by path length, degree, clustering coefficient, and number of cycles. PMID:25932635

Fault-Tolerant Local-Area Network

NASA Technical Reports Server (NTRS)

Morales, Sergio; Friedman, Gary L.

1988-01-01

Local-area network (LAN) for computers prevents single-point failure from interrupting communication between nodes of network. Includes two complete cables, LAN 1 and LAN 2. Microprocessor-based slave switches link cables to network-node devices as work stations, print servers, and file servers. Slave switches respond to commands from master switch, connecting nodes to two cable networks or disconnecting them so they are completely isolated. System monitor and control computer (SMC) acts as gateway, allowing nodes on either cable to communicate with each other and ensuring that LAN 1 and LAN 2 are fully used when functioning properly. Network monitors and controls itself, automatically routes traffic for efficient use of resources, and isolates and corrects its own faults, with potential dramatic reduction in time out of service.

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

PubMed

Crichton, Gamal; Guo, Yufan; Pyysalo, Sampo; Korhonen, Anna

2018-05-21

Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). It can be done using a classifier to output the probability of link formation between nodes. Recently several works have used neural networks to create node representations which allow rich inputs to neural classifiers. Preliminary works were done on this and report promising results. However they did not use realistic settings like time-slicing, evaluate performances with comprehensive metrics or explain when or why neural network methods outperform. We investigated how inputs from four node representation algorithms affect performance of a neural link predictor on random- and time-sliced biomedical graphs of real-world sizes (∼ 6 million edges) containing information relevant to DTI, PPI and LBD. We compared the performance of the neural link predictor to those of established baselines and report performance across five metrics. In random- and time-sliced experiments when the neural network methods were able to learn good node representations and there was a negligible amount of disconnected nodes, those approaches outperformed the baselines. In the smallest graph (∼ 15,000 edges) and in larger graphs with approximately 14% disconnected nodes, baselines such as Common Neighbours proved a justifiable choice for link prediction. At low recall levels (∼ 0.3) the approaches were mostly equal, but at higher recall levels across all nodes and average performance at individual nodes, neural network approaches were superior. Analysis showed that neural network methods performed well on links between nodes with no previous common neighbours; potentially the most interesting links. Additionally, while neural network methods benefit from large amounts of data, they require considerable amounts of computational resources to utilise them. Our results indicate that when there is enough data for the neural network methods to use and there are a negligible amount of disconnected nodes, those approaches outperform the baselines. At low recall levels the approaches are mostly equal but at higher recall levels and average performance at individual nodes, neural network approaches are superior. Performance at nodes without common neighbours which indicate more unexpected and perhaps more useful links account for this.

An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility.

PubMed

Park, Jihong; Kim, Ki-Hyung; Kim, Kangseok

2017-04-19

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. This paper proposes an algorithm to support node mobility in RPL in an energy-efficient manner and describes its operating principle based on different scenarios. The proposed algorithm supports the mobility of nodes by dynamically adjusting the transmission interval of the messages that request the route based on the speed and direction of the motion of mobile nodes, as well as the costs between neighboring nodes. The performance of the proposed algorithm and previous algorithms for supporting node mobility were examined experimentally. From the experiment, it was observed that the proposed algorithm requires fewer messages per unit time for selecting a new parent node following the movement of a mobile node. Since fewer messages are used to select a parent node, the energy consumption is also less than that of previous algorithms.

An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility

PubMed Central

Park, Jihong; Kim, Ki-Hyung; Kim, Kangseok

2017-01-01

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. This paper proposes an algorithm to support node mobility in RPL in an energy-efficient manner and describes its operating principle based on different scenarios. The proposed algorithm supports the mobility of nodes by dynamically adjusting the transmission interval of the messages that request the route based on the speed and direction of the motion of mobile nodes, as well as the costs between neighboring nodes. The performance of the proposed algorithm and previous algorithms for supporting node mobility were examined experimentally. From the experiment, it was observed that the proposed algorithm requires fewer messages per unit time for selecting a new parent node following the movement of a mobile node. Since fewer messages are used to select a parent node, the energy consumption is also less than that of previous algorithms. PMID:28422084

On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies

PubMed Central

Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Rodenas-Herraiz, David; Cruz-Martinez, Felipe; Garcia-Sanchez, Felipe

2016-01-01

Wireless Multimedia Sensor Networks (WMSNs) are a special type of Wireless Sensor Network (WSN) where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES) mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks. PMID:27164106

On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies.

PubMed

Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Rodenas-Herraiz, David; Cruz-Martinez, Felipe; Garcia-Sanchez, Felipe

2016-05-05

Wireless Multimedia Sensor Networks (WMSNs) are a special type of Wireless Sensor Network (WSN) where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES) mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks.

Efficient weighting strategy for enhancing synchronizability of complex networks

NASA Astrophysics Data System (ADS)

Wang, Youquan; Yu, Feng; Huang, Shucheng; Tu, Juanjuan; Chen, Yan

2018-04-01

Networks with high propensity to synchronization are desired in many applications ranging from biology to engineering. In general, there are two ways to enhance the synchronizability of a network: link rewiring and/or link weighting. In this paper, we propose a new link weighting strategy based on the concept of the neighborhood subgroup. The neighborhood subgroup of a node i through node j in a network, i.e. Gi→j, means that node u belongs to Gi→j if node u belongs to the first-order neighbors of j (not include i). Our proposed weighting schema used the local and global structural properties of the networks such as the node degree, betweenness centrality and closeness centrality measures. We applied the method on scale-free and Watts-Strogatz networks of different structural properties and show the good performance of the proposed weighting scheme. Furthermore, as model networks cannot capture all essential features of real-world complex networks, we considered a number of undirected and unweighted real-world networks. To the best of our knowledge, the proposed weighting strategy outperformed the previously published weighting methods by enhancing the synchronizability of these real-world networks.

Detecting and Preventing Sybil Attacks in Wireless Sensor Networks Using Message Authentication and Passing Method.

PubMed

Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani

2015-01-01

Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting.

Detecting and Preventing Sybil Attacks in Wireless Sensor Networks Using Message Authentication and Passing Method

PubMed Central

Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani

2015-01-01

Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting. PMID:26236773

A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

PubMed

Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

2018-03-23

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks

PubMed Central

2018-01-01

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. PMID:29570691

Using LTI Dynamics to Identify the Influential Nodes in a Network

PubMed Central

Jorswieck, Eduard; Scheunert, Christian

2016-01-01

Networks are used for modeling numerous technical, social or biological systems. In order to better understand the system dynamics, it is a matter of great interest to identify the most important nodes within the network. For a large set of problems, whether it is the optimal use of available resources, spreading information efficiently or even protection from malicious attacks, the most important node is the most influential spreader, the one that is capable of propagating information in the shortest time to a large portion of the network. Here we propose the Node Imposed Response (NiR), a measure which accurately evaluates node spreading power. It outperforms betweenness, degree, k-shell and h-index centrality in many cases and shows the similar accuracy to dynamics-sensitive centrality. We utilize the system-theoretic approach considering the network as a Linear Time-Invariant system. By observing the system response we can quantify the importance of each node. In addition, our study provides a robust tool set for various protective strategies. PMID:28030548

Hop Optimization and Relay Node Selection in Multi-hop Wireless Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Li, Xiaohua(Edward)

In this paper we propose an efficient approach to determine the optimal hops for multi-hop ad hoc wireless networks. Based on the assumption that nodes use successive interference cancellation (SIC) and maximal ratio combining (MRC) to deal with mutual interference and to utilize all the received signal energy, we show that the signal-to-interference-plus-noise ratio (SINR) of a node is determined only by the nodes before it, not the nodes after it, along a packet forwarding path. Based on this observation, we propose an iterative procedure to select the relay nodes and to calculate the path SINR as well as capacity of an arbitrary multi-hop packet forwarding path. The complexity of the algorithm is extremely low, and scaling well with network size. The algorithm is applicable in arbitrarily large networks. Its performance is demonstrated as desirable by simulations. The algorithm can be helpful in analyzing the performance of multi-hop wireless networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Dr. Li; Cui, Xiaohui; Cemerlic, Alma

Ad hoc networks are very helpful in situations when no fixed network infrastructure is available, such as natural disasters and military conflicts. In such a network, all wireless nodes are equal peers simultaneously serving as both senders and routers for other nodes. Therefore, how to route packets through reliable paths becomes a fundamental problems when behaviors of certain nodes deviate from wireless ad hoc routing protocols. We proposed a novel Dirichlet reputation model based on Bayesian inference theory which evaluates reliability of each node in terms of packet delivery. Our system offers a way to predict and select a reliablemore » path through combination of first-hand observation and second-hand reputation reports. We also proposed moving window mechanism which helps to adjust ours responsiveness of our system to changes of node behaviors. We integrated the Dirichlet reputation into routing protocol of wireless ad hoc networks. Our extensive simulation indicates that our proposed reputation system can improve good throughput of the network and reduce negative impacts caused by misbehaving nodes.« less

Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks

PubMed Central

Jiang, Peng; Wang, Xingmin; Jiang, Lurong

2015-01-01

Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA). This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA). In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA), which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments. PMID:26184209

Spatial analysis of bus transport networks using network theory

NASA Astrophysics Data System (ADS)

Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

2018-07-01

In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison of the simulation and the empirical data provides useful information on how bus operators can better plan their routes and deploy stops considering the geographically significant nodes.

An Optimized Hidden Node Detection Paradigm for Improving the Coverage and Network Efficiency in Wireless Multimedia Sensor Networks

PubMed Central

Alanazi, Adwan; Elleithy, Khaled

2016-01-01

Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node– continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches. PMID:27618048

The importance of centralities in dark network value chains

NASA Astrophysics Data System (ADS)

Toth, Noemi; Gulyás, László; Legendi, Richard O.; Duijn, Paul; Sloot, Peter M. A.; Kampis, George

2013-09-01

This paper introduces three novel centrality measures based on the nodes' role in the operation of a joint task, i.e., their position in a criminal network value chain. For this, we consider networks where nodes have attributes describing their "capabilities" or "colors", i.e., the possible roles they may play in a value chain. A value chain here is understood as a series of tasks to be performed in a specific order, each requiring a specific capability. The first centrality notion measures how many value chain instances a given node participates in. The other two assess the costs of replacing a node in the value chain in case the given node is no longer available to perform the task. The first of them considers the direct distance (shortest path length) between the node in question and its nearest replacement, while the second evaluates the actual replacement process, assuming that preceding and following nodes in the network should each be able to find and contact the replacement. In this report, we demonstrate the properties of the new centrality measures using a few toy examples and compare them to classic centralities, such as betweenness, closeness and degree centrality. We also apply the new measures to randomly colored empirical networks. We find that the newly introduced centralities differ sufficiently from the classic measures, pointing towards different aspects of the network. Our results also pinpoint the difference between having a replacement node in the network and being able to find one. This is the reason why "introduction distance" often has a noticeable correlation with betweenness. Our studies show that projecting value chains over networks may significantly alter the nodes' perceived importance. These insights might have important implications for the way law enforcement or intelligence agencies look at the effectiveness of dark network disruption strategies over time.

Impact of constrained rewiring on network structure and node dynamics

NASA Astrophysics Data System (ADS)

Rattana, P.; Berthouze, L.; Kiss, I. Z.

2014-11-01

In this paper, we study an adaptive spatial network. We consider a susceptible-infected-susceptible (SIS) epidemic on the network, with a link or contact rewiring process constrained by spatial proximity. In particular, we assume that susceptible nodes break links with infected nodes independently of distance and reconnect at random to susceptible nodes available within a given radius. By systematically manipulating this radius we investigate the impact of rewiring on the structure of the network and characteristics of the epidemic. We adopt a step-by-step approach whereby we first study the impact of rewiring on the network structure in the absence of an epidemic, then with nodes assigned a disease status but without disease dynamics, and finally running network and epidemic dynamics simultaneously. In the case of no labeling and no epidemic dynamics, we provide both analytic and semianalytic formulas for the value of clustering achieved in the network. Our results also show that the rewiring radius and the network's initial structure have a pronounced effect on the endemic equilibrium, with increasingly large rewiring radiuses yielding smaller disease prevalence.

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

PubMed Central

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; Gonzalez-Castaño, Francisco Javier

2013-01-01

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively. PMID:23939582

On maximizing the lifetime of Wireless Sensor Networks by optimally assigning energy supplies.

PubMed

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; González-Castano, Francisco Javier

2013-08-09

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.

Network analysis of translocated Takahe populations to identify disease surveillance targets.

