Science.gov

Sample records for distribution networks sistema

  1. Prototyping distributed simulation networks

    NASA Technical Reports Server (NTRS)

    Doubleday, Dennis L.

    1990-01-01

    Durra is a declarative language designed to support application-level programming. The use of Durra is illustrated to describe a simple distributed application: a simulation of a collection of networked vehicle simulators. It is shown how the language is used to describe the application, its components and structure, and how the runtime executive provides for the execution of the application.

  2. Distributed network scheduling

    NASA Technical Reports Server (NTRS)

    Clement, Bradley J.; Schaffer, Steven R.

    2005-01-01

    We investigate missions where communications resources are limited, requiring autonomous planning and execution. Unlike typical networks, spacecraft networks are also suited to automated planning and scheduling because many communications can be planned in advance.

  3. Distributed Observer Network

    NASA Technical Reports Server (NTRS)

    2008-01-01

    NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

  4. Wealth distribution on complex networks

    NASA Astrophysics Data System (ADS)

    Ichinomiya, Takashi

    2012-12-01

    We study the wealth distribution of the Bouchaud-Mézard model on complex networks. It is known from numerical simulations that this distribution depends on the topology of the network; however, no one has succeeded in explaining it. Using “adiabatic” and “independent” assumptions along with the central-limit theorem, we derive equations that determine the probability distribution function. The results are compared to those of simulations for various networks. We find good agreement between our theory and the simulations, except for the case of Watts-Strogatz networks with a low rewiring rate due to the breakdown of independent assumption.

  5. Distributed Observer Network

    NASA Technical Reports Server (NTRS)

    Conroy, Michael; Mazzone, Rebecca; Little, William; Elfrey, Priscilla; Mann, David; Mabie, Kevin; Cuddy, Thomas; Loundermon, Mario; Spiker, Stephen; McArthur, Frank; Srey, Tate; Bonilla, Dennis

    2010-01-01

    The Distributed Observer network (DON) is a NASA-collaborative environment that leverages game technology to bring three-dimensional simulations to conventional desktop and laptop computers in order to allow teams of engineers working on design and operations, either individually or in groups, to view and collaborate on 3D representations of data generated by authoritative tools such as Delmia Envision, Pro/Engineer, or Maya. The DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3D visual environment. DON has been designed to enhance accessibility and user ability to observe and analyze visual simulations in real time. A variety of NASA mission segment simulations [Synergistic Engineering Environment (SEE) data, NASA Enterprise Visualization Analysis (NEVA) ground processing simulations, the DSS simulation for lunar operations, and the Johnson Space Center (JSC) TRICK tool for guidance, navigation, and control analysis] were experimented with. Desired functionalities, [i.e. Tivo-like functions, the capability to communicate textually or via Voice-over-Internet Protocol (VoIP) among team members, and the ability to write and save notes to be accessed later] were targeted. The resulting DON application was slated for early 2008 release to support simulation use for the Constellation Program and its teams. Those using the DON connect through a client that runs on their PC or Mac. This enables them to observe and analyze the simulation data as their schedule allows, and to review it as frequently as desired. DON team members can move freely within the virtual world. Preset camera points can be established, enabling team members to jump to specific views. This improves opportunities for shared analysis of options, design reviews, tests, operations, training, and evaluations, and improves prospects for verification of requirements, issues, and approaches among dispersed teams.

  6. Distributed semantic networks and CLIPS

    NASA Technical Reports Server (NTRS)

    Snyder, James; Rodriguez, Tony

    1991-01-01

    Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

  7. Distributed downhole drilling network

    DOEpatents

    Hall, David R.; Hall, Jr., H. Tracy; Fox, Joe; Pixton, David S.

    2006-11-21

    A high-speed downhole network providing real-time data from downhole components of a drilling strings includes a bottom-hole node interfacing to a bottom-hole assembly located proximate the bottom end of a drill string. A top-hole node is connected proximate the top end of the drill string. One or several intermediate nodes are located along the drill string between the bottom-hole node and the top-hole node. The intermediate nodes are configured to receive and transmit data packets transmitted between the bottom-hole node and the top-hole node. A communications link, integrated into the drill string, is used to operably connect the bottom-hole node, the intermediate nodes, and the top-hole node. In selected embodiments, a personal or other computer may be connected to the top-hole node, to analyze data received from the intermediate and bottom-hole nodes.

  8. Distributed simulation of network protocols

    NASA Technical Reports Server (NTRS)

    Paterra, Frank; Overstreet, C. Michael; Maly, Kurt J.

    1990-01-01

    Simulations of high speed network protocols are very CPU intensive operations requiring very long run times. Very high speed network protocols (Gigabit/sec rates) require longer simulation runs in order to reach a steady state, while at the same time requiring additional CPU processing for each unit of time because of the data rates for the traffic being simulated. As protocol development proceeds and simulations provide insights into any problems associated with the protocol, the simulation model often must be changed to generate additional or finer statistical performance information. Iterating on this process is very time consuming due to the required run times for the simulation models. The results of the efforts to distribute a high speed ring network protocol, Carrier Sensed Multiple Access/Ring Network (CSMA/RN), are presented.

  9. Ising model for distribution networks

    NASA Astrophysics Data System (ADS)

    Hooyberghs, H.; Van Lombeek, S.; Giuraniuc, C.; Van Schaeybroeck, B.; Indekeu, J. O.

    2012-01-01

    An elementary Ising spin model is proposed for demonstrating cascading failures (breakdowns, blackouts, collapses, avalanches, etc.) that can occur in realistic networks for distribution and delivery by suppliers to consumers. A ferromagnetic Hamiltonian with quenched random fields results from policies that maximize the gap between demand and delivery. Such policies can arise in a competitive market where firms artificially create new demand, or in a solidarity environment where too high a demand cannot reasonably be met. Network failure in the context of a policy of solidarity is possible when an initially active state becomes metastable and decays to a stable inactive state. We explore the characteristics of the demand and delivery, as well as the topological properties, which make the distribution network susceptible of failure. An effective temperature is defined, which governs the strength of the activity fluctuations which can induce a collapse. Numerical results, obtained by Monte Carlo simulations of the model on (mainly) scale-free networks, are supplemented with analytic mean-field approximations to the geometrical random field fluctuations and the thermal spin fluctuations. The role of hubs versus poorly connected nodes in initiating the breakdown of network activity is illustrated and related to model parameters.

  10. Voltage regulation in distribution networks with distributed generation

    NASA Astrophysics Data System (ADS)

    Blažič, B.; Uljanić, B.; Papič, I.

    2012-11-01

    The paper deals with the topic of voltage regulation in distribution networks with relatively high distributed energy resources (DER) penetration. The problem of voltage rise is described and different options for voltage regulation are given. The influence of DER on voltage profile and the effectiveness of the investigated solutions are evaluated by means of simulation in DIgSILENT. The simulated network is an actual distribution network in Slovenia with a relatively high penetration of distributed generation. Recommendations for voltage control in networks with DER penetration are given at the end.

  11. Optimal distributions for multiplex logistic networks.

    PubMed

    Solá Conde, Luis E; Used, Javier; Romance, Miguel

    2016-06-01

    This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates. PMID:27368801

  12. Optimal distributions for multiplex logistic networks

    NASA Astrophysics Data System (ADS)

    Solá Conde, Luis E.; Used, Javier; Romance, Miguel

    2016-06-01

    This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates.

  13. Correct degree distribution of apollonian networks

    NASA Astrophysics Data System (ADS)

    Guo, Jin-Li; Wang, Li-Na

    2010-08-01

    In this paper, we point out that there is a shortcoming of the degree distribution and the analyzing approach of the Apollonian network in [Andrade J S, Herrmann H J, Andrade R F S, et al. Phys. Rev. Lett. 94, 018702 (2005).]. Because the Apollonian network is a deterministic network, its degree distribution can be directly calculated. We correct the degree distribution of the Apollonian network. We also give a numerical simulation of network evolution. The analytical result agrees with the simulation well. The results show that there is the shortcoming of the results of Herrmann et al.

  14. Distance distribution in configuration-model networks

    NASA Astrophysics Data System (ADS)

    Nitzan, Mor; Katzav, Eytan; Kühn, Reimer; Biham, Ofer

    2016-06-01

    We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical simulations for networks with degenerate, binomial, and power-law degree distributions. The mean, mode, and variance of the distribution of shortest path lengths are also evaluated. These results provide expressions for central measures and dispersion measures of the distribution of shortest path lengths in terms of moments of the degree distribution, illuminating the connection between the two distributions.

  15. Distributed intelligence in an astronomical Distributed Sensor Network

    NASA Astrophysics Data System (ADS)

    White, R. R.; Davis, H.; Vestrand, W. T.; Wozniak, P. R.

    2008-03-01

    The Telescope Alert Operations Network System (TALONS) was designed and developed in the year 2000, around the architectural principles of a distributed sensor network. This network supported the original Rapid Telescopes for Optical Response (RAPTOR) project goals; however, only with further development could TALONS meet the goals of the larger Thinking Telescope Project. The complex objectives of the Thinking Telescope project required a paradigm shift in the software architecture - the centralised intelligence merged into the TALONS network operations could no longer meet all of the new requirements. The intelligence needed to be divorced from the network operations and developed as a series of peripheral intelligent agents, distributing the decision making and analytical processes based on the temporal volatility of the data. This paper is presented as only one part of the poster from the workshop and in it we will explore the details of this architecture and how that merges with the current Thinking Telescope system to meet our project goals.

  16. Evolving complex networks with conserved clique distributions

    NASA Astrophysics Data System (ADS)

    Kaczor, Gregor; Gros, Claudius

    2008-07-01

    We propose and study a hierarchical algorithm to generate graphs having a predetermined distribution of cliques, the fully connected subgraphs. The construction mechanism may be either random or incorporate preferential attachment. We evaluate the statistical properties of the graphs generated, such as the degree distribution and network diameters, and compare them to some real-world graphs.

  17. Distributing Executive Information Systems through Networks.

    ERIC Educational Resources Information Center

    Penrod, James I.; And Others

    1993-01-01

    Many colleges and universities will soon adopt distributed systems for executive information and decision support. Distribution of shared information through computer networks will improve decision-making processes dramatically on campuses. Critical success factors include administrative support, favorable organizational climate, ease of use,…

  18. Distributed intelligent control and status networking

    NASA Technical Reports Server (NTRS)

    Fortin, Andre; Patel, Manoj

    1993-01-01

    Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

  19. Distribution characteristics of weighted bipartite evolving networks

    NASA Astrophysics Data System (ADS)

    Zhang, Danping; Dai, Meifeng; Li, Lei; Zhang, Cheng

    2015-06-01

    Motivated by an evolving model of online bipartite networks, we introduce a model of weighted bipartite evolving networks. In this model, there are two disjoint sets of nodes, called user node set and object node set. Edges only exist between two disjoint sets. Edge weights represent the usage amount between a couple of user node and object node. This model not only clinches the bipartite networks' internal mechanism of network growth, but also takes into account the object strength deterioration over time step. User strength and object strength follow power-law distributions, respectively. The weighted bipartite evolving networks have scare-free property in certain situations. Numerical simulations results agree with the theoretical analyses.

  20. Tie strength distribution in scientific collaboration networks

    NASA Astrophysics Data System (ADS)

    Ke, Qing; Ahn, Yong-Yeol

    2014-09-01

    Science is increasingly dominated by teams. Understanding patterns of scientific collaboration and their impacts on the productivity and evolution of disciplines is crucial to understand scientific processes. Electronic bibliography offers a unique opportunity to map and investigate the nature of scientific collaboration. Recent studies have demonstrated a counterintuitive organizational pattern of scientific collaboration networks: densely interconnected local clusters consist of weak ties, whereas strong ties play the role of connecting different clusters. This pattern contrasts itself from many other types of networks where strong ties form communities while weak ties connect different communities. Although there are many models for collaboration networks, no model reproduces this pattern. In this paper, we present an evolution model of collaboration networks, which reproduces many properties of real-world collaboration networks, including the organization of tie strengths, skewed degree and weight distribution, high clustering, and assortative mixing.

  1. Resilient Core Networks for Energy Distribution

    SciTech Connect

    Kuntze, Nicolai; Rudolph, Carsten; Leivesley, Sally; Manz, David O.; Endicott-Popovsky, Barbara E.

    2014-07-28

    Abstract—Substations and their control are crucial for the availability of electricity in today’s energy distribution. Ad- vanced energy grids with Distributed Energy Resources require higher complexity in substations, distributed functionality and communication between devices inside substations and between substations. Also, substations include more and more intelligent devices and ICT based systems. All these devices are connected to other systems by different types of communication links or are situated in uncontrolled environments. Therefore, the risk of ICT based attacks on energy grids is growing. Consequently, security measures to counter these risks need to be an intrinsic part of energy grids. This paper introduces the concept of a Resilient Core Network to interconnected substations. This core network provides essen- tial security features, enables fast detection of attacks and allows for a distributed and autonomous mitigation of ICT based risks.

  2. Robust, Distributed Target Tracking Using Sensor Network

    NASA Astrophysics Data System (ADS)

    Neema, Kartavya

    Distributed target tracking using sensor networks is crucial for supporting a variety of applications such as battlefield monitoring, weather monitoring, and air traffic management. This dissertation presents a problem formulation and solution approach for distributed target tracking, comprising of sensor fusion and sensor target allocation problems, in the presence of faults in the sensor measurements. There are times when an architecture with central node is preferred but other times when distributed is necessary, we seek a distributed case that can approach the attractive features of centralized case. Therefore, we propose that the underlying two-fold goals of the distributed target tracking problem is to: (1) reach a consensus in the allocation decisions across the sensor network, and (2) achieve a consensus in the state estimates across all the sensors in the network. These goals ensure that each sensor node has the same information across the sensor network, and any node can behave as a central node. In the process of achieving our goals, we develop two new algorithms, one for distributed sensor-target allocation and another for distributed sensor fusion. The Dual Phase Consensus Algorithm (DPCA) for distributed sensor target allocation is a real time algorithm that works in two phases. The first phase of DPCA is similar to distributed sequential greedy search that combines the benefits of greedy and consensus algorithms to reach a feasible solution. The second phase iteratively improves the allocation eventually leading toward a global optimum. DPCA converges to a feasible solution at the order of number of sensors, and thus can be useful for implementation in real time systems. For distributed sensor fusion, we extend the state-of-art distributed Kalman filtering technique called Generalized Kalman Consensus Filter (GKCF), and make it robust against faults present in the sensor measurements. We particularly focus on two types of faults: (1) outliers in the

  3. Distributed control network for optogenetic experiments

    NASA Astrophysics Data System (ADS)

    Kasprowicz, G.; Juszczyk, B.; Mankiewicz, L.

    2014-11-01

    Nowadays optogenetic experiments are constructed to examine social behavioural relations in groups of animals. A novel concept of implantable device with distributed control network and advanced positioning capabilities is proposed. It is based on wireless energy transfer technology, micro-power radio interface and advanced signal processing.

  4. Optimal design of spatial distribution networks

    NASA Astrophysics Data System (ADS)

    Gastner, Michael T.; Newman, M. E. J.

    2006-07-01

    We consider the problem of constructing facilities such as hospitals, airports, or malls in a country with a nonuniform population density, such that the average distance from a person’s home to the nearest facility is minimized. We review some previous approximate treatments of this problem that indicate that the optimal distribution of facilities should have a density that increases with population density, but does so slower than linearly, as the two-thirds power. We confirm this result numerically for the particular case of the United States with recent population data using two independent methods, one a straightforward regression analysis, the other based on density-dependent map projections. We also consider strategies for linking the facilities to form a spatial network, such as a network of flights between airports, so that the combined cost of maintenance of and travel on the network is minimized. We show specific examples of such optimal networks for the case of the United States.

  5. Energy distribution in disordered elastic networks

    NASA Astrophysics Data System (ADS)

    Plaza, Gustavo R.

    2010-09-01

    Disordered networks are found in many natural and artificial materials, from gels or cytoskeletal structures to metallic foams or bones. Here, the energy distribution in this type of networks is modeled, taking into account the orientation of the struts. A correlation between the orientation and the energy per unit volume is found and described as a function of the connectivity in the network and the relative bending stiffness of the struts. If one or both parameters have relatively large values, the struts aligned in the loading direction present the highest values of energy. On the contrary, if these have relatively small values, the highest values of energy can be reached in the struts oriented transversally. This result allows explaining in a simple way remodeling processes in biological materials, for example, the remodeling of trabecular bone and the reorganization in the cytoskeleton. Additionally, the correlation between the orientation, the affinity, and the bending-stretching ratio in the network is discussed.

  6. Pruning Neural Networks with Distribution Estimation Algorithms

    SciTech Connect

    Cantu-Paz, E

    2003-01-15

    This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algorithm (GA), the paper considers three distribution estimation algorithms (DEAs): a compact GA, an extended compact GA, and the Bayesian Optimization Algorithm. The objective is to determine if the DEAs present advantages over the simple GA in terms of accuracy or speed in this problem. The experiments used a feed forward neural network trained with standard back propagation and public-domain and artificial data sets. The pruned networks seemed to have better or equal accuracy than the original fully-connected networks. Only in a few cases, pruning resulted in less accurate networks. We found few differences in the accuracy of the networks pruned by the four EAs, but found important differences in the execution time. The results suggest that a simple GA with a small population might be the best algorithm for pruning networks on the data sets we tested.

  7. Distributed multisensor fusion with network connection management

    NASA Astrophysics Data System (ADS)

    Kadar, Ivan

    2005-05-01

    The author in previous publications illustrated the need for better understanding the role of Connection Management (CNM) in spatially and geographically diverse distributed sensor networks. This construct is re-examined in a conceptual CNM architectural framework. The purpose of Connection Management is to provide seamless demand-based resource-allocation and sharing of the information products. For optimum distributed information fusion performance, these systems must minimize communications delays and maximize message throughput, reduce or eliminate out-of-sequence measurements, take into account data pedigree and at the same time optimally allocate bandwidth resources and/or encode track data (sources of information) for optimum distributed estimation of target state. In order to achieve overall distributed "network" effectiveness, these systems must be adaptive, and be able distribute data on demand basis in real-time. While the requirements for these systems are known, research in this area has been fragmented. Related problems, goals and potential solutions are explored highlighting the need for a multi-disciplinary approach among communications, estimation, information and queuing theory, networking, optimization and fusion communities. A CNM conceptual architecture and simulation results are illustrated for optimum demand-based bandwidth allocation.

  8. Automatic balancing valves in distribution networks today

    SciTech Connect

    Golestan, F.

    1996-12-31

    Automatic flow-limiting (self-actuated) valves have been in the heating, ventilating, and air-conditioning (HVAC) market for some time now. Their principle of operation is based on fluid momentum and Bernoulli`s theorem. Basically, they absorb pressure to keep the flow rate constant. The general operation and their flow characteristics are described in the 1992 ASHRAE Handbook--Systems and Equipment, chapter 43 (ASHRAE 1992). The application and interaction of these valves with other system components, when installed in hydronic distribution networks, are outlined in this presentation. A simple, multilevel piping network is analyzed. The network consists of a pump, connecting piping, an automatic temperature control valve (ATC), a coil, and balancing valves.

  9. Self Calibrated Wireless Distributed Environmental Sensory Networks

    NASA Astrophysics Data System (ADS)

    Fishbain, Barak; Moreno-Centeno, Erick

    2016-04-01

    Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art.

  10. Self Calibrated Wireless Distributed Environmental Sensory Networks.

    PubMed

    Fishbain, Barak; Moreno-Centeno, Erick

    2016-01-01

    Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs' calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable's true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

  11. Self Calibrated Wireless Distributed Environmental Sensory Networks

    PubMed Central

    Fishbain, Barak; Moreno-Centeno, Erick

    2016-01-01

    Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

  12. Electricity distribution network power quality regulation

    NASA Astrophysics Data System (ADS)

    Lopez Sanchez, Jose Maria

    The regulation of the electricity distribution utilities has evolved to a scenario based on competition and cost-effectiveness. This cost reduction may affect the quality performance. A quality regulatory proposal based on yardstick competition is presented in this Ph.D. thesis. The proposal focuses on the continuity of supply in the electricity distribution networks. The competition is against objective values of the selected zonal quality indices that are computed using a probabilistic model that takes into account the historical behavior of the distribution network and considers the quality indices as random variables. A monitoring scheme has been developed to obtain the basic reliability indices from the rough data. A methodology to segment the supplied area is proposed. The implementation plan of the regulatory proposal and the incentive/penalty scheme to encourage utilities to improve their quality indices, are also presented. An implementation study case of the scheme is shown. The conceptual framework of this proposal and the different regulations of the continuity of supply of several countries are also reviewed in detail.

  13. Using Content Distribution Networks for Astronomy Outreach

    NASA Astrophysics Data System (ADS)

    Jäger, M.; Christiansen, L. L.; André, M.

    2015-09-01

    Thousands of people from all over the world search the internet on a daily basis for the newest discoveries in astronomy: be it in the form of press releases, high resolution images, videos or even planetarium fulldome content. The growing amount of data available, combined with the increasing number of media files and users distributed across the globe, leads to a significant decrease in speed for those users located furthest from the server delivering the content. One solution for bringing astronomical content to users faster is to use a content delivery network.

  14. eSTAR: a distributed telescope network

    NASA Astrophysics Data System (ADS)

    Steele, Iain A.; Naylor, Tim; Allan, Alisdair; Etherton, Jason; Mottram, C. J.

    2002-11-01

    The e-STAR (e-Science Telescopes for Astronomical Research) project uses GRID techniques to develop the software infrastructure for a global network of robotic telescopes. The basic architecture is based around Intelligent Agents which request data from Discovery Nodes that may be telescopes or databases. Communication is based on a development of the XML RTML language secured using the Globus I/O library, with status serving provided via LDAP. We describe the system architecture and protocols devised to give a distributed approach to telescope scheduling, as well as giving details of the implementation of prototype Intelligent Agent and Discovery Node systems.

  15. Fuzzy probabilistic design of water distribution networks

    NASA Astrophysics Data System (ADS)

    Fu, Guangtao; Kapelan, Zoran

    2011-05-01

    The primary aim of this paper is to present a fuzzy probabilistic approach for optimal design and rehabilitation of water distribution systems, combining aleatoric and epistemic uncertainties in a unified framework. The randomness and imprecision in future water consumption are characterized using fuzzy random variables whose realizations are not real but fuzzy numbers, and the nodal head requirements are represented by fuzzy sets, reflecting the imprecision in customers' requirements. The optimal design problem is formulated as a two-objective optimization problem, with minimization of total design cost and maximization of system performance as objectives. The system performance is measured by the fuzzy random reliability, defined as the probability that the fuzzy head requirements are satisfied across all network nodes. The satisfactory degree is represented by necessity measure or belief measure in the sense of the Dempster-Shafer theory of evidence. An efficient algorithm is proposed, within a Monte Carlo procedure, to calculate the fuzzy random system reliability and is effectively combined with the nondominated sorting genetic algorithm II (NSGAII) to derive the Pareto optimal design solutions. The newly proposed methodology is demonstrated with two case studies: the New York tunnels network and Hanoi network. The results from both cases indicate that the new methodology can effectively accommodate and handle various aleatoric and epistemic uncertainty sources arising from the design process and can provide optimal design solutions that are not only cost-effective but also have higher reliability to cope with severe future uncertainties.

  16. When is an ecological network complex? Connectance drives degree distribution and emerging network properties

    PubMed Central

    Gravel, Dominique

    2014-01-01

    Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution. PMID:24688835

  17. Information Weighted Consensus for Distributed Estimation in Vision Networks

    ERIC Educational Resources Information Center

    Kamal, Ahmed Tashrif

    2013-01-01

    Due to their high fault-tolerance, ease of installation and scalability to large networks, distributed algorithms have recently gained immense popularity in the sensor networks community, especially in computer vision. Multi-target tracking in a camera network is one of the fundamental problems in this domain. Distributed estimation algorithms…

  18. Advanced Energy Storage Management in Distribution Network

    SciTech Connect

    Liu, Guodong; Ceylan, Oguzhan; Xiao, Bailu; Starke, Michael R; Ollis, T Ben; King, Daniel J; Irminger, Philip; Tomsovic, Kevin

    2016-01-01

    With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. The proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. The optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. The proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.

  19. Network integration of distributed power generation

    NASA Astrophysics Data System (ADS)

    Dondi, Peter; Bayoumi, Deia; Haederli, Christoph; Julian, Danny; Suter, Marco

    The world-wide move to deregulation of the electricity and other energy markets, concerns about the environment, and advances in renewable and high efficiency technologies has led to major emphasis being placed on the use of small power generation units in a variety of forms. The paper reviews the position of distributed generation (DG, as these small units are called in comparison with central power plants) with respect to the installation and interconnection of such units with the classical grid infrastructure. In particular, the status of technical standards both in Europe and USA, possible ways to improve the interconnection situation, and also the need for decisions that provide a satisfactory position for the network operator (who remains responsible for the grid, its operation, maintenance and investment plans) are addressed.