PubMed

Grange, Zoë L; VAN Andel, Mary; French, Nigel P; Gartrell, Brett D

2014-04-01

Social network analysis is being increasingly used in epidemiology and disease modeling in humans, domestic animals, and wildlife. We investigated this tool in describing a translocation network (area that allows movement of animals between geographically isolated locations) used for the conservation of an endangered flightless rail, the Takahe (Porphyrio hochstetteri). We collated records of Takahe translocations within New Zealand and used social network principles to describe the connectivity of the translocation network. That is, networks were constructed and analyzed using adjacency matrices with values based on the tie weights between nodes. Five annual network matrices were created using the Takahe data set, each incremental year included records of previous years. Weights of movements between connected locations were assigned by the number of Takahe moved. We calculated the number of nodes (i(total)) and the number of ties (t(total)) between the nodes. To quantify the small-world character of the networks, we compared the real networks to random graphs of the equivalent size, weighting, and node strength. Descriptive analysis of cumulative annual Takahe movement networks involved determination of node-level characteristics, including centrality descriptors of relevance to disease modeling such as weighted measures of in degree (k(i)(in)), out degree (k(i)(out)), and betweenness (B(i)). Key players were assigned according to the highest node measure of k(i)(in), k(i)(out), and B(i) per network. Networks increased in size throughout the time frame considered. The network had some degree small-world characteristics. Nodes with the highest cumulative tie weights connecting them were the captive breeding center, the Murchison Mountains and 2 offshore islands. The key player fluctuated between the captive breeding center and the Murchison Mountains. The cumulative networks identified the captive breeding center every year as the hub of the network until the final network in 2011. Likewise, the wild Murchison Mountains population was consistently the sink of the network. Other nodes, such as the offshore islands and the wildlife hospital, varied in importance over time. Common network descriptors and measures of centrality identified key locations for targeting disease surveillance. The visual representation of movements of animals in a population that this technique provides can aid decision makers when they evaluate translocation proposals or attempt to control a disease outbreak. © 2014 Society for Conservation Biology.

Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs.

PubMed

Alvarez, Carlos F; Palafox, Luis E; Aguilar, Leocundo; Sanchez, Mauricio A; Martinez, Luis G

2016-01-01

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node's behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder.

Link prediction based on local community properties

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

2016-09-01

The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

A new centrality measure for identifying influential nodes in social networks

NASA Astrophysics Data System (ADS)

Rhouma, Delel; Ben Romdhane, Lotfi

2018-04-01

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

PubMed

Duarte, Francisco; Martins, Bruno; Pinto, Cátia Sousa; Silva, Mário J

2018-04-01

We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep neural network that combines word embeddings, recurrent units, and neural attention, for the generation of intermediate representations of the textual contents. The neural network also explores the hierarchical nature of the input data, by building representations from the sequences of words within individual fields, which are then combined according to the sequences of fields that compose the inputs. Moreover, we explore innovative mechanisms for initializing the weights of the final nodes of the network, leveraging co-occurrences between classes together with the hierarchical structure of ICD-10. Experimental results attest to the contribution of the different neural network components. Our best model achieves accuracy scores over 89%, 81%, and 76%, respectively for ICD-10 chapters, blocks, and full-codes. Through examples, we also show that our method can produce interpretable results, useful for public health surveillance. Copyright © 2018 Elsevier Inc. All rights reserved.

Prevention of Malicious Nodes Communication in MANETs by Using Authorized Tokens

NASA Astrophysics Data System (ADS)

Chandrakant, N.; Shenoy, P. Deepa; Venugopal, K. R.; Patnaik, L. M.

A rapid increase of wireless networks and mobile computing applications has changed the landscape of network security. A MANET is more susceptible to the attacks than wired network. As a result, attacks with malicious intent have been and will be devised to take advantage of these vulnerabilities and to cripple the MANET operation. Hence we need to search for new architecture and mechanisms to protect the wireless networks and mobile computing applications. In this paper, we examine the nodes that come under the vicinity of base node and members of the network and communication is provided to genuine nodes only. It is found that the proposed algorithm is a effective algorithm for security in MANETs.

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Distributed clone detection in static wireless sensor networks: random walk with network division.

PubMed

Khan, Wazir Zada; Aalsalem, Mohammed Y; Saad, N M

2015-01-01

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.

Complex Network Analysis of CA3 Transcriptome Reveals Pathogenic and Compensatory Pathways in Refractory Temporal Lobe Epilepsy

PubMed Central

Bando, Silvia Yumi; Silva, Filipi Nascimento; Costa, Luciano da Fontoura; Silva, Alexandre V.; Pimentel-Silva, Luciana R.; Castro, Luiz HM.; Wen, Hung-Tzu; Amaro, Edson; Moreira-Filho, Carlos Alberto

2013-01-01

We previously described – studying transcriptional signatures of hippocampal CA3 explants – that febrile (FS) and afebrile (NFS) forms of refractory mesial temporal lobe epilepsy constitute two distinct genomic phenotypes. That network analysis was based on a limited number (hundreds) of differentially expressed genes (DE networks) among a large set of valid transcripts (close to two tens of thousands). Here we developed a methodology for complex network visualization (3D) and analysis that allows the categorization of network nodes according to distinct hierarchical levels of gene-gene connections (node degree) and of interconnection between node neighbors (concentric node degree). Hubs are highly connected nodes, VIPs have low node degree but connect only with hubs, and high-hubs have VIP status and high overall number of connections. Studying the whole set of CA3 valid transcripts we: i) obtained complete transcriptional networks (CO) for FS and NFS phenotypic groups; ii) examined how CO and DE networks are related; iii) characterized genomic and molecular mechanisms underlying FS and NFS phenotypes, identifying potential novel targets for therapeutic interventions. We found that: i) DE hubs and VIPs are evenly distributed inside the CO networks; ii) most DE hubs and VIPs are related to synaptic transmission and neuronal excitability whereas most CO hubs, VIPs and high hubs are related to neuronal differentiation, homeostasis and neuroprotection, indicating compensatory mechanisms. Complex network visualization and analysis is a useful tool for systems biology approaches to multifactorial diseases. Network centrality observed for hubs, VIPs and high hubs of CO networks, is consistent with the network disease model, where a group of nodes whose perturbation leads to a disease phenotype occupies a central position in the network. Conceivably, the chance for exerting therapeutic effects through the modulation of particular genes will be higher if these genes are highly interconnected in transcriptional networks. PMID:24278214

Effects in the network topology due to node aggregation: Empirical evidence from the domestic maritime transportation in Greece

NASA Astrophysics Data System (ADS)

Tsiotas, Dimitrios; Polyzos, Serafeim

2018-02-01

This article studies the topological consistency of spatial networks due to node aggregation, examining the changes captured between different network representations that result from nodes' grouping and they refer to the same socioeconomic system. The main purpose of this study is to evaluate what kind of topological information remains unalterable due to node aggregation and, further, to develop a framework for linking the data of an empirical network with data of its socioeconomic environment, when the latter are available for hierarchically higher levels of aggregation, in an effort to promote the interdisciplinary research in the field of complex network analysis. The research question is empirically tested on topological and socioeconomic data extracted from the Greek Maritime Network (GMN) that is modeled as a non-directed multilayer (bilayer) graph consisting of a port-layer, where nodes represent ports, and a prefecture-layer, where nodes represent coastal and insular prefectural groups of ports. The analysis highlights that the connectivity (degree) of the GMN is the most consistent aspect of this multilayer network, which preserves both the topological and the socioeconomic information through node aggregation. In terms of spatial analysis and regional science, such effects illustrate the effectiveness of the prefectural administrative division for the functionality of the Greek maritime transportation system. Overall, this approach proposes a methodological framework that can enjoy further applications about the grouping effects induced on the network topology, providing physical, technical, socioeconomic, strategic or political insights.

Systems and methods for optimal power flow on a radial network

DOEpatents

Low, Steven H.; Peng, Qiuyu

2018-04-24

Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

Social network analysis for assessment of avian influenza spread and trading patterns of backyard chickens in Nakhon Pathom, Suphan Buri and Ratchaburi, Thailand.

PubMed

Poolkhet, C; Chairatanayuth, P; Thongratsakul, S; Yatbantoong, N; Kasemsuwan, S; Damchoey, D; Rukkwamsuk, T

2013-09-01

The aim of this study is to explain the social networks of the backyard chicken in Ratchaburi, Suphan Buri and Nakhon Pathom Provinces. In this study, we designed the nodes as groups of persons or places involved in activities relating to backyard chickens. The ties are all activities related to the nodes. The study applied a partial network approach to assess the spreading pattern of avian influenza. From 557 questionnaires collected from the nodes, the researchers found that the degree (the numbers of ties that a node has) and closeness (the distance from one node to the others) centralities of Nakhon Pathom were significantly higher than those of the others (P<0.001). The results show that compared with the remaining areas, this area is more quickly connected to many links. If the avian influenza virus subtype H5N1 was released into the network, the disease would spread throughout this province more rapidly than in Ratchaburi and Suphan Buri. The betweenness centrality in each of these provinces showed no differences (P>0.05). In this study, the nodes that play an important role in all networks are farmers who raise consumable chicken, farmers who raise both consumable chicken and fighting cocks, farmers' households that connect with dominant nodes, and the owners and observers of fighting cocks at arenas and training fields. In this study, we did not find cut points or blocks in the network. Moreover, we detected a random network in all provinces. Thus, connectivity between the nodes covers long or short distances, with less predictable behaviour. Finally, this study suggests that activities between the important nodes must receive special attention for disease control during future disease outbreaks. © 2012 Blackwell Verlag GmbH.

Spreading to localized targets in complex networks

NASA Astrophysics Data System (ADS)

Sun, Ye; Ma, Long; Zeng, An; Wang, Wen-Xu

2016-12-01

As an important type of dynamics on complex networks, spreading is widely used to model many real processes such as the epidemic contagion and information propagation. One of the most significant research questions in spreading is to rank the spreading ability of nodes in the network. To this end, substantial effort has been made and a variety of effective methods have been proposed. These methods usually define the spreading ability of a node as the number of finally infected nodes given that the spreading is initialized from the node. However, in many real cases such as advertising and news propagation, the spreading only aims to cover a specific group of nodes. Therefore, it is necessary to study the spreading ability of nodes towards localized targets in complex networks. In this paper, we propose a reversed local path algorithm for this problem. Simulation results show that our method outperforms the existing methods in identifying the influential nodes with respect to these localized targets. Moreover, the influential spreaders identified by our method can effectively avoid infecting the non-target nodes in the spreading process.

Temporal-varying failures of nodes in networks

NASA Astrophysics Data System (ADS)

Knight, Georgie; Cristadoro, Giampaolo; Altmann, Eduardo G.

2015-08-01

We consider networks in which random walkers are removed because of the failure of specific nodes. We interpret the rate of loss as a measure of the importance of nodes, a notion we denote as failure centrality. We show that the degree of the node is not sufficient to determine this measure and that, in a first approximation, the shortest loops through the node have to be taken into account. We propose approximations of the failure centrality which are valid for temporal-varying failures, and we dwell on the possibility of externally changing the relative importance of nodes in a given network by exploiting the interference between the loops of a node and the cycles of the temporal pattern of failures. In the limit of long failure cycles we show analytically that the escape in a node is larger than the one estimated from a stochastic failure with the same failure probability. We test our general formalism in two real-world networks (air-transportation and e-mail users) and show how communities lead to deviations from predictions for failures in hubs.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

PubMed Central

Yang, Guisong; Liu, Shuai; He, Xingyu; Xiong, Naixue; Wu, Chunxue

2016-01-01

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density. PMID:27941662

Structural and functional properties of spatially embedded scale-free networks.

PubMed

Emmerich, Thorsten; Bunde, Armin; Havlin, Shlomo

2014-06-01

Scale-free networks have been studied mostly as non-spatially embedded systems. However, in many realistic cases, they are spatially embedded and these constraints should be considered. Here, we study the structural and functional properties of a model of scale-free (SF) spatially embedded networks. In our model, both the degree and the length of links follow power law distributions as found in many real networks. We show that not all SF networks can be embedded in space and that the largest degree of a node in the network is usually smaller than in nonembedded SF networks. Moreover, the spatial constraints (each node has only few neighboring nodes) introduce degree-degree anticorrelations (disassortativity) since two high degree nodes cannot stay close in space. We also find significant effects of space embedding on the hopping distances (chemical distance) and the vulnerability of the networks.

Rutgers University Subcontract B611610 Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soundarajan, Sucheta; Eliassi-Rad, Tina; Gallagher, Brian

Given an incomplete (i.e., partially-observed) network, which nodes should we actively probe in order to achieve the highest accuracy for a given network feature? For example, consider a cyber-network administrator who observes only a portion of the network at time t and wants to accurately identify the most important (e.g., highest PageRank) nodes in the complete network. She has a limited budget for probing the network. Of all the nodes she has observed, which should she probe in order to most accurately identify the important nodes? We propose a novel and scalable algorithm, MaxOutProbe, and evaluate it w.r.t. four networkmore » features (largest connected component, PageRank, core-periphery, and community detection), five network sampling strategies, and seven network datasets from different domains. Across a range of conditions, MaxOutProbe demonstrates consistently high performance relative to several baseline strategies« less

IJA: an efficient algorithm for query processing in sensor networks.

PubMed

Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

2011-01-01

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm.