  20. Social Networking Adapted for Distributed Scientific Collaboration

    NASA Technical Reports Server (NTRS)

    Karimabadi, Homa

    2012-01-01

    Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and

  1. Power distribution in two-dimensional optical network channels

    NASA Astrophysics Data System (ADS)

    Wang, Dong-Xue; Karim, Mohammad A.

    1996-04-01

    The power distribution in two-dimensional optical network channels is analyzed. The maximum number of allowable channels as determined by the characteristics of optical detector is identified, in particular, for neural-network and wavelet-transform applications.

  2. Distribution of entanglement in large-scale quantum networks

    NASA Astrophysics Data System (ADS)

    Perseguers, S.; Lapeyre, G. J., Jr.; Cavalcanti, D.; Lewenstein, M.; Acín, A.

    2013-09-01

    The concentration and distribution of quantum entanglement is an essential ingredient in emerging quantum information technologies. Much theoretical and experimental effort has been expended in understanding how to distribute entanglement in one-dimensional networks. However, as experimental techniques in quantum communication develop, protocols for multi-dimensional systems become essential. Here, we focus on recent theoretical developments in protocols for distributing entanglement in regular and complex networks, with particular attention to percolation theory and network-based error correction.

  3. Random networks with tunable degree distribution and clustering

    NASA Astrophysics Data System (ADS)

    Volz, Erik

    2004-11-01

    We present an algorithm for generating random networks with arbitrary degree distribution and clustering (frequency of triadic closure). We use this algorithm to generate networks with exponential, power law, and Poisson degree distributions with variable levels of clustering. Such networks may be used as models of social networks and as a testable null hypothesis about network structure. Finally, we explore the effects of clustering on the point of the phase transition where a giant component forms in a random network, and on the size of the giant component. Some analysis of these effects is presented.

  4. Exploring distributed leadership in the BC Sepsis Network.

    PubMed

    Gorley, Charlotte; Lindstrom, Ronald R; McKeown, Shari; Krause, Christina; Pamplin, Chantale; Sweet, David; Marsden, Julian; Kennedy, Colleen

    2016-03-01

    Commissioned research was undertaken to explore the role of networks in supporting large-scale change and improvement. Participatory action research and social network analysis were used to study the BC Sepsis Network. Findings of this research include insights into distributed leadership, enablers and barriers within a network approach; the importance of relationships and trust; and the need for meaningful and timely data. Recommendations are made for health leaders who are considering utilizing networks for improving patient quality and safety. PMID:26872797

  5. A Complex Network Approach to Distributional Semantic Models

    PubMed Central

    Utsumi, Akira

    2015-01-01

    A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

  6. Sampling from complex networks using distributed learning automata

    NASA Astrophysics Data System (ADS)

    Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

    2014-02-01

    A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

  7. Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

    NASA Astrophysics Data System (ADS)

    Zhang, Xianjun

    The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

  8. Prioritizing the restoration of network distribution transformers using distribution system loading and network reliability indices

    NASA Astrophysics Data System (ADS)

    Hardowar, Roupchan

    A method is proposed to prioritize the repair or replacement of out-of-service transformers that feed a heavily meshed secondary grid. The priority assigned to the restoration of a specific transformer is based on the reduction in risk that results from this replacement. Risk is equated to the number of customer outages that would occur if the transformer remains out of service. This risk addresses both the possibility of network collapse following feeder failures (occasioned by load-induced failure of transformers or feeders) and local customer outages on the secondary network. This prediction of risk makes extensive use of load predictions for feeder sections, distribution transformers and secondary mains. A software tool that implements the equations proposed in this paper gives system planners and operators the ability to quickly and economically select the next transformer to be repaired or replaced.

  9. Distributed Computer Networks in Support of Complex Group Practices

    PubMed Central

    Wess, Bernard P.

    1978-01-01

    The economics of medical computer networks are presented in context with the patient care and administrative goals of medical networks. Design alternatives and network topologies are discussed with an emphasis on medical network design requirements in distributed data base design, telecommunications, satellite systems, and software engineering. The success of the medical computer networking technology is predicated on the ability of medical and data processing professionals to design comprehensive, efficient, and virtually impenetrable security systems to protect data bases, network access and services, and patient confidentiality.

  10. Embedding dynamical networks into distributed models

    NASA Astrophysics Data System (ADS)

    Innocenti, Giacomo; Paoletti, Paolo

    2015-07-01

    Large networks of interacting dynamical systems are well-known for the complex behaviours they are able to display, even when each node features a quite simple dynamics. Despite examples of such networks being widespread both in nature and in technological applications, the interplay between the local and the macroscopic behaviour, through the interconnection topology, is still not completely understood. Moreover, traditional analytical methods for dynamical response analysis fail because of the intrinsically large dimension of the phase space of the network which makes the general problem intractable. Therefore, in this paper we develop an approach aiming to condense all the information in a compact description based on partial differential equations. By focusing on propagative phenomena, rigorous conditions under which the original network dynamical properties can be successfully analysed within the proposed framework are derived as well. A network of Fitzhugh-Nagumo systems is finally used to illustrate the effectiveness of the proposed method.

  11. Pain: A Distributed Brain Information Network?

    PubMed Central

    Mano, Hiroaki; Seymour, Ben

    2015-01-01

    Understanding how pain is processed in the brain has been an enduring puzzle, because there doesn't appear to be a single “pain cortex” that directly codes the subjective perception of pain. An emerging concept is that, instead, pain might emerge from the coordinated activity of an integrated brain network. In support of this view, Woo and colleagues present evidence that distinct brain networks support the subjective changes in pain that result from nociceptive input and self-directed cognitive modulation. This evidence for the sensitivity of distinct neural subsystems to different aspects of pain opens up the way to more formal computational network theories of pain. PMID:25562782

  12. Distributed sensor networks with collective computation

    SciTech Connect

    Lanman, D. R.

    2001-01-01

    Simulations of a network of N sensors have been performed. The simulation space contains a number of sound sources and a large number of sensors. Each sensor is equipped with an omni-directional microphone and is capable of measuring only the time of arrival of a signal. Sensors are able to wirelessly transmit and receive packets of information, and have some computing power. The sensors were programmed to merge all information (received packets as well as local measurements) into a 'world view' for that node. This world view is then transmitted. In this way, information can slowly diffuse across the network. One node was monitored in the network as a proxy for when information had diffused across the network. Simulations demonstrated that the energy expended per sensor per time step was approximately independent of N.

  13. Minimizing communication cost among distributed controllers in software defined networks

    NASA Astrophysics Data System (ADS)

    Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

    2016-08-01

    Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

  14. Distributed neural computations for embedded sensor networks

    NASA Astrophysics Data System (ADS)

    Peckens, Courtney A.; Lynch, Jerome P.; Pei, Jin-Song

    2011-04-01

    Wireless sensing technologies have recently emerged as an inexpensive and robust method of data collection in a variety of structural monitoring applications. In comparison with cabled monitoring systems, wireless systems offer low-cost and low-power communication between a network of sensing devices. Wireless sensing networks possess embedded data processing capabilities which allow for data processing directly at the sensor, thereby eliminating the need for the transmission of raw data. In this study, the Volterra/Weiner neural network (VWNN), a powerful modeling tool for nonlinear hysteretic behavior, is decentralized for embedment in a network of wireless sensors so as to take advantage of each sensor's processing capabilities. The VWNN was chosen for modeling nonlinear dynamic systems because its architecture is computationally efficient and allows computational tasks to be decomposed for parallel execution. In the algorithm, each sensor collects it own data and performs a series of calculations. It then shares its resulting calculations with every other sensor in the network, while the other sensors are simultaneously exchanging their information. Because resource conservation is important in embedded sensor design, the data is pruned wherever possible to eliminate excessive communication between sensors. Once a sensor has its required data, it continues its calculations and computes a prediction of the system acceleration. The VWNN is embedded in the computational core of the Narada wireless sensor node for on-line execution. Data generated by a steel framed structure excited by seismic ground motions is used for validation of the embedded VWNN model.

  15. Comparative-effectiveness research in distributed health data networks.

    PubMed

    Toh, S; Platt, R; Steiner, J F; Brown, J S

    2011-12-01

    Comparative-effectiveness research (CER) can be conducted within a distributed health data network. Such networks allow secure access to separate data sets from different data partners and overcome many practical obstacles related to patient privacy, data security, and proprietary concerns. A scalable network architecture supports a wide range of CER activities and meets the data infrastructure needs envisioned by the Federal Coordinating Council for Comparative Effectiveness Research. PMID:22030567

  16. Degree distributions of bipartite networks and their projections

    NASA Astrophysics Data System (ADS)

    Vasques Filho, Demival; O'Neale, Dion

    Bipartite networks play an important role in the analysis of social and economic systems as they explicitly show the conceptual links between different types of entities. As an example, it is possible to build networks to investigate interactions regarding scientific and technological innovation that are well represented by a natural bipartite structure. Since we are often most interested in only one of the node types (e.g. the authors in an author-publication network), it is common to end up working with a projected version of the underlying bipartite network. The topology of projections and the dynamics that take place on it are highly dependent on the probability distribution of nodes degrees. We use the formalism of generating functions to infer how the degree distributions of the original bipartite network affect the distribution in the projected version. Moreover, we create artificial bipartite graphs by arbitrarily choosing degree distributions for the sets of nodes and construct the projection to analyze the resulting probability distribution. Our findings show that when projecting onto a particular set of nodes, the resulting degree distribution follows the behavior of the probability distribution of such nodes, subject, however, to the tail of the opposite distribution.

  17. Flow distributions and spatial correlations in human brain capillary networks

    NASA Astrophysics Data System (ADS)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  18. Collaborative Estimation in Distributed Sensor Networks

    ERIC Educational Resources Information Center

    Kar, Swarnendu

    2013-01-01

    Networks of smart ultra-portable devices are already indispensable in our lives, augmenting our senses and connecting our lives through real time processing and communication of sensory (e.g., audio, video, location) inputs. Though usually hidden from the user's sight, the engineering of these devices involves fierce tradeoffs between energy…

  19. Optical Intrabuilding and Interbuilding Distribution Networks.

    ERIC Educational Resources Information Center

    Hull, Joseph A.

    Fiber optics communication technology is a potential competitive alternative to coaxial cable and shielded twisted pairlines as a wide-band communications medium. Pilot demonstrations by public institutions such as the health care delivery system can test the application of this new technology. Fiber optic networks may have the potential to be…

  20. Optimization of an interactive distributive computer network

    NASA Technical Reports Server (NTRS)

    Frederick, V.

    1985-01-01

    The activities under a cooperative agreement for the development of a computer network are briefly summarized. Research activities covered are: computer operating systems optimization and integration; software development and implementation of the IRIS (Infrared Imaging of Shuttle) Experiment; and software design, development, and implementation of the APS (Aerosol Particle System) Experiment.

  1. A distributed framework for inter-domain virtual network embedding

    NASA Astrophysics Data System (ADS)

    Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

    2013-03-01

    Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

  2. Department Networks and Distributed Leadership in Schools

    ERIC Educational Resources Information Center

    de Lima, Jorge Avila

    2008-01-01

    Many schools are organised into departments which function as contexts that frame teachers' professional experiences in important ways. Some educational systems have adopted distributed forms of leadership within schools that rely strongly on the departmental structure and on the role of the department coordinator as teacher leader. This paper…

  3. LaRC local area networks to support distributed computing

    NASA Technical Reports Server (NTRS)

    Riddle, E. P.

    1984-01-01

    The Langley Research Center's (LaRC) Local Area Network (LAN) effort is discussed. LaRC initiated the development of a LAN to support a growing distributed computing environment at the Center. The purpose of the network is to provide an improved capability (over inteactive and RJE terminal access) for sharing multivendor computer resources. Specifically, the network will provide a data highway for the transfer of files between mainframe computers, minicomputers, work stations, and personal computers. An important influence on the overall network design was the vital need of LaRC researchers to efficiently utilize the large CDC mainframe computers in the central scientific computing facility. Although there was a steady migration from a centralized to a distributed computing environment at LaRC in recent years, the work load on the central resources increased. Major emphasis in the network design was on communication with the central resources within the distributed environment. The network to be implemented will allow researchers to utilize the central resources, distributed minicomputers, work stations, and personal computers to obtain the proper level of computing power to efficiently perform their jobs.

  4. Network formation: neighborhood structures, establishment costs, and distributed learning.

    PubMed

    Chasparis, Georgios C; Shamma, Jeff S

    2013-12-01

    We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games. PMID:23757585

  5. Distributed Inference in Tree Networks Using Coding Theory

    NASA Astrophysics Data System (ADS)

    Kailkhura, Bhavya; Vempaty, Aditya; Varshney, Pramod K.

    2015-07-01

    In this paper, we consider the problem of distributed inference in tree based networks. In the framework considered in this paper, distributed nodes make a 1-bit local decision regarding a phenomenon before sending it to the fusion center (FC) via intermediate nodes. We propose the use of coding theory based techniques to solve this distributed inference problem in such structures. Data is progressively compressed as it moves towards the FC. The FC makes the global inference after receiving data from intermediate nodes. Data fusion at nodes as well as at the FC is implemented via error correcting codes. In this context, we analyze the performance for a given code matrix and also design the optimal code matrices at every level of the tree. We address the problems of distributed classification and distributed estimation separately and develop schemes to perform these tasks in tree networks. The proposed schemes are of practical significance due to their simple structure. We study the asymptotic inference performance of our schemes for two different classes of tree networks: fixed height tree networks, and fixed degree tree networks. We show that the proposed schemes are asymptotically optimal under certain conditions.

  6. Discriminating topology in galaxy distributions using network analysis

    NASA Astrophysics Data System (ADS)

    Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

    2016-07-01

    The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.

  7. Degree distribution of random birth-and-death network with network size decline

    NASA Astrophysics Data System (ADS)

    Xiao-Jun, Zhang; Hui-Lan, Yang

    2016-06-01

    In this paper, we provide a general method to obtain the exact solutions of the degree distributions for random birth-and-death network (RBDN) with network size decline. First, by stochastic process rules, the steady state transformation equations and steady state degree distribution equations are given in the case of m ≥ 3 and 0 < p < 1/2, then the average degree of network with n nodes is introduced to calculate the degree distributions. Specifically, taking m = 3 for example, we explain the detailed solving process, in which computer simulation is used to verify our degree distribution solutions. In addition, the tail characteristics of the degree distribution are discussed. Our findings suggest that the degree distributions will exhibit Poisson tail property for the declining RBDN. Project supported by the National Natural Science Foundation of China (Grant No. 61273015) and the Chinese Scholarship Council.

  8. Exploring empowerment in settings: mapping distributions of network power.

    PubMed

    Neal, Jennifer Watling

    2014-06-01

    This paper brings together two trends in the empowerment literature-understanding empowerment in settings and understanding empowerment as relational-by examining what makes settings empowering from a social network perspective. Specifically, extending Neal and Neal's (Am J Community Psychol 48(3/4):157-167, 2011) conception of network power, an empowering setting is defined as one in which (1) actors have existing relationships that allow for the exchange of resources and (2) the distribution of network power among actors in the setting is roughly equal. The paper includes a description of how researchers can examine distributions of network power in settings. Next, this process is illustrated in both an abstract example and using empirical data on early adolescents' peer relationships in urban classrooms. Finally, implications for theory, methods, and intervention related to understanding empowering settings are explored. PMID:24213301

  9. Interconnecting PV on New York City's Secondary Network Distribution System

    SciTech Connect

    Anderson, K; Coddington, M; Burman, K; Hayter, S; Kroposki, B; Watson, and A

    2009-11-01

    The U.S. Department of Energy (DOE) has teamed with cities across the country through the Solar America Cities (SAC) partnership program to help reduce barriers and accelerate implementation of solar energy. The New York City SAC team is a partnership between the City University of New York (CUNY), the New York City Mayor s Office of Long-term Planning and Sustainability, and the New York City Economic Development Corporation (NYCEDC).The New York City SAC team is working with DOE s National Renewable Energy Laboratory (NREL) and Con Edison, the local utility, to develop a roadmap for photovoltaic (PV) installations in the five boroughs. The city set a goal to increase its installed PV capacity from1.1 MW in 2005 to 8.1 MW by 2015 (the maximum allowed in 2005). A key barrier to reaching this goal, however, is the complexity of the interconnection process with the local utility. Unique challenges are associated with connecting distributed PV systems to secondary network distribution systems (simplified to networks in this report). Although most areas of the country use simpler radial distribution systems to distribute electricity, larger metropolitan areas like New York City typically use networks to increase reliability in large load centers. Unlike the radial distribution system, where each customer receives power through a single line, a network uses a grid of interconnected lines to deliver power to each customer through several parallel circuits and sources. This redundancy improves reliability, but it also requires more complicated coordination and protection schemes that can be disrupted by energy exported from distributed PV systems. Currently, Con Edison studies each potential PV system in New York City to evaluate the system s impact on the network, but this is time consuming for utility engineers and may delay the customer s project or add cost for larger installations. City leaders would like to streamline this process to facilitate faster, simpler, and

  10. A distributed name resolution system in information centric networks

    NASA Astrophysics Data System (ADS)

    Elbreiki, Walid; Arlimatti, Shivaleela; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

    2016-08-01

    Information Centric Networks (ICN) is the new paradigm that envisages to shift the Internet away from its existing Point-to-Point architecture to a data centric, where communication is based on named hosts rather than the information stored on these hosts. Name Resolution is the center of attraction for ICN, where Named Data Objects (NDO) are used for identifying the information and guiding for routing or forwarding inside ICN. Recently, several researches use distributed NRS to overcome the problem of interest flooding, congestion and overloading. Yet the distribution of NRS is based on random distribution. How to distribute the NRS is still an important and challenging problem. In this work, we address the problem of distribution of NRS by proposing a new mechanism called Distributed Name Resolution System (DNRS), by considering the time of publishing the NDOs in the NRS. This mechanism partitions the network to distribute the workload among NRSs by increasing storage capacity. In addition, partitioning the network increases flexibility and scalability of NRS. We evaluate the effectiveness of our proposed mechanism, which achieves lesser end-to-end delay with more average throughputs compared to random distribution of NRS without disturbing the underlying routing or forwarding strategies.

  11. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    NASA Astrophysics Data System (ADS)

    Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang

    2008-12-01

    Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  12. Development of Distributed Generic Simulator (GenSim) through Invention of Simulated Network (simNetwork)

    NASA Astrophysics Data System (ADS)

    Koo, Cheol-Hea; Lee, Hoon-Hee; Cheon, Yee-Jin

    2011-09-01

    A simulated network protocol provides the capability of distributed simulation to a generic simulator. Through this, full coverage of management of data and service handling among separated simulators is achieved. The distributed simulation environment is much more conducive to handling simulation load balancing and hazard treatment than a standalone computer. According to the simulated network protocol, one simulator takes on the role of server and the other simulators take on the role of client, and client is controlled by server. The purpose of the simulated network protocol is to seamlessly connect multiple simulator instances into a single simulation environment. This paper presents the development of a simulated network (simNetwork) that provides the capability of distributed simulation to a generic simulator (GenSim), which is a software simulator of satellites that has been developed by the Korea Aerospace Research Institute since 2010, to use as a flight software! validation bench for future satellite development.

  13. Distributed authentication for randomly compromised networks

    NASA Astrophysics Data System (ADS)

    Beals, Travis R.; Hynes, Kevin P.; Sanders, Barry C.

    2009-08-01

    We introduce a simple, practical approach with probabilistic information-theoretic security to solve one of quantum key distribution's major security weaknesses: the requirement of an authenticated classical channel to prevent man-in-the-middle attacks. Our scheme employs classical secret sharing and partially trusted intermediaries to provide arbitrarily high confidence in the security of the protocol. Although certain failures elude detection, we discuss preemptive strategies to reduce the probability of failure to an arbitrarily small level: the probability of such failures is exponentially suppressed with increases in connectivity (i.e. connections per node).

  14. Joint Channel-Network Coding (JCNC) for Distributed Storage in Wireless Network

    NASA Astrophysics Data System (ADS)

    Wang, Ning; Lin, Jiaru

    We propose to construct a joint channel-network coding (knosswn as Random Linear Coding) scheme based on improved turbo codes for the distributed storage in wireless communication network with k data nodes, s storage nodes (kdistributed storage with erasure channel to AWGN and fading channel scenario. We investigate the throughput performance of the Joint Channel-Network Coding (JCNC) system benefits from network coding, compared with that of system without network coding based only on store and forward (S-F) approach. Another helpful parameter: node degree (L) indicates how many storage nodes one data packet should fall onto. L characterizes the en/decoding complexity of the system. Moreover, this proposed framework can be extended to ad-hoc and sensor network easily.

  15. Heat flux distribution and rectification of complex networks

    NASA Astrophysics Data System (ADS)

    Liu, Zonghua; Wu, Xiang; Yang, Huijie; Gupte, Neelima; Li, Baowen

    2010-02-01

    It was recently found that the heterogeneity of complex networks can enhance transport properties such as epidemic spreading, electric energy transfer, etc. A trivial deduction would be that the presence of hubs in complex networks can also accelerate the heat transfer although no concrete research has been done so far. In the present study, we have studied this problem and have found a surprising answer: the heterogeneity does not favor but prevents the heat transfer. We present a model to study heat conduction in complex networks and find that the network topology greatly affects the heat flux. The heat conduction decreases with the increase of heterogeneity of the network caused by both degree distribution and the clustering coefficient. Its underlying mechanism can be understood by using random matrix theory. Moreover, we also study the rectification effect and find that it is related to the degree difference of the network, and the distance between the source and the sink. These findings may have potential applications in real networks, such as nanotube/nanowire networks and biological networks.

  16. Gene network inference by fusing data from diverse distributions

    PubMed Central

    Žitnik, Marinka; Zupan, Blaž

    2015-01-01

    Motivation: Markov networks are undirected graphical models that are widely used to infer relations between genes from experimental data. Their state-of-the-art inference procedures assume the data arise from a Gaussian distribution. High-throughput omics data, such as that from next generation sequencing, often violates this assumption. Furthermore, when collected data arise from multiple related but otherwise nonidentical distributions, their underlying networks are likely to have common features. New principled statistical approaches are needed that can deal with different data distributions and jointly consider collections of datasets. Results: We present FuseNet, a Markov network formulation that infers networks from a collection of nonidentically distributed datasets. Our approach is computationally efficient and general: given any number of distributions from an exponential family, FuseNet represents model parameters through shared latent factors that define neighborhoods of network nodes. In a simulation study, we demonstrate good predictive performance of FuseNet in comparison to several popular graphical models. We show its effectiveness in an application to breast cancer RNA-sequencing and somatic mutation data, a novel application of graphical models. Fusion of datasets offers substantial gains relative to inference of separate networks for each dataset. Our results demonstrate that network inference methods for non-Gaussian data can help in accurate modeling of the data generated by emergent high-throughput technologies. Availability and implementation: Source code is at https://github.com/marinkaz/fusenet. Contact: blaz.zupan@fri.uni-lj.si Supplementary information: Supplementary information is available at Bioinformatics online. PMID:26072487

  17. Distributed Reinforcement Learning Approach for Vehicular Ad Hoc Networks

    NASA Astrophysics Data System (ADS)

    Wu, Celimuge; Kumekawa, Kazuya; Kato, Toshihiko

    In Vehicular Ad hoc Networks (VANETs), general purpose ad hoc routing protocols such as AODV cannot work efficiently due to the frequent changes in network topology caused by vehicle movement. This paper proposes a VANET routing protocol QLAODV (Q-Learning AODV) which suits unicast applications in high mobility scenarios. QLAODV is a distributed reinforcement learning routing protocol, which uses a Q-Learning algorithm to infer network state information and uses unicast control packets to check the path availability in a real time manner in order to allow Q-Learning to work efficiently in a highly dynamic network environment. QLAODV is favored by its dynamic route change mechanism, which makes it capable of reacting quickly to network topology changes. We present an analysis of the performance of QLAODV by simulation using different mobility models. The simulation results show that QLAODV can efficiently handle unicast applications in VANETs.