IJA: An Efficient Algorithm for Query Processing in Sensor Networks

PubMed Central

Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

2011-01-01

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm. PMID:22319375

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

Applications of graph theory to landscape genetics

PubMed Central

Garroway, Colin J; Bowman, Jeff; Carr, Denis; Wilson, Paul J

2008-01-01

We investigated the relationships among landscape quality, gene flow, and population genetic structure of fishers (Martes pennanti) in ON, Canada. We used graph theory as an analytical framework considering each landscape as a network node. The 34 nodes were connected by 93 edges. Network structure was characterized by a higher level of clustering than expected by chance, a short mean path length connecting all pairs of nodes, and a resiliency to the loss of highly connected nodes. This suggests that alleles can be efficiently spread through the system and that extirpations and conservative harvest are not likely to affect their spread. Two measures of node centrality were negatively related to both the proportion of immigrants in a node and node snow depth. This suggests that central nodes are producers of emigrants, contain high-quality habitat (i.e., deep snow can make locomotion energetically costly) and that fishers were migrating from high to low quality habitat. A method of community detection on networks delineated five genetic clusters of nodes suggesting cryptic population structure. Our analyses showed that network models can provide system-level insight into the process of gene flow with implications for understanding how landscape alterations might affect population fitness and evolutionary potential. PMID:25567802

Exploring anti-community structure in networks with application to incompatibility of traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Zhu, Jiajing; Liu, Yongguo; Zhang, Yun; Liu, Xiaofeng; Xiao, Yonghua; Wang, Shidong; Wu, Xindong

2017-11-01

Community structure is one of the most important properties in networks, in which a node shares its most connections with the others in the same community. On the contrary, the anti-community structure means the nodes in the same group have few or no connections with each other. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a challenge to the clinical medication safety. In this paper, we propose a new anti-community detection algorithm, Random non-nEighboring nOde expansioN (REON), to find anti-communities in networks, in which a new evaluation criterion, anti-modularity, is designed to measure the quality of the obtained anti-community structure. In order to establish anti-communities in REON, we expand the node set by non-neighboring node expansion and regard the node set with the highest anti-modularity as an anti-community. Inspired by the phenomenon that the node with higher degree has greater contribution to the anti-modularity, an improved algorithm called REONI is developed by expanding node set by the non-neighboring node with the maximum degree, which greatly enhances the efficiency of REON. Experiments on synthetic and real-world networks demonstrate the superiority of the proposed algorithms over the existing methods. In addition, by applying REONI to the herb network, we find that it can discover incompatible herb combinations.

Switch for serial or parallel communication networks

DOEpatents

Crosette, D.B.

1994-07-19

A communication switch apparatus and a method for use in a geographically extensive serial, parallel or hybrid communication network linking a multi-processor or parallel processing system has a very low software processing overhead in order to accommodate random burst of high density data. Associated with each processor is a communication switch. A data source and a data destination, a sensor suite or robot for example, may also be associated with a switch. The configuration of the switches in the network are coordinated through a master processor node and depends on the operational phase of the multi-processor network: data acquisition, data processing, and data exchange. The master processor node passes information on the state to be assumed by each switch to the processor node associated with the switch. The processor node then operates a series of multi-state switches internal to each communication switch. The communication switch does not parse and interpret communication protocol and message routing information. During a data acquisition phase, the communication switch couples sensors producing data to the processor node associated with the switch, to a downlink destination on the communications network, or to both. It also may couple an uplink data source to its processor node. During the data exchange phase, the switch couples its processor node or an uplink data source to a downlink destination (which may include a processor node or a robot), or couples an uplink source to its processor node and its processor node to a downlink destination. 9 figs.

Switch for serial or parallel communication networks

DOEpatents

Crosette, Dario B.

1994-01-01

A communication switch apparatus and a method for use in a geographically extensive serial, parallel or hybrid communication network linking a multi-processor or parallel processing system has a very low software processing overhead in order to accommodate random burst of high density data. Associated with each processor is a communication switch. A data source and a data destination, a sensor suite or robot for example, may also be associated with a switch. The configuration of the switches in the network are coordinated through a master processor node and depends on the operational phase of the multi-processor network: data acquisition, data processing, and data exchange. The master processor node passes information on the state to be assumed by each switch to the processor node associated with the switch. The processor node then operates a series of multi-state switches internal to each communication switch. The communication switch does not parse and interpret communication protocol and message routing information. During a data acquisition phase, the communication switch couples sensors producing data to the processor node associated with the switch, to a downlink destination on the communications network, or to both. It also may couple an uplink data source to its processor node. During the data exchange phase, the switch couples its processor node or an uplink data source to a downlink destination (which may include a processor node or a robot), or couples an uplink source to its processor node and its processor node to a downlink destination.

Robustness of a network formed by n interdependent networks with a one-to-one correspondence of dependent nodes.

PubMed

Gao, Jianxi; Buldyrev, S V; Havlin, S; Stanley, H E

2012-06-01

Many real-world networks interact with and depend upon other networks. We develop an analytical framework for studying a network formed by n fully interdependent randomly connected networks, each composed of the same number of nodes N. The dependency links connecting nodes from different networks establish a unique one-to-one correspondence between the nodes of one network and the nodes of the other network. We study the dynamics of the cascades of failures in such a network of networks (NON) caused by a random initial attack on one of the networks, after which a fraction p of its nodes survives. We find for the fully interdependent loopless NON that the final state of the NON does not depend on the dynamics of the cascades but is determined by a uniquely defined mutual giant component of the NON, which generalizes both the giant component of regular percolation of a single network (n=1) and the recently studied case of the mutual giant component of two interdependent networks (n=2). We also find that the mutual giant component does not depend on the topology of the NON and express it in terms of generating functions of the degree distributions of the network. Our results show that, for any n≥2 there exists a critical p=p(c)>0 below which the mutual giant component abruptly collapses from a finite nonzero value for p≥p(c) to zero for p2, a RR NON is stable for any n with p(c)<1). This results arises from the critical role played by singly connected nodes which exist in an ER NON and enhance the cascading failures, but do not exist in a RR NON.

A Distributed Energy-Aware Trust Management System for Secure Routing in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Stelios, Yannis; Papayanoulas, Nikos; Trakadas, Panagiotis; Maniatis, Sotiris; Leligou, Helen C.; Zahariadis, Theodore

Wireless sensor networks are inherently vulnerable to security attacks, due to their wireless operation. The situation is further aggravated because they operate in an infrastructure-less environment, which mandates the cooperation among nodes for all networking tasks, including routing, i.e. all nodes act as “routers”, forwarding the packets generated by their neighbours in their way to the sink node. This implies that malicious nodes (denying their cooperation) can significantly affect the network operation. Trust management schemes provide a powerful tool for the detection of unexpected node behaviours (either faulty or malicious). Once misbehaving nodes are detected, their neighbours can use this information to avoid cooperating with them either for data forwarding, data aggregation or any other cooperative function. We propose a secure routing solution based on a novel distributed trust management system, which allows for fast detection of a wide set of attacks and also incorporates energy awareness.

An efficient collaborative approach for black hole attack discovery and mitigating its impact in manet

NASA Astrophysics Data System (ADS)

Devipriya, K.; Ivy, B. Persis Urbana; Prabha, D.

2018-04-01

A mobile ad hoc network (MANET) is an assemblage of nodes composed of mobile devices coupled in various ways wirelessly which do not have any central administration. Each node in MANET cooperates in forwarding packets in the network. This type of collaboration incurs high cost but there exits nodes that declines to cooperate leading to selfish conduct of nodes which effects overall network performance. To discover the attacks caused by such nodes, a renowned mechanism using watchdog can be deployed. In infrastructure less network attack detection and reaction and high false positives, false negatives initiating black hole attack becomes major issue in watchdog. This paper put forward a collaborative approach for identifying such attacks in MANET. Through abstract analysis and extensive simulation of this approach, the detection time of misbehaved nodes is reduced and substantial enhancement in overhead and throughput is witnessed.

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

Competing contact processes in the Watts-Strogatz network

NASA Astrophysics Data System (ADS)

Rybak, Marcin; Malarz, Krzysztof; Kułakowski, Krzysztof

2016-06-01

We investigate two competing contact processes on a set of Watts-Strogatz networks with the clustering coefficient tuned by rewiring. The base for network construction is one-dimensional chain of N sites, where each site i is directly linked to nodes labelled as i ± 1 and i ± 2. So initially, each node has the same degree k i = 4. The periodic boundary conditions are assumed as well. For each node i the links to sites i + 1 and i + 2 are rewired to two randomly selected nodes so far not-connected to node i. An increase of the rewiring probability q influences the nodes degree distribution and the network clusterization coefficient 𝓒. For given values of rewiring probability q the set 𝓝(q)={𝓝1,𝓝2,...,𝓝 M } of M networks is generated. The network's nodes are decorated with spin-like variables s i ∈ { S,D }. During simulation each S node having a D-site in its neighbourhood converts this neighbour from D to S state. Conversely, a node in D state having at least one neighbour also in state D-state converts all nearest-neighbours of this pair into D-state. The latter is realized with probability p. We plot the dependence of the nodes S final density n S T on initial nodes S fraction n S 0. Then, we construct the surface of the unstable fixed points in (𝓒, p, n S 0) space. The system evolves more often toward n S T for (𝓒, p, n S 0) points situated above this surface while starting simulation with (𝓒, p, n S 0) parameters situated below this surface leads system to n S T =0. The points on this surface correspond to such value of initial fraction n S * of S nodes (for fixed values 𝓒 and p) for which their final density is n S T=1/2.

Providing Self-Healing Ability for Wireless Sensor Node by Using Reconfigurable Hardware

PubMed Central

Yuan, Shenfang; Qiu, Lei; Gao, Shang; Tong, Yao; Yang, Weiwei

2012-01-01

Wireless sensor networks (WSNs) have received tremendous attention over the past ten years. In engineering applications of WSNs, a number of sensor nodes are usually spread across some specific geographical area. Some of these nodes have to work in harsh environments. Dependability of the Wireless Sensor Network (WSN) is very important for its successful applications in the engineering area. In ordinary research, when a node has a failure, it is usually discarded and the network is reorganized to ensure the normal operation of the WSN. Using appropriate WSN re-organization methods, though the sensor networks can be reorganized, this causes additional maintenance costs and sometimes still decreases the function of the networks. In those situations where the sensor networks cannot be reorganized, the performance of the whole WSN will surely be degraded. In order to ensure the reliable and low cost operation of WSNs, a method to develop a wireless sensor node with self-healing ability based on reconfigurable hardware is proposed in this paper. Two self-healing WSN node realization paradigms based on reconfigurable hardware are presented, including a redundancy-based self-healing paradigm and a whole FPAA/FPGA based self-healing paradigm. The nodes designed with the self-healing ability can dynamically change their node configurations to repair the nodes' hardware failures. To demonstrate these two paradigms, a strain sensor node is adopted as an illustration to show the concepts. Two strain WSN sensor nodes with self-healing ability are developed respectively according to the proposed self-healing paradigms. Evaluation experiments on self-healing ability and power consumption are performed. Experimental results show that the developed nodes can self-diagnose the failures and recover to a normal state automatically. The research presented can improve the robustness of WSNs and reduce the maintenance cost of WSNs in engineering applications. PMID:23202176

Brain Network Changes and Memory Decline in Aging

PubMed Central

Beason-Held, Lori L.; Hohman, Timothy J.; Venkatraman, Vijay; An, Yang; Resnick, Susan M.

2016-01-01

One theory of age-related cognitive decline proposes that changes within the default mode network (DMN) of the brain impact the ability to successfully perform cognitive operations. To investigate this theory, we examined functional covariance within brain networks using regional cerebral blood flow data, measured by 15O-water PET, from 99 participants (mean baseline age 68.6 ±7.5) in the Baltimore Longitudinal Study of Aging collected over a 7.4 year period. The sample was divided in tertiles based on longitudinal performance on a verbal recognition memory task administered during scanning, and functional covariance was compared between the upper (improvers) and lower (decliners) tertile groups. The DMN and verbal memory networks (VMN) were then examined during the verbal memory scan condition. For each network, group differences in node-to-network coherence and individual node-to-node covariance relationships were assessed at baseline and in change over time. Compared with improvers, decliners showed differences in node-to-network coherence and in node-to-node relationships in the DMN but not the VMN during verbal memory. These DMN differences reflected greater covariance with better task performance at baseline and both increasing and declining covariance with declining task performance over time for decliners. When examined during the resting state alone, the direction of change in DMN covariance was similar to that seen during task performance, but node-to-node relationships differed from those observed during the task condition. These results suggest that disengagement of DMN components during task performance is not essential for successful cognitive performance as previously proposed. Instead, a proper balance in network processes may be needed to support optimal task performance. PMID:27319002

Robust Routing Protocol For Digital Messages

NASA Technical Reports Server (NTRS)

Marvit, Maclen

1994-01-01

Refinement of ditigal-message-routing protocol increases fault tolerance of polled networks. AbNET-3 is latest of generic AbNET protocols for transmission of messages among computing nodes. AbNET concept described in "Multiple-Ring Digital Communication Network" (NPO-18133). Specifically aimed at increasing fault tolerance of network in broadcast mode, in which one node broadcasts message to and receives responses from all other nodes. Communication in network of computers maintained even when links fail.