  18. Evolution of the statistical distribution in a topological defect network

    PubMed Central

    Xue, Fei; Wang, Xueyun; socolenco, Ion; Gu, Yijia; Chen, Long-Qing; Cheong, Sang-Wook

    2015-01-01

    The complex networks of numerous topological defects in hexagonal manganites are highly relevant to vastly different phenomena from the birth of our cosmos to superfluidity transition. The topological defects in hexagonal manganites form two types of domain networks: type-I without and type-II with electric self-poling. A combined phase-field simulations and experimental study shows that the frequencies of domains with N-sides, i.e. of N-gons, in a type-I network are fitted by a lognormal distribution, whereas those in type-II display a scale-free power-law distribution with exponent ∼2. A preferential attachment process that N-gons with a larger N have higher probability of coalescence is responsible for the emergence of the scale-free networks. Since the domain networks can be observed, analyzed, and manipulated at room temperature, hexagonal manganites provide a unique opportunity to explore how the statistical distribution of a topological defect network evolves with an external electric field. PMID:26586339

  19. Evolution of the statistical distribution in a topological defect network

    NASA Astrophysics Data System (ADS)

    Xue, Fei; Wang, Xueyun; Socolenco, Ion; Gu, Yijia; Chen, Long-Qing; Cheong, Sang-Wook

    2015-11-01

    The complex networks of numerous topological defects in hexagonal manganites are highly relevant to vastly different phenomena from the birth of our cosmos to superfluidity transition. The topological defects in hexagonal manganites form two types of domain networks: type-I without and type-II with electric self-poling. A combined phase-field simulations and experimental study shows that the frequencies of domains with N-sides, i.e. of N-gons, in a type-I network are fitted by a lognormal distribution, whereas those in type-II display a scale-free power-law distribution with exponent ∼2. A preferential attachment process that N-gons with a larger N have higher probability of coalescence is responsible for the emergence of the scale-free networks. Since the domain networks can be observed, analyzed, and manipulated at room temperature, hexagonal manganites provide a unique opportunity to explore how the statistical distribution of a topological defect network evolves with an external electric field.

  20. Evolution of the statistical distribution in a topological defect network.

    PubMed

    Xue, Fei; Wang, Xueyun; Socolenco, Ion; Gu, Yijia; Chen, Long-Qing; Cheong, Sang-Wook

    2015-01-01

    The complex networks of numerous topological defects in hexagonal manganites are highly relevant to vastly different phenomena from the birth of our cosmos to superfluidity transition. The topological defects in hexagonal manganites form two types of domain networks: type-I without and type-II with electric self-poling. A combined phase-field simulations and experimental study shows that the frequencies of domains with N-sides, i.e. of N-gons, in a type-I network are fitted by a lognormal distribution, whereas those in type-II display a scale-free power-law distribution with exponent ∼2. A preferential attachment process that N-gons with a larger N have higher probability of coalescence is responsible for the emergence of the scale-free networks. Since the domain networks can be observed, analyzed, and manipulated at room temperature, hexagonal manganites provide a unique opportunity to explore how the statistical distribution of a topological defect network evolves with an external electric field. PMID:26586339

  1. Distributed network management in the flat structured mobile communities

    NASA Astrophysics Data System (ADS)

    Balandina, Elena

    2005-10-01

    Delivering proper management into the flat structured mobile communities is crucial for improving users experience and increase applications diversity in mobile networks. The available P2P applications do application-centric management, but it cannot replace network-wide management, especially when a number of different applications are used simultaneously in the network. The network-wide management is the key element required for a smooth transition from standalone P2P applications to the self-organizing mobile communities that maintain various services with quality and security guaranties. The classical centralized network management solutions are not applicable in the flat structured mobile communities due to the decentralized nature and high mobility of the underlying networks. Also the basic network management tasks have to be revised taking into account specialties of the flat structured mobile communities. The network performance management becomes more dependent on the current nodes' context, which also requires extension of the configuration management functionality. The fault management has to take into account high mobility of the network nodes. The performance and accounting managements are mainly targeted in maintain an efficient and fair access to the resources within the community, however they also allow unbalanced resource use of the nodes that explicitly permit it, e.g. as a voluntary donation to the community or due to the profession (commercial) reasons. The security management must implement the new trust models, which are based on the community feedback, professional authorization, and a mix of both. For fulfilling these and another specialties of the flat structured mobile communities, a new network management solution is demanded. The paper presents a distributed network management solution for flat structured mobile communities. Also the paper points out possible network management roles for the different parties (e.g. operators, service

  2. Experimental and computational studies of fatty acid distribution networks.

    PubMed

    Liu, Yong; Buendía-Rodríguez, Germán; Peñuelas-Rívas, Claudia Giovanna; Tan, Zhiliang; Rívas-Guevara, María; Tenorio-Borroto, Esvieta; Munteanu, Cristian R; Pazos, Alejandro; González-Díaz, Humberto

    2015-11-01

    Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal microbiome fatty acid (FA) composition/distribution play a vital role in discovering the contribution of food components to ruminant products (e.g., meat and milk) when pursuing a healthy diet. Hansch's models based on Linear Free Energy Relationships (LFERs) using physicochemical parameters, such as partition coefficients, molar refractivity, and polarizability, as input variables (Vk) are advocated. In this work, a new combined experimental and theoretical strategy was proposed to study the effect of ω-6/ω-3 ratios, FA chemical structure, and other factors over FA distribution networks in the ruminal microbiome. In step 1, experiments were carried out to measure long chain fatty acid (LCFA) profiles in the rumen microbiome (bacterial and protozoan), and volatile fatty acids (VFAs) in fermentation media. In step 2, the proportions and physicochemical parameter values of LCFAs and VFAs were calculated under different boundary conditions (cj) like c1 = acid and/or base methylation treatments, c2 = with/without fermentation, c3 = FA distribution phase (media, bacterial, or protozoan microbiome), etc. In step 3, Perturbation Theory (PT) and LFER ideas were combined to develop a PT-LFER model of a FA distribution network using physicochemical parameters (V(k)), the corresponding Box-Jenkins (ΔV(kj)) and PT operators (ΔΔV(kj)) in statistical analysis. The best PT-LFER model found predicted the effects of perturbations over the FA distribution network with sensitivity, specificity, and accuracy > 80% for 407 655 cases in training + external validation series. In step 4, alternative PT-LFER and PT-NLFER models were tested for training Linear and Non-Linear Artificial Neural Networks (ANNs). PT-NLFER models based on ANNs presented better performance but are

  3. Acoustic mapping of ocean currents using networked distributed sensors.

    PubMed

    Huang, Chen-Fen; Yang, T C; Liu, Jin-Yuan; Schindall, Jeff

    2013-09-01

    Distributed underwater sensors are expected to provide oceanographic monitoring over large areas. As fabrication technology advances, low cost sensors will be available for many uses. The sensors communicate to each other and are networked using acoustic communications. This paper first studies the performance of such systems for current measurements using tomographic inversion approaches to compare with that of a conventional system which distributes the sensors on the periphery of the area of interest. It then proposes two simple signal processing methods for ocean current mapping (using distributed networked sensors) aimed at real-time in-buoy processing. Tomographic inversion generally requires solving a challenging high dimensional inverse problem, involving substantial computations. Given distributed sensors, currents can be constructed locally based on data from neighboring sensors. It is shown using simulated data that similar results are obtained using distributed processing as using conventional tomographic approaches. The advantage for distributed systems is that by increasing the number of nodes, one gains a much more improved performance. Furthermore, distributed systems use much less energy than a conventional tomographic system for the same area coverage. Experimental data from an acoustic communication and networking experiment are used to demonstrate the feasibility of acoustic current mapping. PMID:23967940

  4. Multiplexed Signal Distribution Using Fiber Network For Radar Applications

    NASA Astrophysics Data System (ADS)

    Meena, D.; Prakasam, L. G. M.; Pandey, D. C.; Shivaleela, E. S.; Srinivas, T.

    2011-10-01

    Most of the modern Active phased Array Radars consist of multiple receive modules in an Antenna array. This demands the distribution of various Local Oscillator Signals (LOs) for the down conversion of received signals to the Intermediate Frequency (IF) band signals. This is normally achieved through Radio Frequency (RF) cables with Complex distribution networks which adds additional weight to the Arrays. Similarly these kinds of receivers require Control/Clock signals which are digital in nature, for the synchronization of all receive modules of the radar system which are also distributed through electrical cables. In addition some of the control messages (Digital in nature) are distributed through Optical interfaces. During Transmit operation, the RF transmit Signal is also distributed through the same receiver modules which will in turn distribute to all the elements of the Array which require RF cables which are bulky in nature. So it is very essential to have a multiplexed Signal distribution scheme through the existing Optical Interface for distribution of these signals which are RF and Digital in nature. This paper discusses about various distribution schemes for the realization in detail. We propose a distribution network architecture where existing fibers can be further extended for the distribution of other types of signals also. In addition, it also briefs about a comparative analysis done on these schemes by considering the complexity and space constraint factors. Thus we bring out an optimum scheme which will lead to the reduction in both hardware complexity and weight of the array systems. In addition, being an Optical network it is free from Electromagnetic interference which is a crucial requirement in an array environment.

  5. Universal scaling of optimal current distribution in transportation networks.

    PubMed

    Simini, Filippo; Rinaldo, Andrea; Maritan, Amos

    2009-04-01

    Transportation networks are inevitably selected with reference to their global cost which depends on the strengths and the distribution of the embedded currents. We prove that optimal current distributions for a uniformly injected d -dimensional network exhibit robust scale-invariance properties, independently of the particular cost function considered, as long as it is convex. We find that, in the limit of large currents, the distribution decays as a power law with an exponent equal to (2d-1)/(d-1). The current distribution can be exactly calculated in d=2 for all values of the current. Numerical simulations further suggest that the scaling properties remain unchanged for both random injections and by randomizing the convex cost functions. PMID:19518304

  6. EDONIO: Extended distributed object network I/O library

    SciTech Connect

    D`Azevedo, E.F.; Romine, C.H.

    1995-03-01

    This report describes EDONIO (Extended Distributed Object Network I/O), an enhanced version of DONIO (Distributed Object Network I/O Library) optimized for the Intel Paragon Systems using the new M-ASYNC access mode. DONIO provided fast file I/O capabilities in the Intel iPSC/860 and Paragon distributed memory parallel environments by caching a copy of the entire file in memory distributed across all processors. EDONIO is more memory efficient by caching only a subset of the disk file at a time. DONIO was restricted by the high memory requirements and use of 32-bit integer indexing to handle files no larger than 2 Gigabytes. EDONIO overcomes this barrier by using the extended integer library routines provided by Intel`s NX operating system. For certain applications, EDONIO may show a ten-fold improvement in performance over the native NX I/O routines.

  7. Conductivity in percolation networks with broad distributions of resistances

    NASA Astrophysics Data System (ADS)

    Machta, J.; Guyer, R. A.; Moore, S. M.

    1986-04-01

    Diluted resistor networks with a broad distribution of resistances are studied near the percolation threshold. A hierarchical model of the backbone of the percolation cluster is employed. Resistor networks are considered where the resistors, R, are chosen from a distribution having a power-law tail such that Prob\\{R>X\\}~X-α as X-->∞, 0<α<1. Such distributions arise naturally in con- tinuum percolation systems. The hierarchical model is studied numerically and using a renormalization-group transformation for the distribution of resistances. The conclusion is that the conductivity exponent t is the greater of to and (d-2)ν+1/α where to is the universal value of the conductivity exponent and ν is the correlation-length exponent. This result is in agreement with Straley's earlier predictions [J. Phys. C 15, 2333 (1982); 15, 2343 (1982)].

  8. Fault location of underground distribution network based on RBF network optimized by improved PSO algorithm

    NASA Astrophysics Data System (ADS)

    Tian, Shu; Zhao, Min

    2013-03-01

    To solve the difficult problem that exists in the location of single-phase ground fault for coal mine underground distribution network, a fault location method using RBF network optimized by improved PSO algorithm based on the mapping relationship between wavelet packet transform modulus maxima of specific frequency bands transient state zero sequence current in the fault line and fault point position is presented. The simulation analysis results in the cases of different transition resistances and fault distances show that the RBF network optimized by improved PSO algorithm can obtain accurate and reliable fault location results, and the fault location perfor- mance is better than traditional RBF network.

  9. Determination Method for Optimal Installation of Active Filters in Distribution Network with Distributed Generation

    NASA Astrophysics Data System (ADS)

    Kawasaki, Shoji; Hayashi, Yasuhiro; Matsuki, Junya; Kikuya, Hirotaka; Hojo, Masahide

    Recently, the harmonic troubles in a distribution network are worried in the background of the increase of the connection of distributed generation (DG) and the spread of the power electronics equipments. As one of the strategies, control the harmonic voltage by installing an active filter (AF) has been researched. In this paper, the authors propose a computation method to determine the optimal allocations, gains and installation number of AFs so as to minimize the maximum value of voltage total harmonic distortion (THD) for a distribution network with DGs. The developed method is based on particle swarm optimization (PSO) which is one of the nonlinear optimization methods. Especially, in this paper, the case where the harmonic voltage or the harmonic current in a distribution network is assumed by connecting many DGs through the inverters, and the authors propose a determination method of the optimal allocation and gain of AF that has the harmonic restrictive effect in the whole distribution network. Moreover, the authors propose also about a determination method of the necessary minimum installation number of AFs, by taking into consideration also about the case where the target value of harmonic suppression cannot be reached, by one set only of AF. In order to verify the validity and effectiveness of the proposed method, the numerical simulations are carried out by using an analytical model of distribution network with DGs.