Robustness of networks with assortative dependence groups

NASA Astrophysics Data System (ADS)

Wang, Hui; Li, Ming; Deng, Lin; Wang, Bing-Hong

2018-07-01

Assortativity is one of the important characteristics in real networks. To study the effects of this characteristic on the robustness of networks, we propose a percolation model on networks with assortative dependence group. The assortativity in this model means that the nodes with the same or similar degrees form dependence groups, for which one node fails, other nodes in the same group are very likely to fail. We find that the assortativity makes the nodes with large degrees easier to survive from the cascading failure. In this way, such networks are more robust than that with random dependence group, which also proves the assortative network is robust in another perspective. Furthermore, we also present exact solutions to the size of the giant component and the critical point, which are in agreement with the simulation results well.

A generalized approach to complex networks

NASA Astrophysics Data System (ADS)

Costa, L. Da F.; da Rocha, L. E. C.

2006-03-01

This work describes how the formalization of complex network concepts in terms of discrete mathematics, especially mathematical morphology, allows a series of generalizations and important results ranging from new measurements of the network topology to new network growth models. First, the concepts of node degree and clustering coefficient are extended in order to characterize not only specific nodes, but any generic subnetwork. Second, the consideration of distance transform and rings are used to further extend those concepts in order to obtain a signature, instead of a single scalar measurement, ranging from the single node to whole graph scales. The enhanced discriminative potential of such extended measurements is illustrated with respect to the identification of correspondence between nodes in two complex networks, namely a protein-protein interaction network and a perturbed version of it.

Percolation of localized attack on isolated and interdependent random networks

NASA Astrophysics Data System (ADS)

Shao, Shuai; Huang, Xuqing; Stanley, H. Eugene; Havlin, Shlomo

2014-03-01

Percolation properties of isolated and interdependent random networks have been investigated extensively. The focus of these studies has been on random attacks where each node in network is attacked with the same probability or targeted attack where each node is attacked with a probability being a function of its centrality, such as degree. Here we discuss a new type of realistic attacks which we call a localized attack where a group of neighboring nodes in the networks are attacked. We attack a randomly chosen node, its neighbors, and its neighbor of neighbors and so on, until removing a fraction (1 - p) of the network. This type of attack reflects damages due to localized disasters, such as earthquakes, floods and war zones in real-world networks. We study, both analytically and by simulations the impact of localized attack on percolation properties of random networks with arbitrary degree distributions and discuss in detail random regular (RR) networks, Erdős-Rényi (ER) networks and scale-free (SF) networks. We extend and generalize our theoretical and simulation results of single isolated networks to networks formed of interdependent networks.

Method and computer product to increase accuracy of time-based software verification for sensor networks

DOEpatents

Foo Kune, Denis [Saint Paul, MN; Mahadevan, Karthikeyan [Mountain View, CA

2011-01-25

A recursive verification protocol to reduce the time variance due to delays in the network by putting the subject node at most one hop from the verifier node provides for an efficient manner to test wireless sensor nodes. Since the software signatures are time based, recursive testing will give a much cleaner signal for positive verification of the software running on any one node in the sensor network. In this protocol, the main verifier checks its neighbor, who in turn checks its neighbor, and continuing this process until all nodes have been verified. This ensures minimum time delays for the software verification. Should a node fail the test, the software verification downstream is halted until an alternative path (one not including the failed node) is found. Utilizing techniques well known in the art, having a node tested twice, or not at all, can be avoided.

A Specific Mapping Study Using Fluorescence Sentinel Lymph Node Detection in Patients with Intermediate- and High-risk Prostate Cancer Undergoing Extended Pelvic Lymph Node Dissection.

PubMed

Nguyen, Daniel P; Huber, Philipp M; Metzger, Tobias A; Genitsch, Vera; Schudel, Hans H; Thalmann, George N

2016-11-01

Sentinel lymph node (SLN) detection techniques have the potential to change the standard of surgical care for patients with prostate cancer. We performed a lymphatic mapping study and determined the value of fluorescence SLN detection with indocyanine green (ICG) for the detection of lymph node metastases in intermediate- and high-risk patients undergoing radical prostatectomy and extended pelvic lymph node dissection. A total of 42 patients received systematic or specific ICG injections into the prostate base, the midportion, the apex, the left lobe, or the right lobe. We found (1) that external and internal iliac regions encompass the majority of SLNs, (2) that common iliac regions contain up to 22% of all SLNs, (3) that a prostatic lobe can drain into the contralateral group of pelvic lymph nodes, and (4) that the fossa of Marcille also receives significant drainage. Among the 12 patients who received systematic ICG injections, 5 (42%) had a total of 29 lymph node metastases. Of these, 16 nodes were ICG positive, yielding 55% sensitivity. The complex drainage pattern of the prostate and the low sensitivity of ICG for the detection of lymph node metastases reported in our study highlight the difficulties related to the implementation of SNL techniques in prostate cancer. There is controversy about how extensive lymph node dissection (LND) should be during prostatectomy. We investigated the lymphatic drainage of the prostate and whether sentinel node fluorescence techniques would be useful to detect node metastases. We found that the drainage pattern is complex and that the sentinel node technique is not able to replace extended pelvic LND. Copyright © 2016. Published by Elsevier B.V.

Optimal navigation for characterizing the role of the nodes in complex networks

NASA Astrophysics Data System (ADS)

Cajueiro, Daniel O.

2010-05-01

In this paper, we explore how the approach of optimal navigation (Cajueiro (2009) [33]) can be used to evaluate the centrality of a node and to characterize its role in a network. Using the subway network of Boston and the London rapid transit rail as proxies for complex networks, we show that the centrality measures inherited from the approach of optimal navigation may be considered if one desires to evaluate the centrality of the nodes using other pieces of information beyond the geometric properties of the network. Furthermore, evaluating the correlations between these inherited measures and classical measures of centralities such as the degree of a node and the characteristic path length of a node, we have found two classes of results. While for the London rapid transit rail, these inherited measures can be easily explained by these classical measures of centrality, for the Boston underground transportation system we have found nontrivial results.

Efficient packet transportation on complex networks with nonuniform node capacity distribution

NASA Astrophysics Data System (ADS)

He, Xuan; Niu, Kai; He, Zhiqiang; Lin, Jiaru; Jiang, Zhong-Yuan

2015-03-01

Provided that node delivery capacity may be not uniformly distributed in many realistic networks, we present a node delivery capacity distribution in which each node capacity is composed of uniform fraction and degree related proportion. Based on the node delivery capacity distribution, we construct a novel routing mechanism called efficient weighted routing (EWR) strategy to enhance network traffic capacity and transportation efficiency. Compared with the shortest path routing and the efficient routing strategies, the EWR achieves the highest traffic capacity. After investigating average path length, network diameter, maximum efficient betweenness, average efficient betweenness, average travel time and average traffic load under extensive simulations, it indicates that the EWR appears to be a very effective routing method. The idea of this routing mechanism gives us a good insight into network science research. The practical use of this work is prospective in some real complex systems such as the Internet.

Network exploitation using WAMI tracks

NASA Astrophysics Data System (ADS)

Rimey, Ray; Record, Jim; Keefe, Dan; Kennedy, Levi; Cramer, Chris

2011-06-01

Creating and exploiting network models from wide area motion imagery (WAMI) is an important task for intelligence analysis. Tracks of entities observed moving in the WAMI sensor data are extracted, then large numbers of tracks are studied over long time intervals to determine specific locations that are visited (e.g., buildings in an urban environment), what locations are related to other locations, and the function of each location. This paper describes several parts of the network detection/exploitation problem, and summarizes a solution technique for each: (a) Detecting nodes; (b) Detecting links between known nodes; (c) Node attributes to characterize a node; (d) Link attributes to characterize each link; (e) Link structure inferred from node attributes and vice versa; and (f) Decomposing a detected network into smaller networks. Experimental results are presented for each solution technique, and those are used to discuss issues for each problem part and its solution technique.

Going End to End to Deliver High-Speed Data

NASA Technical Reports Server (NTRS)

2005-01-01

By the end of the 1990s, the optical fiber "backbone" of the telecommunication and data-communication networks had evolved from megabits-per-second transmission rates to gigabits-per-second transmission rates. Despite this boom in bandwidth, however, users at the end nodes were still not being reached on a consistent basis. (An end node is any device that does not behave like a router or a managed hub or switch. Examples of end node objects are computers, printers, serial interface processor phones, and unmanaged hubs and switches.) The primary reason that prevents bandwidth from reaching the end nodes is the complex local network topology that exists between the optical backbone and the end nodes. This complex network topology consists of several layers of routing and switch equipment which introduce potential congestion points and network latency. By breaking down the complex network topology, a true optical connection can be achieved. Access Optical Networks, Inc., is making this connection a reality with guidance from NASA s nondestructive evaluation experts.

Extension of analog network coding in wireless information exchange

NASA Astrophysics Data System (ADS)

Chen, Cheng; Huang, Jiaqing

2012-01-01

Ever since the concept of analog network coding(ANC) was put forward by S.Katti, much attention has been focused on how to utilize analog network coding to take advantage of wireless interference, which used to be considered generally harmful, to improve throughput performance. Previously, only the case of two nodes that need to exchange information has been fully discussed while the issue of extending analog network coding to more than three nodes remains undeveloped. In this paper, we propose a practical transmission scheme to extend analog network coding to more than two nodes that need to exchange information among themselves. We start with the case of three nodes that need to exchange information and demonstrate that through utilizing our algorithm, the throughput can achieve 33% and 20% increase compared with that of traditional transmission scheduling and digital network coding, respectively. Then, we generalize the algorithm so that it can fit for occasions with any number of nodes. We also discuss some technical issues and throughput analysis as well as the bit error rate.

GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

PubMed

Lin, Chi; Wu, Guowei; Pirozmand, Poria

2015-06-04

The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.

A novel complex networks clustering algorithm based on the core influence of nodes.

PubMed

Tong, Chao; Niu, Jianwei; Dai, Bin; Xie, Zhongyu

2014-01-01

In complex networks, cluster structure, identified by the heterogeneity of nodes, has become a common and important topological property. Network clustering methods are thus significant for the study of complex networks. Currently, many typical clustering algorithms have some weakness like inaccuracy and slow convergence. In this paper, we propose a clustering algorithm by calculating the core influence of nodes. The clustering process is a simulation of the process of cluster formation in sociology. The algorithm detects the nodes with core influence through their betweenness centrality, and builds the cluster's core structure by discriminant functions. Next, the algorithm gets the final cluster structure after clustering the rest of the nodes in the network by optimizing method. Experiments on different datasets show that the clustering accuracy of this algorithm is superior to the classical clustering algorithm (Fast-Newman algorithm). It clusters faster and plays a positive role in revealing the real cluster structure of complex networks precisely.

Embedding global barrier and collective in torus network with each node combining input from receivers according to class map for output to senders

DOEpatents

Chen, Dong; Coteus, Paul W; Eisley, Noel A; Gara, Alan; Heidelberger, Philip; Senger, Robert M; Salapura, Valentina; Steinmacher-Burow, Burkhard; Sugawara, Yutaka; Takken, Todd E

2013-08-27

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.

All-Direction Random Routing for Source-Location Privacy Protecting against Parasitic Sensor Networks.

PubMed

Wang, Na; Zeng, Jiwen

2017-03-17

Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes.

An energy-efficient and compact clustering scheme with temporary support nodes for cognitive radio sensor networks.

PubMed

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-08-11

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members.

RoCoMAR: robots' controllable mobility aided routing and relay architecture for mobile sensor networks.

PubMed

Le, Duc Van; Oh, Hoon; Yoon, Seokhoon

2013-07-05

In a practical deployment, mobile sensor network (MSN) suffers from a low performance due to high node mobility, time-varying wireless channel properties, and obstacles between communicating nodes. In order to tackle the problem of low network performance and provide a desired end-to-end data transfer quality, in this paper we propose a novel ad hoc routing and relaying architecture, namely RoCoMAR (Robots' Controllable Mobility Aided Routing) that uses robotic nodes' controllable mobility. RoCoMAR repeatedly performs link reinforcement process with the objective of maximizing the network throughput, in which the link with the lowest quality on the path is identified and replaced with high quality links by placing a robotic node as a relay at an optimal position. The robotic node resigns as a relay if the objective is achieved or no more gain can be obtained with a new relay. Once placed as a relay, the robotic node performs adaptive link maintenance by adjusting its position according to the movements of regular nodes. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols for MSN in terms of network throughput and end-to-end delay.