  10. Using Distributed Sensor Network Architecture to Link Heterogeneous Astronomical Assets

    NASA Astrophysics Data System (ADS)

    White, R.; Evans, S.; Pergande, J.; Vestrand, W.; Wozniak, P.; Wren, J.

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in this type of instrumentation. Here we present the Telescope ALert Operations Network System (TALONS), a network software suite that allows intercommunication between external and internal astronomical resources and controls the distribution of information to each of the resources. TALONS is an fundamental element of the Thinking Telescopes System, in operation at Los Alamos National Laboratory, and has been enabling great science for the past four years. The system allows a distributed network of telescopes to perform more efficiently in synchronous operation than as individual instruments. TALONS is designed as a merger between a standard server/client architecture and a Distributed Sensor Network (DSN). It can dynamically regulate its client base, allowing any number of heterogeneous resources to be linked together and communicate. TALONS couples that capability with collaborative analysis and maintenance modules so that it can respond quickly to external requests and changing network environments. TALONS clients connect via an intelligent agent, which acts in proxy for the scientist, allowing the telescope to analyze incoming information and respond autonomously. TALONS has a proven track record of effectively supporting the instruments at Los Alamos and other astronomical resources around the world.

  11. Distributed control architecture of high-speed networks

    NASA Astrophysics Data System (ADS)

    Cidon, Israel; Gopal, Inder; Kaplan, Marc A.; Kutten, Shay

    1995-05-01

    A control architecture for a high-speed packet-switched network is described. The architecture was designed and implemented as part of the PARIS (subsequently plaNET and BBNS) networking project at IBM. This high bandwidth network for integrated communication (data, voice, video) is currently operational as a laboratory prototype. It will also be deployed within the AURORA Testbed that is part of the NSF/DARPA gigabit networking program. The high bandwidth dictates the need for specialized hardware to support faster packet handling for both point-to-point and multicast connections. A faster and more efficient network control is also required in order to support the increased number of connections and their changing requirements with time. The new network control architecture presented exploits specialized hardware, thereby enabling tasks to be performed faster and with less computation overhead. In particular, since control information can be distributed quickly using hardware packet handling mechanisms, decisions can be made based upon more complete and accurate information. In some respects, this has the effect of having the benefits of centralized control (e.g., easier bandwidth resource allocation to connections), while retaining the fault tolerance and scalability of a distributed architecture.

  12. Traffic network and distribution of cars: Maximum-entropy approach

    SciTech Connect

    Das, N.C.; Chakrabarti, C.G.; Mazumder, S.K.

    2000-02-01

    An urban transport system plays a vital role in the modeling of the modern cosmopolis. A great emphasis is needed for the proper development of a transport system, particularly the traffic network and flow, to meet possible future demand. There are various mathematical models of traffic network and flow. The role of Shannon entropy in the modeling of traffic network and flow was stressed by Tomlin and Tomlin (1968) and Tomlin (1969). In the present note the authors study the role of maximum-entropy principle in the solution of an important problem associated with the traffic network flow. The maximum-entropy principle initiated by Jaynes is a powerful optimization technique of determining the distribution of a random system in the case of partial or incomplete information or data available about the system. This principle has now been broadened and extended and has found wide applications in different fields of science and technology. In the present note the authors show how the Jaynes' maximum-entropy principle, slightly modified, can be successfully applied in determining the flow or distribution of cars in different paths of a traffic network when incomplete information is available about the network.

  13. Distribution of Link Distances in a Wireless Network

    PubMed Central

    Miller, Leonard E.

    2001-01-01

    The probability distribution is found for the link distance between two randomly positioned mobile radios in a wireless network for two representative deployment scenarios: (1) the mobile locations are uniformly distributed over a rectangular area and (2) the x and y coordinates of the mobile locations have Gaussian distributions. It is shown that the shapes of the link distance distributions for these scenarios are very similar when the width of the rectangular area in the first scenario is taken to be about three times the standard deviation of the location distribution in the second scenario. Thus the choice of mobile location distribution is not critical, but can be selected for the convenience of other aspects of the analysis or simulation of the mobile system.

  14. Distributed simulation using a real-time shared memory network

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

    1993-01-01

    The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

  15. Distributed wireless quantum communication networks with partially entangled pairs

    NASA Astrophysics Data System (ADS)

    Yu, Xu-Tao; Zhang, Zai-Chen; Xu, Jin

    2014-01-01

    Wireless quantum communication networks transfer quantum state by teleportation. Existing research focuses on maximal entangled pairs. In this paper, we analyse the distributed wireless quantum communication networks with partially entangled pairs. A quantum routing scheme with multi-hop teleportation is proposed. With the proposed scheme, is not necessary for the quantum path to be consistent with the classical path. The quantum path and its associated classical path are established in a distributed way. Direct multi-hop teleportation is conducted on the selected path to transfer a quantum state from the source to the destination. Based on the feature of multi-hop teleportation using partially entangled pairs, if the node number of the quantum path is even, the destination node will add another teleportation at itself. We simulated the performance of distributed wireless quantum communication networks with a partially entangled state. The probability of transferring the quantum state successfully is statistically analyzed. Our work shows that multi-hop teleportation on distributed wireless quantum networks with partially entangled pairs is feasible.

  16. Social Networks and Performance in Distributed Learning Communities

    ERIC Educational Resources Information Center

    Cadima, Rita; Ojeda, Jordi; Monguet, Josep M.

    2012-01-01

    Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this…

  17. 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.

  18. Reliable distribution networks design with nonlinear fortification function

    NASA Astrophysics Data System (ADS)

    Li, Qingwei; Savachkin, Alex

    2016-03-01

    Distribution networks have been facing an increased exposure to the risk of unpredicted disruptions causing significant economic losses. The current literature features a limited number of studies considering fortification of network facilities. In this paper, we develop a reliable uncapacitated fixed-charge location model with fortification to support the design of distribution networks. The model considers heterogeneous facility failure probabilities, one layer of supplier backup, and facility fortification within a finite budget. Facility reliability improvement is modelled as a nonlinear function of fortification investment. The problem is formulated as a nonlinear mixed integer programming model proven to be ?-hard. A Lagrangian relaxation-based heuristic algorithm is developed and its computational efficiency for solving large-scale problems is demonstrated.

  19. On the Local-Field Distribution in Attractor Neural Networks

    NASA Astrophysics Data System (ADS)

    Korutcheva, E.; Koroutchev, K.

    In this paper a simple two-layer neural network's model, similar to that studied by D. Amit and N. Brunel,11 is investigated in the frames of the mean-field approximation. The distributions of the local fields are analytically derived and compared to those obtained in Ref. 11. The dynamic properties are discussed and the basin of attraction in some parametric space is found. A procedure for driving the system into a basin of attraction by using a regulation imposed on the network is proposed. The effect of outer stimulus is shown to have a destructive influence on the attractor, forcing the latter to disappear if the distribution of the stimulus has high enough variance or if the stimulus has a spatial structure with sufficient contrast. The techniques, used in this paper, for obtaining the analytical results can be applied to more complex topologies of linked recurrent neural networks.

  20. Fault Diagnosis in a Fully Distributed Local Computer Network.

    NASA Astrophysics Data System (ADS)

    Kwag, Hye Keun

    Local computer networks are being installed in diverse application areas. Many of the networks employ a distributed control scheme, which has advantages in performance and reliability over a centralized one. However, distribution of control increases the difficulty in locating faulty hardware elements. Consequently, advantages may not be fully realized unless measures are taken to account for the difficulties of fault diagnosis; yet, not much work has been done in this area. A hardcore is defined as a node or a part of a node which is fault-free and which can diagnose other elements in a system. Faults are diagnosed in most existing distributed local computer networks by assuming that every node, or a part of every node, is a fixed hardcore: a fixed node or a part of a fixed node is always a hardcore. Maintaining such high reliability may not be possible or cost-effective for some systems. A distributed network contains dynamically redundant elements, and it is reasonable to assume that fewer nodes are simultaneously faulty than are fault-free at any point in the life cycle of the network. A diagnostic model is proposed herein which determines bindary evaluation results according to the status of the testing and tested nodes, and which leads the network to dynamically locate a fault-free node (a hardcore). This diagnostic model is, in most cases, simpler to implement and more cost-effective than the fixed hardcore. The selected hardcore can diagnose the other elements and can locate permanent faults. In a hop-by-hop test, the destination node and every intermediate node in a path test the transmitted data. This dissertation presents another method to locate an element with frequent transient faults; it checks data only at the destination, thereby, eliminating the need for a hop-by-hop test.

  1. Distributed Detection of Wormhole Attacks in Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    de Graaf, Rennie; Hegazy, Islam; Horton, Jeffrey; Safavi-Naini, Reihaneh

    Sensors in a wireless sensor network depend on their neighbours to route their messages. Yet, routing protocols in wireless sensor network are vulnerable to different types of attacks. In this paper, we consider the wormhole attack in which the adversary diverts traffic from one part of the network to another part by introducing a low cost tunnel between the two parts. We introduce a distributed intrusion detection system that monitors the communication in the network and propose a criterion for the placement of intrusion detection nodes. The intrusion detection system searches for violations of that criterion to detect wormholes of length above a certain minimum value. We evaluate the effectiveness of our system in a simulated environment. The experiments show that our system can detect 100% of the wormholes that are beyond the communication range of the intrusion detection nodes. Finally, we discuss our results and show directions for future work.

  2. Joint physical and numerical modeling of water distribution networks.

    SciTech Connect

    Zimmerman, Adam; O'Hern, Timothy John; Orear, Leslie Jr.; Kajder, Karen C.; Webb, Stephen Walter; Cappelle, Malynda A.; Khalsa, Siri Sahib; Wright, Jerome L.; Sun, Amy Cha-Tien; Chwirka, J. Benjamin; Hartenberger, Joel David; McKenna, Sean Andrew; van Bloemen Waanders, Bart Gustaaf; McGrath, Lucas K.; Ho, Clifford Kuofei

    2009-01-01

    This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.

  3. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  4. An architecture for distributed video applications based on declarative networking

    NASA Astrophysics Data System (ADS)

    Wang, Xiping; Gonzales, Cesar; Lobo, Jorge; Calo, Seraphin; Verma, Dinesh

    2012-06-01

    Video surveillance applications are examples of complex distributed coalition tasks. Real-time capture and analysis of image sensor data is one of the most important tasks in a number of military critical decision making scenarios. In complex battlefield situations, there is a need to coordinate the operation of distributed image sensors and the analysis of their data as transmitted over a heterogeneous wireless network where bandwidth, power, and computational capabilities are constrained. There is also a need to automate decision making based on the results of the analysis of video data. Declarative Networking is a promising technology for controlling complex video surveillance applications in this sort of environment. This paper presents a flexible and extensible architecture for deploying distributed video surveillance applications using the declarative networking paradigm, which allows us to dynamically connect and manage distributed image sensors and deploy various modules for the analysis of video data to satisfy a variety of video surveillance requirements. With declarative computing, it becomes possible for us not only to express the program control structure in a declarative fashion, but also to simplify the management of distributed video surveillance applications.

  5. A distributed data base management system. [for Deep Space Network

    NASA Technical Reports Server (NTRS)

    Bryan, A. I.

    1975-01-01

    Major system design features of a distributed data management system for the NASA Deep Space Network (DSN) designed for continuous two-way deep space communications are described. The reasons for which the distributed data base utilizing third-generation minicomputers is selected as the optimum approach for the DSN are threefold: (1) with a distributed master data base, valid data is available in real-time to support DSN management activities at each location; (2) data base integrity is the responsibility of local management; and (3) the data acquisition/distribution and processing power of a third-generation computer enables the computer to function successfully as a data handler or as an on-line process controller. The concept of the distributed data base is discussed along with the software, data base integrity, and hardware used. The data analysis/update constraint is examined.

  6. Towards the distribution network of time and frequency

    NASA Astrophysics Data System (ADS)

    Lipiński, M.; Krehlik, P.; Śliwczyński, Ł.; Buczek, Ł.; Kołodziej, J.; Nawrocki, J.; Nogaś, P.; Dunst, P.; Lemański, D.; Czubla, A.; Pieczerak, J.; Adamowicz, W.; Pawszak, T.; Igalson, J.; Binczewski, A.; Bogacki, W.; Ostapowicz, P.; Stroiński, M.; Turza, K.

    2014-05-01

    In the paper the genesis, current stage and perspectives of the OPTIME project are described. The main goal of the project is to demonstrate that the newdeveloped at AGH technology of fiber optic transfer of the atomic clocks reference signals is ready to be used in building the domestic Time and Frequency distribution network. In the first part we summarize the two-year continuous operation of 420 kmlong link connecting the Laboratory of Time and Frequency at Central Office of Measures GUM in Warsaw and Time Service Laboratory at Astrogeodynamic Obserwatory AOS in Borowiec near Poznan. For the first time, we are reporting the two year comparison of UTC(PL) and UTC(AOS) atomic timescales with this link, and we refer it to the results of comparisons performed by GPS-based methods. We also address some practical aspects of maintaining time and frequency dissemination over fiber optical network. In the second part of the paper the concept of the general architecture of the distribution network with two Reference Time and Frequency Laboratories and local repositories is proposed. Moreover the brief project of the second branch connecting repositories in Poznan Polish Supercomputing and Networking Center and Torun Nicolaus Copernicus University with the first end-users in Torun such as National Laboratory of Atomic, Molecular and Optical Physics and Nicolaus Copernicus Astronomical Center is described. In the final part the perspective of developing the network both in the domestic range as far as extention with the international connections possibilities are presented.

  7. Distributed detection of communities in complex networks using synthetic coordinates

    NASA Astrophysics Data System (ADS)

    Papadakis, H.; Panagiotakis, C.; Fragopoulou, P.

    2014-03-01

    Various applications like finding Web communities, detecting the structure of social networks, and even analyzing a graph’s structure to uncover Internet attacks are just some of the applications for which community detection is important. In this paper, we propose an algorithm that finds the entire community structure of a network, on the basis of local interactions between neighboring nodes and an unsupervised distributed hierarchical clustering algorithm. The novelty of the proposed approach, named SCCD (standing for synthetic coordinate community detection), lies in the fact that the algorithm is based on the use of Vivaldi synthetic network coordinates computed by a distributed algorithm. The current paper not only presents an efficient distributed community finding algorithm, but also demonstrates that synthetic network coordinates could be used to derive efficient solutions to a variety of problems. Experimental results and comparisons with other methods from the literature are presented for a variety of benchmark graphs with known community structure, derived from varying a number of graph parameters and real data set graphs. The experimental results and comparisons to existing methods with similar computation cost on real and synthetic data sets demonstrate the high performance and robustness of the proposed scheme.

  8. Efficient server selection system for widely distributed multiserver networks

    NASA Astrophysics Data System (ADS)

    Lee, Hyun-pyo; Park, Sung-sik; Lee, Kyoon-Ha

    2001-07-01

    In order to providing more improved quality of Internet service, the access speed to a subscriber's network and a server which is the Internet access device was rapidly enhanced by traffic distribution and installation of high-performance server. But the Internet access quality and the content for a speed were remained out of satisfaction. With such a hazard, an extended node at Internet access device has a limitation for coping with growing network traffic, and the root cause is located in the Middle-mile node between a CP (Content Provider) server and a user node. For such a problem, this paper proposes a new method to select a effective server to a client as minimizing the number of node between the server and the client while keeping the load balance among servers which is clustered by the client's location on the physically distributed multi-site environments. The proposed method use a NSP (Network Status Prober) and a contents server manager so as to get a status of each servers and distributed network, a new architecture will be shown for the server selecting algorithm and the implementation for the algorithm. And also, this paper shows the parameters selecting a best service providing server for client and that the grantor will be confirmed by the experiment over the proposed architectures.

  9. Distributed networks enable advances in US space weather operations

    NASA Astrophysics Data System (ADS)

    Tobiska, W. Kent; Bouwer, S. Dave

    2011-06-01

    Space weather, the shorter-term variable impact of the Sun’s photons, solar wind particles, and interplanetary magnetic field upon the Earth’s environment, adversely affects our technological systems. These technological systems, including their space component, are increasingly being seen as a way to help solve 21st Century problems such as climate change, energy access, fresh water availability, and transportation coordination. Thus, the effects of space weather on space systems and assets must be mitigated and operational space weather using automated distributed networks has emerged as a common operations methodology. The evolution of space weather operations is described and the description of distributed network architectures is provided, including their use of tiers, data objects, redundancy, and time domain definitions. There are several existing distributed networks now providing space weather information and the lessons learned in developing those networks are discussed along with the details of examples for the Solar Irradiance Platform (SIP), Communication Alert and Prediction System (CAPS), GEO Alert and Prediction System (GAPS), LEO Alert and Prediction System (LAPS), Radiation Alert and Prediction System (RAPS), and Magnetosphere Alert and Prediction System (MAPS).

  10. Hadoop neural network for parallel and distributed feature selection.

    PubMed

    Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

    2016-06-01

    In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. PMID:26403824

  11. Distributed policy based access to networked heterogeneous ISR data sources

    NASA Astrophysics Data System (ADS)

    Bent, G.; Vyvyan, D.; Wood, David; Zerfos, Petros; Calo, Seraphin

    2010-04-01

    Within a coalition environment, ad hoc Communities of Interest (CoI's) come together, perhaps for only a short time, with different sensors, sensor platforms, data fusion elements, and networks to conduct a task (or set of tasks) with different coalition members taking different roles. In such a coalition, each organization will have its own inherent restrictions on how it will interact with the others. These are usually stated as a set of policies, including security and privacy policies. The capability that we want to enable for a coalition operation is to provide access to information from any coalition partner in conformance with the policies of all. One of the challenges in supporting such ad-hoc coalition operations is that of providing efficient access to distributed sources of data, where the applications requiring the data do not have knowledge of the location of the data within the network. To address this challenge the International Technology Alliance (ITA) program has been developing the concept of a Dynamic Distributed Federated Database (DDFD), also know as a Gaian Database. This type of database provides a means for accessing data across a network of distributed heterogeneous data sources where access to the information is controlled by a mixture of local and global policies. We describe how a network of disparate ISR elements can be expressed as a DDFD and how this approach enables sensor and other information sources to be discovered autonomously or semi-autonomously and/or combined, fused formally defined local and global policies.

  12. Physical Modeling of Scaled Water Distribution System Networks.

    SciTech Connect

    O'Hern, Timothy J.; Hammond, Glenn Edward; Orear, Leslie ,; van Bloemen Waanders, Bart G.; Paul Molina; Ross Johnson

    2005-10-01

    Threats to water distribution systems include release of contaminants and Denial of Service (DoS) attacks. A better understanding, and validated computational models, of the flow in water distribution systems would enable determination of sensor placement in real water distribution networks, allow source identification, and guide mitigation/minimization efforts. Validation data are needed to evaluate numerical models of network operations. Some data can be acquired in real-world tests, but these are limited by 1) unknown demand, 2) lack of repeatability, 3) too many sources of uncertainty (demand, friction factors, etc.), and 4) expense. In addition, real-world tests have limited numbers of network access points. A scale-model water distribution system was fabricated, and validation data were acquired over a range of flow (demand) conditions. Standard operating variables included system layout, demand at various nodes in the system, and pressure drop across various pipe sections. In addition, the location of contaminant (salt or dye) introduction was varied. Measurements of pressure, flowrate, and concentration at a large number of points, and overall visualization of dye transport through the flow network were completed. Scale-up issues that that were incorporated in the experiment design include Reynolds number, pressure drop across nodes, and pipe friction and roughness. The scale was chosen to be 20:1, so the 10 inch main was modeled with a 0.5 inch pipe in the physical model. Controlled validation tracer tests were run to provide validation to flow and transport models, especially of the degree of mixing at pipe junctions. Results of the pipe mixing experiments showed large deviations from predicted behavior and these have a large impact on standard network operations models.3

  13. A Distributed Recurrent Network Contributes to Temporally Precise Vocalizations.

    PubMed

    Hamaguchi, Kosuke; Tanaka, Masashi; Mooney, Richard

    2016-08-01

    How do forebrain and brainstem circuits interact to produce temporally precise and reproducible behaviors? Birdsong is an elaborate, temporally precise, and stereotyped vocal behavior controlled by a network of forebrain and brainstem nuclei. An influential idea is that song premotor neurons in a forebrain nucleus (HVC) form a synaptic chain that dictates song timing in a top-down manner. Here we combine physiological, dynamical, and computational methods to show that song timing is not generated solely by a mechanism localized to HVC but instead is the product of a distributed and recurrent synaptic network spanning the forebrain and brainstem, of which HVC is a component. PMID:27397518

  14. Fast Distributed Dynamics of Semantic Networks via Social Media.

    PubMed

    Carrillo, Facundo; Cecchi, Guillermo A; Sigman, Mariano; Slezak, Diego Fernández

    2015-01-01

    We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network. PMID:26074953

  15. Distributed Estimation for Vector Signal in Linear Coherent Sensor Networks

    NASA Astrophysics Data System (ADS)

    Wu, Chien-Hsien; Lin, Ching-An

    We introduce the distributed estimation of a random vector signal in wireless sensor networks that follow coherent multiple access channel model. We adopt the linear minimum mean squared error fusion rule. The problem of interest is to design linear coding matrices for those sensors in the network so as to minimize mean squared error of the estimated vector signal under a total power constraint. We show that the problem can be formulated as a convex optimization problem and we obtain closed form expressions of the coding matrices. Numerical results are used to illustrate the performance of the proposed method.

  16. Fast Distributed Dynamics of Semantic Networks via Social Media

    PubMed Central

    Carrillo, Facundo; Cecchi, Guillermo A.; Sigman, Mariano; Fernández Slezak, Diego

    2015-01-01

    We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network. PMID:26074953

  17. Efficient network meta-analysis: a confidence distribution approach*

    PubMed Central

    Yang, Guang; Liu, Dungang; Liu, Regina Y.; Xie, Minge; Hoaglin, David C.

    2014-01-01

    Summary Network meta-analysis synthesizes several studies of multiple treatment comparisons to simultaneously provide inference for all treatments in the network. It can often strengthen inference on pairwise comparisons by borrowing evidence from other comparisons in the network. Current network meta-analysis approaches are derived from either conventional pairwise meta-analysis or hierarchical Bayesian methods. This paper introduces a new approach for network meta-analysis by combining confidence distributions (CDs). Instead of combining point estimators from individual studies in the conventional approach, the new approach combines CDs which contain richer information than point estimators and thus achieves greater efficiency in its inference. The proposed CD approach can e ciently integrate all studies in the network and provide inference for all treatments even when individual studies contain only comparisons of subsets of the treatments. Through numerical studies with real and simulated data sets, the proposed approach is shown to outperform or at least equal the traditional pairwise meta-analysis and a commonly used Bayesian hierarchical model. Although the Bayesian approach may yield comparable results with a suitably chosen prior, it is highly sensitive to the choice of priors (especially the prior of the between-trial covariance structure), which is often subjective. The CD approach is a general frequentist approach and is prior-free. Moreover, it can always provide a proper inference for all the treatment effects regardless of the between-trial covariance structure. PMID:25067933

  18. A Distributed Network Mobility Management Scheme for Hierarchical Mobile IPv6 Networks

    NASA Astrophysics Data System (ADS)

    Kawano, Keita; Kinoshita, Kazuhiko; Yamai, Nariyoshi

    Route optimization for network mobility is a key technique for providing a node in a mobile network (Mobile Network Node or MNN) with high quality broadband communications. Many schemes adding route optimization function to Network Mobility (NEMO) Basic Support protocol, the standardized network mobility management protocol from the IETF nemo working group, have already been proposed in recent years. One such scheme, a scheme using Hierarchical Mobile IPv6 (HMIPv6) aims to overcome micromobility management issues as well by applying a mechanism based on HMIPv6. The traditional scheme, however, suffers from a significant number of signaling messages as the number of MNNs and/or the number of their Correspondent Nodes (CNs) increase, because many messages notifying the MNNs' Home Agents (HAMNNs) and the CNs of the mobile network's movement are generated simultaneously each time the mobile network moves to the domain of another micromobility management router (Mobility Anchor Point or MAP). This paper proposes a scheme to overcome this problem. Our scheme reduces the number of signaling messages generated at the same time by managing the mobility of MNNs using multiple MAPs distributed within a network for load sharing. The results of simulation experiments show that our scheme works efficiently compared to the traditional scheme when a mobile network has many MNNs and/or these MNNs communicate with many CNs.

  19. S-curve networks and an approximate method for estimating degree distributions of complex networks

    NASA Astrophysics Data System (ADS)

    Guo, Jin-Li

    2010-12-01

    In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

  20. A precise clock distribution network for MRPC-based experiments

    NASA Astrophysics Data System (ADS)

    Wang, S.; Cao, P.; Shang, L.; An, Q.