An Energy-Efficient and Compact Clustering Scheme with Temporary Support Nodes for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members. PMID:25116905

RoCoMAR: Robots' Controllable Mobility Aided Routing and Relay Architecture for Mobile Sensor Networks

PubMed Central

Van Le, Duc; Oh, Hoon; Yoon, Seokhoon

2013-01-01

In a practical deployment, mobile sensor network (MSN) suffers from a low performance due to high node mobility, time-varying wireless channel properties, and obstacles between communicating nodes. In order to tackle the problem of low network performance and provide a desired end-to-end data transfer quality, in this paper we propose a novel ad hoc routing and relaying architecture, namely RoCoMAR (Robots' Controllable Mobility Aided Routing) that uses robotic nodes' controllable mobility. RoCoMAR repeatedly performs link reinforcement process with the objective of maximizing the network throughput, in which the link with the lowest quality on the path is identified and replaced with high quality links by placing a robotic node as a relay at an optimal position. The robotic node resigns as a relay if the objective is achieved or no more gain can be obtained with a new relay. Once placed as a relay, the robotic node performs adaptive link maintenance by adjusting its position according to the movements of regular nodes. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols for MSN in terms of network throughput and end-to-end delay. PMID:23881134

Community detection for networks with unipartite and bipartite structure

NASA Astrophysics Data System (ADS)

Chang, Chang; Tang, Chao

2014-09-01

Finding community structures in networks is important in network science, technology, and applications. To date, most algorithms that aim to find community structures only focus either on unipartite or bipartite networks. A unipartite network consists of one set of nodes and a bipartite network consists of two nonoverlapping sets of nodes with only links joining the nodes in different sets. However, a third type of network exists, defined here as the mixture network. Just like a bipartite network, a mixture network also consists of two sets of nodes, but some nodes may simultaneously belong to two sets, which breaks the nonoverlapping restriction of a bipartite network. The mixture network can be considered as a general case, with unipartite and bipartite networks viewed as its limiting cases. A mixture network can represent not only all the unipartite and bipartite networks, but also a wide range of real-world networks that cannot be properly represented as either unipartite or bipartite networks in fields such as biology and social science. Based on this observation, we first propose a probabilistic model that can find modules in unipartite, bipartite, and mixture networks in a unified framework based on the link community model for a unipartite undirected network [B Ball et al (2011 Phys. Rev. E 84 036103)]. We test our algorithm on synthetic networks (both overlapping and nonoverlapping communities) and apply it to two real-world networks: a southern women bipartite network and a human transcriptional regulatory mixture network. The results suggest that our model performs well for all three types of networks, is competitive with other algorithms for unipartite or bipartite networks, and is applicable to real-world networks.

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

PubMed Central

Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171

Tackling Information Asymmetry in Networks: A New Entropy-Based Ranking Index

NASA Astrophysics Data System (ADS)

Barucca, Paolo; Caldarelli, Guido; Squartini, Tiziano

2018-06-01

Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel index—InfoRank—intended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.

A game-theoretic response strategy for coordinator attack in wireless sensor networks.

PubMed

Liu, Jianhua; Yue, Guangxue; Shen, Shigen; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security.

Space physics analysis network node directory (The Yellow Pages): Fourth edition

NASA Technical Reports Server (NTRS)

Peters, David J.; Sisson, Patricia L.; Green, James L.; Thomas, Valerie L.

1989-01-01

The Space Physics Analysis Network (SPAN) is a component of the global DECnet Internet, which has over 17,000 host computers. The growth of SPAN from its implementation in 1981 to its present size of well over 2,500 registered SPAN host computers, has created a need for users to acquire timely information about the network through a central source. The SPAN Network Information Center (SPAN-NIC) an online facility managed by the National Space Science Data Center (NSSDC) was developed to meet this need for SPAN-wide information. The remote node descriptive information in this document is not currently contained in the SPAN-NIC database, but will be incorporated in the near future. Access to this information is also available to non-DECnet users over a variety of networks such as Telenet, the NASA Packet Switched System (NPSS), and the TCP/IP Internet. This publication serves as the Yellow Pages for SPAN node information. The document also provides key information concerning other computer networks connected to SPAN, nodes associated with each SPAN routing center, science discipline nodes, contacts for primary SPAN nodes, and SPAN reference information. A section on DECnet Internetworking discusses SPAN connections with other wide-area DECnet networks (many with thousands of nodes each). Another section lists node names and their disciplines, countries, and institutions in the SPAN Network Information Center Online Data Base System. All remote sites connected to US-SPAN and European-SPAN (E-SPAN) are indexed. Also provided is information on the SPAN tail circuits, i.e., those remote nodes connected directly to a SPAN routing center, which is the local point of contact for resolving SPAN-related problems. Reference material is included for those who wish to know more about SPAN. Because of the rapid growth of SPAN, the SPAN Yellow Pages is reissued periodically.

Quantum statistics in complex networks

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

The Barabasi-Albert (BA) model for a complex network shows a characteristic power law connectivity distribution typical of scale free systems. The Ising model on the BA network shows that the ferromagnetic phase transition temperature depends logarithmically on its size. We have introduced a fitness parameter for the BA network which describes the different abilities of nodes to compete for links. This model predicts the formation of a scale free network where each node increases its connectivity in time as a power-law with an exponent depending on its fitness. This model includes the fact that the node connectivity and growth rate do not depend on the node age alone and it reproduces non trivial correlation properties of the Internet. We have proposed a model of bosonic networks by a generalization of the BA model where the properties of quantum statistics can be applied. We have introduced a fitness eta i = e-bei where the temperature T = 1/ b is determined by the noise in the system and the energy ei accounts for qualitative differences of each node for acquiring links. The results of this work show that a power law network with exponent gamma = 2 can give a Bose condensation where a single node grabs a finite fraction of all the links. In order to address the connection with self-organized processes we have introduced a model for a growing Cayley tree that generalizes the dynamics of invasion percolation. At each node we associate a parameter ei (called energy) such that the probability to grow for each node is given by pii ∝ ebei where T = 1/ b is a statistical parameter of the system determined by the noise called the temperature. This model has been solved analytically with a similar mathematical technique as the bosonic scale-free networks and it shows the self organization of the low energy nodes at the interface. In the thermodynamic limit the Fermi distribution describes the probability of the energy distribution at the interface.

Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes

NASA Astrophysics Data System (ADS)

Yang, Hui; Tang, Ming; Gross, Thilo

2015-08-01

One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.

Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes.

PubMed

Yang, Hui; Tang, Ming; Gross, Thilo

2015-08-21

One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.

Some scale-free networks could be robust under selective node attacks

NASA Astrophysics Data System (ADS)

Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

2011-04-01

It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

Robustness and percolation of holes in complex networks

NASA Astrophysics Data System (ADS)

Zhou, Andu; Maletić, Slobodan; Zhao, Yi

2018-07-01

Efficient robustness and fault tolerance of complex network is significantly influenced by its connectivity, commonly modeled by the structure of pairwise relations between network elements, i.e., nodes. Nevertheless, aggregations of nodes build higher-order structures embedded in complex network, which may be more vulnerable when the fraction of nodes is removed. The structure of higher-order aggregations of nodes can be naturally modeled by simplicial complexes, whereas the removal of nodes affects the values of topological invariants, like the number of higher-dimensional holes quantified with Betti numbers. Following the methodology of percolation theory, as the fraction of nodes is removed, new holes appear, which have the role of merger between already present holes. In the present article, relationship between the robustness and homological properties of complex network is studied, through relating the graph-theoretical signatures of robustness and the quantities derived from topological invariants. The simulation results of random failures and intentional attacks on networks suggest that the changes of graph-theoretical signatures of robustness are followed by differences in the distribution of number of holes per cluster under different attack strategies. In the broader sense, the results indicate the importance of topological invariants research for obtaining further insights in understanding dynamics taking place over complex networks.

The use of social network analysis to examine the transmission of Salmonella spp. within a vertically integrated broiler enterprise.

PubMed

Crabb, Helen Kathleen; Allen, Joanne Lee; Devlin, Joanne Maree; Firestone, Simon Matthew; Stevenson, Mark Anthony; Gilkerson, James Rudkin

2018-05-01

To better understand factors influencing infectious agent dispersal within a livestock population information is needed on the nature and frequency of contacts between farm enterprises. This study uses social network analysis to describe the contact network within a vertically integrated broiler poultry enterprise to identify the potential horizontal and vertical transmission pathways for Salmonella spp. Nodes (farms, sheds, production facilities) were identified and the daily movement of commodities (eggs, birds, feed, litter) and people between nodes were extracted from routinely kept farm records. Three time periods were examined in detail, 1- and 8- and 17-weeks of the production cycle and contact networks were described for all movements, and by commodity and production type. All nodes were linked by at least one movement during the study period but network density was low indicating that all potential pathways between nodes did not exist. Salmonella spp. transmission via vertical or horizontal pathways can only occur along directed pathways when those pathways are present. Only two locations (breeder or feed nodes) were identified where the transmission of a single Salmonella spp. clone could theoretically percolate through the network to the broiler or processing nodes. Only the feed transmission pathway directly connected all parts of the network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Authentication and Key Establishment in Dynamic Wireless Sensor Networks

PubMed Central

Qiu, Ying; Zhou, Jianying; Baek, Joonsang; Lopez, Javier

2010-01-01

When a sensor node roams within a very large and distributed wireless sensor network, which consists of numerous sensor nodes, its routing path and neighborhood keep changing. In order to provide a high level of security in this environment, the moving sensor node needs to be authenticated to new neighboring nodes and a key established for secure communication. The paper proposes an efficient and scalable protocol to establish and update the authentication key in a dynamic wireless sensor network environment. The protocol guarantees that two sensor nodes share at least one key with probability 1 (100%) with less memory and energy cost, while not causing considerable communication overhead. PMID:22319321

Node-node correlations and transport properties in scale-free networks

NASA Astrophysics Data System (ADS)

Obregon, Bibiana; Guzman, Lev

2011-03-01

We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-12-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

Multi-channel multi-radio using 802.11 based media access for sink nodes in wireless sensor networks.

PubMed

Campbell, Carlene E-A; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Multi-Channel Multi-Radio Using 802.11 Based Media Access for Sink Nodes in Wireless Sensor Networks

PubMed Central

Campbell, Carlene E.-A.; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives. PMID:22163883

Improving resolution of dynamic communities in human brain networks through targeted node removal

PubMed Central

Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2017-01-01

Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Dahiya, R.; Arora, A. K.; Singh, V. R.

2015-09-01

Energy is an important requirement of wireless sensor networks for better performance. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduce operational capabilities. In this paper, Markov model of a sensor network is developed. The node is considered to enter a sleep mode. This model is used to investigate the system performance in terms of energy consumption, network capacity and data delivery delay.

Zone routing in a torus network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Heidelberger, Philip; Kumar, Sameer

A system for routing data in a network comprising a network logic device at a sending node for determining a path between the sending node and a receiving node, wherein the network logic device sets one or more selection bits and one or more hint bits within the data packet, a control register for storing one or more masks, wherein the network logic device uses the one or more selection bits to select a mask from the control register and the network logic device applies the selected mask to the hint bits to restrict routing of the data packet tomore » one or more routing directions for the data packet within the network and selects one of the restricted routing directions from the one or more routing directions and sends the data packet along a link in the selected routing direction toward the receiving node.« less

Expected number of quantum channels in quantum networks.

PubMed

Chen, Xi; Wang, He-Ming; Ji, Dan-Tong; Mu, Liang-Zhu; Fan, Heng

2015-07-15

Quantum communication between nodes in quantum networks plays an important role in quantum information processing. Here, we proposed the use of the expected number of quantum channels as a measure of the efficiency of quantum communication for quantum networks. This measure quantified the amount of quantum information that can be teleported between nodes in a quantum network, which differs from classical case in that the quantum channels will be consumed if teleportation is performed. We further demonstrated that the expected number of quantum channels represents local correlations depicted by effective circles. Significantly, capacity of quantum communication of quantum networks quantified by ENQC is independent of distance for the communicating nodes, if the effective circles of communication nodes are not overlapped. The expected number of quantum channels can be enhanced through transformations of the lattice configurations of quantum networks via entanglement swapping. Our results can shed lights on the study of quantum communication in quantum networks.

Expected number of quantum channels in quantum networks

PubMed Central

Chen, Xi; Wang, He-Ming; Ji, Dan-Tong; Mu, Liang-Zhu; Fan, Heng

2015-01-01

Quantum communication between nodes in quantum networks plays an important role in quantum information processing. Here, we proposed the use of the expected number of quantum channels as a measure of the efficiency of quantum communication for quantum networks. This measure quantified the amount of quantum information that can be teleported between nodes in a quantum network, which differs from classical case in that the quantum channels will be consumed if teleportation is performed. We further demonstrated that the expected number of quantum channels represents local correlations depicted by effective circles. Significantly, capacity of quantum communication of quantum networks quantified by ENQC is independent of distance for the communicating nodes, if the effective circles of communication nodes are not overlapped. The expected number of quantum channels can be enhanced through transformations of the lattice configurations of quantum networks via entanglement swapping. Our results can shed lights on the study of quantum communication in quantum networks. PMID:26173556

DebtRank-transparency: Controlling systemic risk in financial networks

PubMed Central

Thurner, Stefan; Poledna, Sebastian

2013-01-01

Nodes in a financial network, such as banks, cannot assess the true risks associated with lending to other nodes in the network, unless they have full information on the riskiness of all other nodes. These risks can be estimated by using network metrics (as DebtRank) of the interbank liability network. With a simple agent based model we show that systemic risk in financial networks can be drastically reduced by increasing transparency, i.e. making the DebtRank of individual banks visible to others, and by imposing a rule, that reduces interbank borrowing from systemically risky nodes. This scheme does not reduce the efficiency of the financial network, but fosters a more homogeneous risk-distribution within the system in a self-organized critical way. The reduction of systemic risk is due to a massive reduction of cascading failures in the transparent system. A regulation-policy implementation of the proposed scheme is discussed. PMID:23712454

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

2017-04-20

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Distinguishing Adolescents With ADHD From Their Unaffected Siblings and Healthy Comparison Subjects by Neural Activation Patterns During Response Inhibition.

PubMed

van Rooij, Daan; Hoekstra, Pieter J; Mennes, Maarten; von Rhein, Daniel; Thissen, Andrieke J A M; Heslenfeld, Dirk; Zwiers, Marcel P; Faraone, Stephen V; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Buitelaar, Jan K; Hartman, Catharina A

2015-07-01

Dysfunctional response inhibition is a key executive function impairment in attention deficit hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate affected from unaffected individuals. The authors therefore investigated neural correlates of response inhibition and the familial nature of these neural correlates. Functional MRI measurements of neural activation during the stop-signal task and behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy comparison subjects (N=124). Stop-signal task reaction times were longer and error rates were higher in participants with ADHD, but not in their unaffected siblings, while reaction time variability was higher in both groups than in comparison subjects. Relative to comparison subjects, participants with ADHD and unaffected siblings had neural hypoactivation in frontal-striatal and frontal-parietal networks, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between levels of participants with ADHD and comparison subjects. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity. Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings supports the familial nature of the underlying neural process. Activation deficits in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family.

A new routing enhancement scheme based on node blocking state advertisement in wavelength-routed WDM networks

NASA Astrophysics Data System (ADS)

Hu, Peigang; Jin, Yaohui; Zhang, Chunlei; He, Hao; Hu, WeiSheng

2005-02-01

The increasing switching capacity brings the optical node with considerable complexity. Due to the limitation in cost and technology, an optical node is often designed with partial switching capability and partial resource sharing. It means that the node is of blocking to some extent, for example multi-granularity switching node, which in fact is a structure using pass wavelength to reduce the dimension of OXC, and partial sharing wavelength converter (WC) OXC. It is conceivable that these blocking nodes will have great effects on the problem of routing and wavelength assignment. Some previous works studied the blocking case, partial WC OXC, using complicated wavelength assignment algorithm. But the complexities of these schemes decide them to be not in practice in real networks. In this paper, we propose a new scheme based on the node blocking state advertisement to reduce the retry or rerouting probability and improve the efficiency of routing in the networks with blocking nodes. In the scheme, node blocking state are advertised to the other nodes in networks, which will be used for subsequent route calculation to find a path with lowest blocking probability. The performance of the scheme is evaluated using discrete event model in 14-node NSFNET, all the nodes of which employ a kind of partial sharing WC OXC structure. In the simulation, a simple First-Fit wavelength assignment algorithm is used. The simulation results demonstrate that the new scheme considerably reduces the retry or rerouting probability in routing process.

Synchronization in node of complex networks consist of complex chaotic system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Qiang, E-mail: qiangweibeihua@163.com; Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin; Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024

2014-07-15

A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

NASA Astrophysics Data System (ADS)

Azevedo, Hátylas; Moreira-Filho, Carlos Alberto

2015-11-01

Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks’ robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.

Epidemic dynamics on a risk-based evolving social network

NASA Astrophysics Data System (ADS)

Antwi, Shadrack; Shaw, Leah

2013-03-01

Social network models have been used to study how behavior affects the dynamics of an infection in a population. Motivated by HIV, we consider how a trade-off between benefits and risks of sexual connections determine network structure and disease prevalence. We define a stochastic network model with formation and breaking of links as changes in sexual contacts. Each node has an intrinsic benefit its neighbors derive from connecting to it. Nodes' infection status is not apparent to others, but nodes with more connections (higher degree) are assumed more likely to be infected. The probability to form and break links is determined by a payoff computed from the benefit and degree-dependent risk. The disease is represented by a SI (susceptible-infected) model. We study network and epidemic evolution via Monte Carlo simulation and analytically predict the behavior with a heterogeneous mean field approach. The dependence of network connectivity and infection threshold on parameters is determined, and steady state degree distribution and epidemic levels are obtained. We also study a situation where system-wide infection levels alter perception of risk and cause nodes to adjust their behavior. This is a case of an adaptive network, where node status feeds back to change network geometry.

Impact of degree heterogeneity on the behavior of trapping in Koch networks

NASA Astrophysics Data System (ADS)

Zhang, Zhongzhi; Gao, Shuyang; Xie, Wenlei

2010-12-01

Previous work shows that the mean first-passage time (MFPT) for random walks to a given hub node (node with maximum degree) in uncorrelated random scale-free networks is closely related to the exponent γ of power-law degree distribution P(k )˜k-γ, which describes the extent of heterogeneity of scale-free network structure. However, extensive empirical research indicates that real networked systems also display ubiquitous degree correlations. In this paper, we address the trapping issue on the Koch networks, which is a special random walk with one trap fixed at a hub node. The Koch networks are power-law with the characteristic exponent γ in the range between 2 and 3, they are either assortative or disassortative. We calculate exactly the MFPT that is the average of first-passage time from all other nodes to the trap. The obtained explicit solution shows that in large networks the MFPT varies lineally with node number N, which is obviously independent of γ and is sharp contrast to the scaling behavior of MFPT observed for uncorrelated random scale-free networks, where γ influences qualitatively the MFPT of trapping problem.

A similarity based agglomerative clustering algorithm in networks

NASA Astrophysics Data System (ADS)

Liu, Zhiyuan; Wang, Xiujuan; Ma, Yinghong

2018-04-01

The detection of clusters is benefit for understanding the organizations and functions of networks. Clusters, or communities, are usually groups of nodes densely interconnected but sparsely linked with any other clusters. To identify communities, an efficient and effective community agglomerative algorithm based on node similarity is proposed. The proposed method initially calculates similarities between each pair of nodes, and form pre-partitions according to the principle that each node is in the same community as its most similar neighbor. After that, check each partition whether it satisfies community criterion. For the pre-partitions who do not satisfy, incorporate them with others that having the biggest attraction until there are no changes. To measure the attraction ability of a partition, we propose an attraction index that based on the linked node's importance in networks. Therefore, our proposed method can better exploit the nodes' properties and network's structure. To test the performance of our algorithm, both synthetic and empirical networks ranging in different scales are tested. Simulation results show that the proposed algorithm can obtain superior clustering results compared with six other widely used community detection algorithms.

Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

NASA Astrophysics Data System (ADS)

Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

2018-01-01

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

Distributed Clone Detection in Static Wireless Sensor Networks: Random Walk with Network Division

PubMed Central

Khan, Wazir Zada; Aalsalem, Mohammed Y.; Saad, N. M.

2015-01-01

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads. PMID:25992913

Classification between Failed Nodes and Left Nodes in Mobile Asset Tracking Systems †

PubMed Central

Kim, Kwangsoo; Jin, Jae-Yeon; Jin, Seong-il

2016-01-01

Medical asset tracking systems track a medical device with a mobile node and determine its status as either in or out, because it can leave a monitoring area. Due to a failed node, this system may decide that a mobile asset is outside the area, even though it is within the area. In this paper, an efficient classification method is proposed to separate mobile nodes disconnected from a wireless sensor network between nodes with faults and a node that actually has left the monitoring region. The proposed scheme uses two trends extracted from the neighboring nodes of a disconnected mobile node. First is the trend in a series of the neighbor counts; the second is that of the ratios of the boundary nodes included in the neighbors. Based on such trends, the proposed method separates failed nodes from mobile nodes that are disconnected from a wireless sensor network without failures. The proposed method is evaluated using both real data generated from a medical asset tracking system and also using simulations with the network simulator (ns-2). The experimental results show that the proposed method correctly differentiates between failed nodes and nodes that are no longer in the monitoring region, including the cases that the conventional methods fail to detect. PMID:26901200

Rapid self-organised initiation of ad hoc sensor networks close above the percolation threshold

NASA Astrophysics Data System (ADS)

Korsnes, Reinert

2010-07-01

This work shows potentials for rapid self-organisation of sensor networks where nodes collaborate to relay messages to a common data collecting unit (sink node). The study problem is, in the sense of graph theory, to find a shortest path tree spanning a weighted graph. This is a well-studied problem where for example Dijkstra’s algorithm provides a solution for non-negative edge weights. The present contribution shows by simulation examples that simple modifications of known distributed approaches here can provide significant improvements in performance. Phase transition phenomena, which are known to take place in networks close to percolation thresholds, may explain these observations. An initial method, which here serves as reference, assumes the sink node starts organisation of the network (tree) by transmitting a control message advertising its availability for its neighbours. These neighbours then advertise their current cost estimate for routing a message to the sink. A node which in this way receives a message implying an improved route to the sink, advertises its new finding and remembers which neighbouring node the message came from. This activity proceeds until there are no more improvements to advertise to neighbours. The result is a tree network for cost effective transmission of messages to the sink (root). This distributed approach has potential for simple improvements which are of interest when minimisation of storage and communication of network information are a concern. Fast organisation of the network takes place when the number k of connections for each node ( degree) is close above its critical value for global network percolation and at the same time there is a threshold for the nodes to decide to advertise network route updates.

Approximating frustration scores in complex networks via perturbed Laplacian spectra

NASA Astrophysics Data System (ADS)

Savol, Andrej J.; Chennubhotla, Chakra S.

2015-12-01

Systems of many interacting components, as found in physics, biology, infrastructure, and the social sciences, are often modeled by simple networks of nodes and edges. The real-world systems frequently confront outside intervention or internal damage whose impact must be predicted or minimized, and such perturbations are then mimicked in the models by altering nodes or edges. This leads to the broad issue of how to best quantify changes in a model network after some type of perturbation. In the case of node removal there are many centrality metrics which associate a scalar quantity with the removed node, but it can be difficult to associate the quantities with some intuitive aspect of physical behavior in the network. This presents a serious hurdle to the application of network theory: real-world utility networks are rarely altered according to theoretic principles unless the kinetic impact on the network's users are fully appreciated beforehand. In pursuit of a kinetically interpretable centrality score, we discuss the f-score, or frustration score. Each f-score quantifies whether a selected node accelerates or inhibits global mean first passage times to a second, independently selected target node. We show that this is a natural way of revealing the dynamical importance of a node in some networks. After discussing merits of the f-score metric, we combine spectral and Laplacian matrix theory in order to quickly approximate the exact f-score values, which can otherwise be expensive to compute. Following tests on both synthetic and real medium-sized networks, we report f-score runtime improvements over exact brute force approaches in the range of 0 to 400 % with low error (<3 % ).

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

PubMed

Gibbs, David L; Shmulevich, Ilya

2017-06-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

A decentralized mechanism for improving the functional robustness of distribution networks.

PubMed

Shi, Benyun; Liu, Jiming

2012-10-01

Most real-world distribution systems can be modeled as distribution networks, where a commodity can flow from source nodes to sink nodes through junction nodes. One of the fundamental characteristics of distribution networks is the functional robustness, which reflects the ability of maintaining its function in the face of internal or external disruptions. In view of the fact that most distribution networks do not have any centralized control mechanisms, we consider the problem of how to improve the functional robustness in a decentralized way. To achieve this goal, we study two important problems: 1) how to formally measure the functional robustness, and 2) how to improve the functional robustness of a network based on the local interaction of its nodes. First, we derive a utility function in terms of network entropy to characterize the functional robustness of a distribution network. Second, we propose a decentralized network pricing mechanism, where each node need only communicate with its distribution neighbors by sending a "price" signal to its upstream neighbors and receiving "price" signals from its downstream neighbors. By doing so, each node can determine its outflows by maximizing its own payoff function. Our mathematical analysis shows that the decentralized pricing mechanism can produce results equivalent to those of an ideal centralized maximization with complete information. Finally, to demonstrate the properties of our mechanism, we carry out a case study on the U.S. natural gas distribution network. The results validate the convergence and effectiveness of our mechanism when comparing it with an existing algorithm.

The effects of node exclusion on the centrality measures in graph models of interacting economic agents

NASA Astrophysics Data System (ADS)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-07-01

This work concerns the study of the effects felt by a network as a whole when a specific node is perturbed. Many real world systems can be described by network models in which the interactions of the various agents can be represented as an edge of a graph. With a graph model in hand, it is possible to evaluate the effect of deleting some of its edges on the architecture and values of nodes of the network. Eventually a node may end up isolated from the rest of the network and an interesting problem is to have a quantitative measure of the impact of such an event. For instance, in the field of finance, the network models are very popular and the proposed methodology allows to carry out "what if" tests in terms of weakening the links between the economic agents, represented as nodes. The two main concepts employed in the proposed methodology are (i) the vibrational IC-Information Centrality, which can provide a measure of the relative importance of a particular node in a network and (ii) autocatalytic networks that can indicate the evolutionary trends of the network. Although these concepts were originally proposed in the context of other fields of knowledge, they were also found to be useful in analyzing financial networks. In order to illustrate the applicability of the proposed methodology, a case of study using the actual data comprising stock market indices of 12 countries is presented.

Analytical network process based optimum cluster head selection in wireless sensor network.

PubMed

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Analytical network process based optimum cluster head selection in wireless sensor network

PubMed Central

Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. PMID:28719616

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

PubMed

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W(k)(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation).

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

PubMed

Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

2015-11-24

Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

Neural node network and model, and method of teaching same

DOEpatents

Parlos, A.G.; Atiya, A.F.; Fernandez, B.; Tsai, W.K.; Chong, K.T.

1995-12-26

The present invention is a fully connected feed forward network that includes at least one hidden layer. The hidden layer includes nodes in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device occurring in the feedback path (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit from all the other nodes within the same layer. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing. 21 figs.

Reconfigurable routing protocol for free space optical sensor networks.

PubMed

Xie, Rong; Yang, Won-Hyuk; Kim, Young-Chon

2012-01-01

Recently, free space optical sensor networks (FSOSNs), which are based on free space optics (FSO) instead of radio frequency (RF), have gained increasing visibility over traditional wireless sensor networks (WSNs) due to their advantages such as larger capacity, higher security, and lower cost. However, the performance of FSOSNs is restricted to the requirement of a direct line-of-sight (LOS) path between a sender and a receiver pair. Once a node dies of energy depletion, the network would probably suffer from a dramatic decrease of connectivity, resulting in a huge loss of data packets. Thus, this paper proposes a reconfigurable routing protocol (RRP) to overcome this problem by dynamically reconfiguring the network virtual topology. The RRP works in three phases: (1) virtual topology construction, (2) routing establishment, and (3) reconfigurable routing. When data transmission begins, the data packets are first routed through the shortest hop paths. Then a reconfiguration is initiated by the node whose residual energy falls below a threshold. Nodes affected by this dying node are classified into two types, namely maintenance nodes and adjustment nodes, and they are reconfigured according to the types. An energy model is designed to evaluate the performance of RRP through OPNET simulation. Our simulation results indicate that the RRP achieves better performance compared with the simple-link protocol and a direct reconfiguration scheme in terms of connectivity, network lifetime, packet delivery ratio and the number of living nodes.

Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network).

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods.

Neural node network and model, and method of teaching same

DOEpatents

Parlos, Alexander G.; Atiya, Amir F.; Fernandez, Benito; Tsai, Wei K.; Chong, Kil T.

1995-01-01

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Peregrine System Configuration | High-Performance Computing | NREL

Science.gov Websites

nodes and storage are connected by a high speed InfiniBand network. Compute nodes are diskless with an directories are mounted on all nodes, along with a file system dedicated to shared projects. A brief processors with 64 GB of memory. All nodes are connected to the high speed Infiniband network and and a

Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2012-01-10

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Efficient implementation of a multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2008-01-01

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Network resiliency through memory health monitoring and proactive management

DOEpatents

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory.

PubMed

Feng, Renjian; Xu, Xiaofeng; Zhou, Xiang; Wan, Jiangwen

2011-01-01

For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that 'hard to acquire and easy to lose'. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation.

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

Fairness of QoS supporting in optical burst switching

NASA Astrophysics Data System (ADS)

Xuan, Xuelei; Liu, Hua; Chen, Chunfeng; Zhang, Zhizhong

2004-04-01

In this paper we investigate the fairness problem of offset-time-based quality of service (QoS) scheme proposed by Qiao and Dixit in optical burst switching (OBS) networks. In the proposed schemes, QoS relies on the fact that the requests for reservation further into the future, but for practical, benchmark offset-time of data bursts at the intermediate nodes is not equal to each other. Here, a new offset-time-based QoS scheme is introduced, where data bursts are classified according to their offset-time and isolated in the wavelength domain or time domain to achieve the parallel reservation. Through simulation, it is found that this scheme achieves fairness among data bursts with different priority.

Antisynchronization of Two Complex Dynamical Networks

NASA Astrophysics Data System (ADS)

Banerjee, Ranjib; Grosu, Ioan; Dana, Syamal K.

A nonlinear type open-plus-closed-loop (OPCL) coupling is investi-gated for antisynchronization of two complex networks under unidirectional and bidirectional interactions where each node of the networks is considered as a continuous dynamical system. We present analytical results for antisynchroni-zation in identical networks. A numerical example is given for unidirectional coupling with each node represented by a spiking-bursting type Hindmarsh-Rose neuron model. Antisynchronization for mutual interaction is allowed only to inversion symmetric dynamical systems as chosen nodes.

Scaling of Average Weighted Receiving Time on Double-Weighted Koch Networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Ye, Dandan; Hou, Jie; Li, Xingyi

2015-03-01

In this paper, we introduce a model of the double-weighted Koch networks based on actual road networks depending on the two weight factors w,r ∈ (0, 1]. The double weights represent the capacity-flowing weight and the cost-traveling weight, respectively. Denote by wFij the capacity-flowing weight connecting the nodes i and j, and denote by wCij the cost-traveling weight connecting the nodes i and j. Let wFij be related to the weight factor w, and let wCij be related to the weight factor r. This paper assumes that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the capacity-flowing weight of edge linking them. The weighted time for two adjacency nodes is the cost-traveling weight connecting the two nodes. We define the average weighted receiving time (AWRT) on the double-weighted Koch networks. The obtained result displays that in the large network, the AWRT grows as power-law function of the network order with the exponent, represented by θ(w,r) = ½ log2(1 + 3wr). We show that the AWRT exhibits a sublinear or linear dependence on network order. Thus, the double-weighted Koch networks are more efficient than classic Koch networks in receiving information.

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

NASA Astrophysics Data System (ADS)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

All-Direction Random Routing for Source-Location Privacy Protecting against Parasitic Sensor Networks

PubMed Central

Wang, Na; Zeng, Jiwen

2017-01-01

Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes. PMID:28304367

Research in Wireless Networks and Communications

DTIC Science & Technology

2008-05-01

TESTBED SETUP AND INITIAL MULTI-HOP EXPERIENCE As a proof of concept, we assembled a testbed platform of nodes based on 400MHz AMD Geode single-board...experi- ments on a testbed network consisting of 400MHz AMD Geode single-board computers made by Thecus Inc. We equipped each of these nodes with two...ground nodes were placed on a line, with about 3 feet of separation between adjacent nodes. The nodes were powered by 400MHz AMD Geode single-board

Energy efficient mechanisms for high-performance Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Alsaify, Baha'adnan

2009-12-01

Due to recent advances in microelectronics, the development of low cost, small, and energy efficient devices became possible. Those advances led to the birth of the Wireless Sensor Networks (WSNs). WSNs consist of a large set of sensor nodes equipped with communication capabilities, scattered in the area to monitor. Researchers focus on several aspects of WSNs. Such aspects include the quality of service the WSNs provide (data delivery delay, accuracy of data, etc...), the scalability of the network to contain thousands of sensor nodes (the terms node and sensor node are being used interchangeably), the robustness of the network (allowing the network to work even if a certain percentage of nodes fails), and making the energy consumption in the network as low as possible to prolong the network's lifetime. In this thesis, we present an approach that can be applied to the sensing devices that are scattered in an area for Sensor Networks. This work will use the well-known approach of using a awaking scheduling to extend the network's lifespan. We designed a scheduling algorithm that will reduce the delay's upper bound the reported data will experience, while at the same time keeps the advantages that are offered by the use of the awaking scheduling -- the energy consumption reduction which will lead to the increase in the network's lifetime. The wakeup scheduling is based on the location of the node relative to its neighbors and its distance from the Base Station (the terms Base Station and sink are being used interchangeably). We apply the proposed method to a set of simulated nodes using the "ONE Simulator". We test the performance of this approach with three other approaches -- Direct Routing technique, the well known LEACH algorithm, and a multi-parent scheduling algorithm. We demonstrate a good improvement on the network's quality of service and a reduction of the consumed energy.

A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks.

PubMed

Mi, Shichao; Han, Hui; Chen, Cailian; Yan, Jian; Guan, Xinping

2016-02-19

Heterogeneous wireless sensor networks (HWSNs) can achieve more tasks and prolong the network lifetime. However, they are vulnerable to attacks from the environment or malicious nodes. This paper is concerned with the issues of a consensus secure scheme in HWSNs consisting of two types of sensor nodes. Sensor nodes (SNs) have more computation power, while relay nodes (RNs) with low power can only transmit information for sensor nodes. To address the security issues of distributed estimation in HWSNs, we apply the heterogeneity of responsibilities between the two types of sensors and then propose a parameter adjusted-based consensus scheme (PACS) to mitigate the effect of the malicious node. Finally, the convergence property is proven to be guaranteed, and the simulation results validate the effectiveness and efficiency of PACS.

Fragmenting networks by targeting collective influencers at a mesoscopic level.

PubMed

Kobayashi, Teruyoshi; Masuda, Naoki

2016-11-25

A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.

Fragmenting networks by targeting collective influencers at a mesoscopic level

NASA Astrophysics Data System (ADS)

Kobayashi, Teruyoshi; Masuda, Naoki

2016-11-01

A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.

Fragmenting networks by targeting collective influencers at a mesoscopic level

PubMed Central

Kobayashi, Teruyoshi; Masuda, Naoki

2016-01-01

A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure. PMID:27886251

Auto-Configuration Protocols in Mobile Ad Hoc Networks

PubMed Central

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

The TCP/IP protocol allows the different nodes in a network to communicate by associating a different IP address to each node. In wired or wireless networks with infrastructure, we have a server or node acting as such which correctly assigns IP addresses, but in mobile ad hoc networks there is no such centralized entity capable of carrying out this function. Therefore, a protocol is needed to perform the network configuration automatically and in a dynamic way, which will use all nodes in the network (or part thereof) as if they were servers that manage IP addresses. This article reviews the major proposed auto-configuration protocols for mobile ad hoc networks, with particular emphasis on one of the most recent: D2HCP. This work also includes a comparison of auto-configuration protocols for mobile ad hoc networks by specifying the most relevant metrics, such as a guarantee of uniqueness, overhead, latency, dependency on the routing protocol and uniformity. PMID:22163814

A cooperative game framework for detecting overlapping communities in social networks

NASA Astrophysics Data System (ADS)

Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan

2018-02-01

Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.

Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks

PubMed Central

Piraveenan, Mahendra; Prokopenko, Mikhail; Hossain, Liaquat

2013-01-01

A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns) because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks. PMID:23349699

Trade-offs between driving nodes and time-to-control in complex networks

PubMed Central

Pequito, Sérgio; Preciado, Victor M.; Barabási, Albert-László; Pappas, George J.

2017-01-01

Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, which we used to find that in many complex networks only a small fraction of driving (or driven) nodes is required to steer the network to a desired state within a relatively small time window. Furthermore, our empirical studies reveal that, even though synthetic network models are designed to present structural properties similar to those observed in real networks, their actuation spectra can be dramatically different. Thus, it supports the need to develop new synthetic network models able to replicate controllability properties of real-world networks. PMID:28054597

Trade-offs between driving nodes and time-to-control in complex networks

NASA Astrophysics Data System (ADS)

Pequito, Sérgio; Preciado, Victor M.; Barabási, Albert-László; Pappas, George J.

2017-01-01

Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, which we used to find that in many complex networks only a small fraction of driving (or driven) nodes is required to steer the network to a desired state within a relatively small time window. Furthermore, our empirical studies reveal that, even though synthetic network models are designed to present structural properties similar to those observed in real networks, their actuation spectra can be dramatically different. Thus, it supports the need to develop new synthetic network models able to replicate controllability properties of real-world networks.

Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks

NASA Astrophysics Data System (ADS)

Guitton, Alexandre; Andres, Frédéric; Cardoso, Jarbas Lopes; Kawtrakul, Asanee; Barbin, Silvio E.

2015-10-01

The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection.

An improved network model for railway traffic

NASA Astrophysics Data System (ADS)

Li, Keping; Ma, Xin; Shao, Fubo

In railway traffic, safety analysis is a key issue for controlling train operation. Here, the identification and order of key factors are very important. In this paper, a new network model is constructed for analyzing the railway safety, in which nodes are regarded as causation factors and links represent possible relationships among those factors. Our aim is to give all these nodes an importance order, and to find the in-depth relationship among these nodes including how failures spread among them. Based on the constructed network model, we propose a control method to ensure the safe state by setting each node a threshold. As the results, by protecting the Hub node of the constructed network, the spreading of railway accident can be controlled well. The efficiency of such a method is further tested with the help of numerical example.

Which Brain Regions are Important for Seizure Dynamics in Epileptic Networks? Influence of Link Identification and EEG Recording Montage on Node Centralities.

PubMed

Geier, Christian; Lehnertz, Klaus

2017-02-01

Nodes in large-scale epileptic networks that are crucial for seizure facilitation and termination can be regarded as potential targets for individualized focal therapies. Graph-theoretical approaches based on centrality concepts can help to identify such important nodes, however, they may be influenced by the way networks are derived from empirical data. Here we investigate evolving functional epileptic brain networks during 82 focal seizures with different anatomical onset locations that we derive from multichannel intracranial electroencephalographic recordings from 51 patients. We demonstrate how the various methodological steps (from the recording montage via node and link inference to the assessment of node centralities) affect importance estimation and discuss their impact on the interpretability of findings in the context of pathophysiological aspects of seizure dynamics.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

Using Trust to Establish a Secure Routing Model in Cognitive Radio Network.

PubMed

Zhang, Guanghua; Chen, Zhenguo; Tian, Liqin; Zhang, Dongwen

2015-01-01

Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes' forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes' trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

ERIC Educational Resources Information Center

Gou, Liang

2012-01-01

Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

Loss surface of XOR artificial neural networks

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Zhang, Gang

2013-12-15

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme ismore » confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.« less

Research on TCP/IP network communication based on Node.js

NASA Astrophysics Data System (ADS)

Huang, Jing; Cai, Lixiong

2018-04-01

In the face of big data, long connection and high synchronization, TCP/IP network communication will cause performance bottlenecks due to its blocking multi-threading service model. This paper presents a method of TCP/IP network communication protocol based on Node.js. On the basis of analyzing the characteristics of Node.js architecture and asynchronous non-blocking I/O model, the principle of its efficiency is discussed, and then compare and analyze the network communication model of TCP/IP protocol to expound the reasons why TCP/IP protocol stack is widely used in network communication. Finally, according to the large data and high concurrency in the large-scale grape growing environment monitoring process, a TCP server design based on Node.js is completed. The results show that the example runs stably and efficiently.

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs

PubMed Central

Palafox, Luis E.; Aguilar, Leocundo; Sanchez, Mauricio A.; Martinez, Luis G.

2016-01-01

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder. PMID:27219671

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Distributed computation of graphics primitives on a transputer network

NASA Technical Reports Server (NTRS)

Ellis, Graham K.

1988-01-01

A method is developed for distributing the computation of graphics primitives on a parallel processing network. Off-the-shelf transputer boards are used to perform the graphics transformations and scan-conversion tasks that would normally be assigned to a single transputer based display processor. Each node in the network performs a single graphics primitive computation. Frequently requested tasks can be duplicated on several nodes. The results indicate that the current distribution of commands on the graphics network shows a performance degradation when compared to the graphics display board alone. A change to more computation per node for every communication (perform more complex tasks on each node) may cause the desired increase in throughput.

A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

PubMed

Khan, Jawaad Ullah; Cho, Ho-Shin

2015-08-06

In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.

Speedy routing recovery protocol for large failure tolerance in wireless sensor networks.

PubMed

Lee, Joa-Hyoung; Jung, In-Bum

2010-01-01

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols.

Design and Implementation of a MAC Protocol for Timely and Reliable Delivery of Command and Data in Dynamic Wireless Sensor Networks

PubMed Central

Oh, Hoon; Van Vinh, Phan

2013-01-01

This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results. PMID:24084116

Design and implementation of a MAC protocol for timely and reliable delivery of command and data in dynamic wireless sensor networks.

PubMed

Oh, Hoon; Van Vinh, Phan

2013-09-30

This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results.

Optical Circuit Switched Protocol

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

2000-01-01

The present invention is a system and method embodied in an optical circuit switched protocol for the transmission of data through a network. The optical circuit switched protocol is an all-optical circuit switched network and includes novel optical switching nodes for transmitting optical data packets within a network. Each optical switching node comprises a detector for receiving the header, header detection logic for translating the header into routing information and eliminating the header, and a controller for receiving the routing information and configuring an all optical path within the node. The all optical path located within the node is solely an optical path without having electronic storage of the data and without having optical delay of the data. Since electronic storage of the header is not necessary and the initial header is eliminated by the first detector of the first switching node. multiple identical headers are sent throughout the network so that subsequent switching nodes can receive and read the header for setting up an optical data path.

Service discovery with routing protocols for MANETs

NASA Astrophysics Data System (ADS)

Gu, Xuemai; Shi, Shuo

2005-11-01

Service discovery is becoming an important topic as its use throughout the Internet becomes more widespread. In Mobile Ad hoc Networks (MANETs), the routing protocol is very important because it is special network. To find a path for data, and destination nodes, nodes send packets to each node, creating substantial overhead traffic and consuming much time. Even though a variety of routing protocols have been developed for use in MANETs, they are insufficient for reducing overhead traffic and time. In this paper, we propose SDRP: a new service discovery protocol combined with routing policies in MANETs. The protocol is performed upon a distributed network. We describe a service by a unique ID number and use a group-cast routing policy in advertisement and request. The group-cast routing policy decreases the traffic in networks, and it is efficient to find destination node. In addition, the nodes included in the reply path also cache the advertisement information, and it means when each node finds a node next time, they can know where it is as soon as possible, so they minimize the time. Finally, we compare SDRP with both Flood and MAODV in terms of overload, and average delay. Simulation results show SDRP can spend less response time and accommodate even high mobility network environments.

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

PubMed

Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S

2017-03-08

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance. Copyright © 2017 Chan et al.

Complex network structure of musical compositions: Algorithmic generation of appealing music

NASA Astrophysics Data System (ADS)

Liu, Xiao Fan; Tse, Chi K.; Small, Michael

2010-01-01

In this paper we construct networks for music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurring connections. We analyze classical music from Bach, Mozart, Chopin, as well as other types of music such as Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. We conjecture that preserving the universal network properties is a necessary step in artificial composition of music. Power-law exponents of node degree, node strength and/or edge weight distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be composed artificially using a controlled random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. By generating a large number of compositions, we find that this algorithm generates music which has the necessary qualities to be subjectively judged as appealing.

A distributed geo-routing algorithm for wireless sensor networks.

PubMed

Joshi, Gyanendra Prasad; Kim, Sung Won

2009-01-01

Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.

Link Prediction in Evolving Networks Based on Popularity of Nodes.

PubMed

Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

2017-08-02

Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

The model of microblog message diffusion based on complex social network

NASA Astrophysics Data System (ADS)

Zhang, Wei; Bai, Shu-Ying; Jin, Rui

2014-05-01

Microblog is a micromessage communication network in which users are the nodes and the followship between users are the edges. Sina Weibo is a typical case of these microblog service websites. As the enormous scale of nodes and complex links in the network, we choose a sample network crawled in Sina Weibo as the base of empirical analysis. The study starts with the analysis of its topological features, and brings in epidemiological SEIR model to explore the mode of message spreading throughout the microblog network. It is found that the network is obvious small-world and scale-free, which made it succeed in transferring messages and failed in resisting negative influence. In addition, the paper focuses on the rich nodes as they constitute a typical feature of Sina Weibo. It is also found that whether the message starts with a rich node will not account for its final coverage. Actually, the rich nodes always play the role of pivotal intermediaries who speed up the spreading and make the message known by much more people.

Threshold cascades with response heterogeneity in multiplex networks

NASA Astrophysics Data System (ADS)

Lee, Kyu-Min; Brummitt, Charles D.; Goh, K.-I.

2014-12-01

Threshold cascade models have been used to describe the spread of behavior in social networks and cascades of default in financial networks. In some cases, these networks may have multiple kinds of interactions, such as distinct types of social ties or distinct types of financial liabilities; furthermore, nodes may respond in different ways to influence from their neighbors of multiple types. To start to capture such settings in a stylized way, we generalize a threshold cascade model to a multiplex network in which nodes follow one of two response rules: some nodes activate when, in at least one layer, a large enough fraction of neighbors is active, while the other nodes activate when, in all layers, a large enough fraction of neighbors is active. Varying the fractions of nodes following either rule facilitates or inhibits cascades. Near the inhibition regime, global cascades appear discontinuously as the network density increases; however, the cascade grows more slowly over time. This behavior suggests a way in which various collective phenomena in the real world could appear abruptly yet slowly.

Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Distinguishing manipulated stocks via trading network analysis

NASA Astrophysics Data System (ADS)

Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang

2011-10-01

Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.

Ad Hoc Access Gateway Selection Algorithm

NASA Astrophysics Data System (ADS)

Jie, Liu

With the continuous development of mobile communication technology, Ad Hoc access network has become a hot research, Ad Hoc access network nodes can be used to expand capacity of multi-hop communication range of mobile communication system, even business adjacent to the community, improve edge data rates. For mobile nodes in Ad Hoc network to internet, internet communications in the peer nodes must be achieved through the gateway. Therefore, the key Ad Hoc Access Networks will focus on the discovery gateway, as well as gateway selection in the case of multi-gateway and handover problems between different gateways. This paper considers the mobile node and the gateway, based on the average number of hops from an average access time and the stability of routes, improved gateway selection algorithm were proposed. An improved gateway selection algorithm, which mainly considers the algorithm can improve the access time of Ad Hoc nodes and the continuity of communication between the gateways, were proposed. This can improve the quality of communication across the network.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Heterogeneous network promotes species coexistence: metapopulation model for rock-paper-scissors game.

PubMed

Nagatani, Takashi; Ichinose, Genki; Tainaka, Kei-Ichi

2018-05-04

Understanding mechanisms of biodiversity has been a central question in ecology. The coexistence of three species in rock-paper-scissors (RPS) systems are discussed by many authors; however, the relation between coexistence and network structure is rarely discussed. Here we present a metapopulation model for RPS game. The total population is assumed to consist of three subpopulations (nodes). Each individual migrates by random walk; the destination of migration is randomly determined. From reaction-migration equations, we obtain the population dynamics. It is found that the dynamic highly depends on network structures. When a network is homogeneous, the dynamics are neutrally stable: each node has a periodic solution, and the oscillations synchronize in all nodes. However, when a network is heterogeneous, the dynamics approach stable focus and all nodes reach equilibriums with different densities. Hence, the heterogeneity of the network promotes biodiversity.

Embedding global and collective in a torus network with message class map based tree path selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Coteus, Paul W.; Eisley, Noel A.

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less

Network structure, topology, and dynamics in generalized models of synchronization

NASA Astrophysics Data System (ADS)

Lerman, Kristina; Ghosh, Rumi

2012-08-01

Network structure is a product of both its topology and interactions between its nodes. We explore this claim using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state, nodes synchronize in stages, revealing the network's underlying community structure. Traditional models of synchronization assume that interactions between nodes are mediated by a conservative process similar to diffusion. However, social and biological processes are often nonconservative. We propose a model of synchronization in a network of oscillators coupled via nonconservative processes. We study the dynamics of synchronization of a synthetic and real-world networks and show that the traditional and nonconservative models of synchronization reveal different structures within the same network.

Metropolitan all-pass and inter-city quantum communication network.

PubMed

Chen, Teng-Yun; Wang, Jian; Liang, Hao; Liu, Wei-Yue; Liu, Yang; Jiang, Xiao; Wang, Yuan; Wan, Xu; Cai, Wei-Qi; Ju, Lei; Chen, Luo-Kan; Wang, Liu-Jun; Gao, Yuan; Chen, Kai; Peng, Cheng-Zhi; Chen, Zeng-Bing; Pan, Jian-Wei

2010-12-20

We have demonstrated a metropolitan all-pass quantum communication network in field fiber for four nodes. Any two nodes of them can be connected in the network to perform quantum key distribution (QKD). An optical switching module is presented that enables arbitrary 2-connectivity among output ports. Integrated QKD terminals are worked out, which can operate either as a transmitter, a receiver, or even both at the same time. Furthermore, an additional link in another city of 60 km fiber (up to 130 km) is seamless integrated into this network based on a trusted relay architecture. On all the links, we have implemented protocol of decoy state scheme. All of necessary electrical hardware, synchronization, feedback control, network software, execution of QKD protocols are made by tailored designing, which allow a completely automatical and stable running. Our system has been put into operation in Hefei in August 2009, and publicly demonstrated during an evaluation conference on quantum network organized by the Chinese Academy of Sciences on August 29, 2009. Real-time voice telephone with one-time pad encoding between any two of the five nodes (four all-pass nodes plus one additional node through relay) is successfully established in the network within 60 km.