    2016-06-01

    In high energy physics experiments, the MRPC (Multi-Gap Resistive Plate Chamber) detectors are widely used recently which can provide higher-resolution measurement for particle identification. However, the application of MRPC detectors leads to a series of challenges in electronics design with large number of front-end electronic channels, especially for distributing clock precisely. To deal with these challenges, this paper presents a universal scheme of clock transmission network for MRPC-based experiments with advantages of both precise clock distribution and global command synchronization. For precise clock distributing, the clock network is designed into a tree architecture with two stages: the first one has a point-to-multipoint long range bidirectional distribution with optical channels and the second one has a fan-out structure with copper link inside readout crates. To guarantee the precision of clock frequency or phase, the r-PTP (reduced Precision Time Protocol) and the DDMTD (digital Dual Mixer Time Difference) methods are used for frequency synthesis, phase measurement and adjustment, which is implemented by FPGA (Field Programmable Gate Array) in real-time. In addition, to synchronize global command execution, based upon this clock distribution network, synchronous signals are coded with clock for transmission. With technique of encoding/decoding and clock data recovery, signals such as global triggers or system control commands, can be distributed to all front-end channels synchronously, which greatly simplifies the system design. The experimental results show that both the clock jitter (RMS) and the clock skew can be less than 100 ps.

  1. Mapping distributed brain function and networks with diffuse optical tomography

    PubMed Central

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-01-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson’s disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging. PMID:25083161

  2. Mapping distributed brain function and networks with diffuse optical tomography

    NASA Astrophysics Data System (ADS)

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-06-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

  3. Biometrics based novel key distribution solution for body sensor networks.

    PubMed

    Miao, Fen; Jiang, Lei; Li, Ye; Zhang, Yuan-Ting

    2009-01-01

    The security of wireless body sensor network (BSN) is very important to telemedicine and m-healthcare, and it still remains a critical challenge. This paper presents a novel key distribution solution which allows two sensors in one BSN to agree on a changeable cryptographic key. A previously published scheme, fuzzy vault, is firstly applied to secure the random cryptographic key generated from electrocardiographic (ECG) signals. Simulations based on ECG data from MIT PhysioBank database, produce a minimum half total error rate (HTER) of 0.65%, which demonstrates our key distribution solution is promising compared with previous method, with HTER of 4.26%. PMID:19964960

  4. Optimal operation of a potable water distribution network.

    PubMed

    Biscos, C; Mulholland, M; Le Lann, M V; Brouckaert, C J; Bailey, R; Roustan, M

    2002-01-01

    This paper presents an approach to an optimal operation of a potable water distribution network. The main control objective defined during the preliminary steps was to maximise the use of low-cost power, maintaining at the same time minimum emergency levels in all reservoirs. The combination of dynamic elements (e.g. reservoirs) and discrete elements (pumps, valves, routing) makes this a challenging predictive control and constrained optimisation problem, which is being solved by MINLP (Mixed Integer Non-linear Programming). Initial experimental results show the performance of this algorithm and its ability to control the water distribution process. PMID:12448464

  5. Event-triggered output feedback control for distributed networked systems.

    PubMed

    Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

    2016-01-01

    This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. PMID:26708304

  6. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center. PMID:25850092

  7. Alert Distribution Network And Public Data Of The SVOM Mission

    SciTech Connect

    Claret, A.

    2008-05-22

    SVOM (Space-based multi-band astronomical Variable Objects Monitor) has been designed to detect all known types of gamma-ray bursts (GRBs), to provide fast and reliable GRB positions, to measure the broadband spectral shape and temporal properties of the GRB prompt emission, and to quickly identify the optical afterglows, including those which are highly redshifted. In this paper, we focus on the alert distribution network and the public data which will be available to the GRB community.

  8. Application of geographic information system in distribution power network automation

    NASA Astrophysics Data System (ADS)

    Wei, Xianmin

    2011-02-01

    Geographic information system (GIS) is the computer system in support of computer software with collection, storage, management, retrieval and comprehensive analysis of a variety of geospatial information, with various forms output data and graphics products. This paper introduced GIS data organization and its main applications in distribution power network automation, including both offline and online, and proposed component-based system development model and the need to establish WEBGIS and reliability.

  9. Automatic analysis of attack data from distributed honeypot network

    NASA Astrophysics Data System (ADS)

    Safarik, Jakub; Voznak, MIroslav; Rezac, Filip; Partila, Pavol; Tomala, Karel

    2013-05-01

    There are many ways of getting real data about malicious activity in a network. One of them relies on masquerading monitoring servers as a production one. These servers are called honeypots and data about attacks on them brings us valuable information about actual attacks and techniques used by hackers. The article describes distributed topology of honeypots, which was developed with a strong orientation on monitoring of IP telephony traffic. IP telephony servers can be easily exposed to various types of attacks, and without protection, this situation can lead to loss of money and other unpleasant consequences. Using a distributed topology with honeypots placed in different geological locations and networks provides more valuable and independent results. With automatic system of gathering information from all honeypots, it is possible to work with all information on one centralized point. Communication between honeypots and centralized data store use secure SSH tunnels and server communicates only with authorized honeypots. The centralized server also automatically analyses data from each honeypot. Results of this analysis and also other statistical data about malicious activity are simply accessible through a built-in web server. All statistical and analysis reports serve as information basis for an algorithm which classifies different types of used VoIP attacks. The web interface then brings a tool for quick comparison and evaluation of actual attacks in all monitored networks. The article describes both, the honeypots nodes in distributed architecture, which monitor suspicious activity, and also methods and algorithms used on the server side for analysis of gathered data.

  10. 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. PMID:22408514

  11. Distributed communications and control network for robotic mining

    NASA Technical Reports Server (NTRS)

    Schiffbauer, William H.

    1989-01-01

    The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.

  12. 3-D target-based distributed smart camera network localization.

    PubMed

    Kassebaum, John; Bulusu, Nirupama; Feng, Wu-Chi

    2010-10-01

    For distributed smart camera networks to perform vision-based tasks such as subject recognition and tracking, every camera's position and orientation relative to a single 3-D coordinate frame must be accurately determined. In this paper, we present a new camera network localization solution that requires successively showing a 3-D feature point-rich target to all cameras, then using the known geometry of a 3-D target, cameras estimate and decompose projection matrices to compute their position and orientation relative to the coordinatization of the 3-D target's feature points. As each 3-D target position establishes a distinct coordinate frame, cameras that view more than one 3-D target position compute translations and rotations relating different positions' coordinate frames and share the transform data with neighbors to facilitate realignment of all cameras to a single coordinate frame. Compared to other localization solutions that use opportunistically found visual data, our solution is more suitable to battery-powered, processing-constrained camera networks because it requires communication only to determine simultaneous target viewings and for passing transform data. Additionally, our solution requires only pairwise view overlaps of sufficient size to see the 3-D target and detect its feature points, while also giving camera positions in meaningful units. We evaluate our algorithm in both real and simulated smart camera networks. In the real network, position error is less than 1 ('') when the 3-D target's feature points fill only 2.9% of the frame area. PMID:20679031

  13. Biological Instability in a Chlorinated Drinking Water Distribution Network

    PubMed Central

    Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

    2014-01-01

    The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×103 cells mL−1 to 4.66×105 cells mL−1 in the network. While this parameter did not exceed 2.1×104 cells mL−1 in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×105 cells mL−1. This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability. PMID:24796923

  14. Mechanical Network in Titin Immunoglobulin from Force Distribution Analysis

    PubMed Central

    Wilmanns, Matthias; Gräter, Frauke

    2009-01-01

    The role of mechanical force in cellular processes is increasingly revealed by single molecule experiments and simulations of force-induced transitions in proteins. How the applied force propagates within proteins determines their mechanical behavior yet remains largely unknown. We present a new method based on molecular dynamics simulations to disclose the distribution of strain in protein structures, here for the newly determined high-resolution crystal structure of I27, a titin immunoglobulin (IG) domain. We obtain a sparse, spatially connected, and highly anisotropic mechanical network. This allows us to detect load-bearing motifs composed of interstrand hydrogen bonds and hydrophobic core interactions, including parts distal to the site to which force was applied. The role of the force distribution pattern for mechanical stability is tested by in silico unfolding of I27 mutants. We then compare the observed force pattern to the sparse network of coevolved residues found in this family. We find a remarkable overlap, suggesting the force distribution to reflect constraints for the evolutionary design of mechanical resistance in the IG family. The force distribution analysis provides a molecular interpretation of coevolution and opens the road to the study of the mechanism of signal propagation in proteins in general. PMID:19282960

  15. Distributed fault estimation with randomly occurring uncertainties over sensor networks

    NASA Astrophysics Data System (ADS)

    Dong, Hongli; Wang, Zidong; Bu, Xianye; Alsaadi, Fuad E.

    2016-07-01

    This paper is concerned with the distributed fault estimation problem for a class of uncertain stochastic systems over sensor networks. The norm-bounded uncertainty enters into the system in a random way governed by a set of Bernoulli distributed white sequence. The purpose of the addressed problem is to design distributed fault estimators, via available output measurements from not only the individual sensor, but also its neighbouring sensors, such that the fault estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the ? performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed ? performance for the overall estimation error dynamics. Simulation results are provided to demonstrate the effectiveness of the proposed fault estimation technique in this paper.

  16. Patch Network for Power Allocation and Distribution in Smart Materials

    NASA Technical Reports Server (NTRS)

    Golembiewski, Walter T.

    2000-01-01

    The power allocation and distribution (PAD) circuitry is capable of allocating and distributing a single or multiple sources of power over multi-elements of a power user grid system. The purpose of this invention is to allocate and distribute power that is collected by individual patch rectennas to a region of specific power-user devices, such as actuators. The patch rectenna converts microwave power into DC power. Then this DC power is used to drive actuator devices. However, the power from patch rectennas is not sufficient to drive actuators unless all the collected power is effectively used to drive another group by allocation and distribution. The power allocation and distribution (PAD) circuitry solves the shortfall of power for devices in a large array. The PAD concept is based on the networked power control in which power collected over the whole array of rectennas is allocated to a sub domain where a group of devices is required to be activated for operation. Then the allocated power is distributed to individual element of power-devices in the sub domain according to a selected run-mode.

  17. DataONE: A Distributed Earth Science Data Network

    NASA Astrophysics Data System (ADS)

    Cook, R. B.; DataONE Leadership Team

    2011-12-01

    Addressing the Earth's environmental problems requires that we change the ways that we harness existing data and develop new methods to combine, analyze, and visualize diverse data resources. DataONE (Observation Network for Earth) represents a virtual organization whose goal is to enable new science and knowledge creation through universal access to data about life on Earth and the environment that sustains it. DataONE is designed to be the foundation of innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to easily discovered Earth observational data. DataONE is interdisciplinary, making disparate biological and environmental data available and engaging scientists, land-managers, policy makers, students, educators, and the public through logical access and intuitive visualizations. The foundation of DataONE is the established collaboration among participating organizations that have multi-decadal expertise in a wide range of fields that includes: existing archive initiatives, libraries, environmental observing systems and research networks, data and information management, science synthesis centers, and professional societies. Most importantly, DataONE will serve a broad range of science domains both directly and through the interoperability with the DataONE distributed network.

  18. Assessing mechanical vulnerability in water distribution networks under multiple failures

    NASA Astrophysics Data System (ADS)

    Berardi, Luigi; Ugarelli, Rita; Røstum, Jon; Giustolisi, Orazio

    2014-03-01

    Understanding mechanical vulnerability of water distribution networks (WDN) is of direct relevance for water utilities since it entails two different purposes. On the one hand, it might support the identification of severe failure scenarios due to external causes (e.g., natural or intentional events) which result into the most critical consequences on WDN supply capacity. On the other hand, it aims at figure out the WDN portions which are more prone to be affected by asset disruptions. The complexity of such analysis stems from the number of possible scenarios with single and multiple simultaneous shutdowns of asset elements leading to modifications of network topology and insufficient water supply to customers. In this work, the search for the most disruptive combinations of multiple asset failure events is formulated and solved as a multiobjective optimization problem. The higher vulnerability failure scenarios are detected as those causing the lower supplied demand due to the lower number of simultaneous failures. The automatic detection of WDN topology, subsequent to the detachments of failed elements, is combined with pressure-driven analysis. The methodology is demonstrated on a real water distribution network. Results show that, besides the failures causing the detachment of reservoirs, tanks, or pumps, there are other different topological modifications which may cause severe WDN service disruptions. Such information is of direct relevance to support planning asset enhancement works and improve the preparedness to extreme events.

  19. Distributed System Intruder Tools, Trinoo and Tribe Flood Network

    SciTech Connect

    Criscuolo, P.J.; Rathbun, T

    1999-12-21

    Trinoo and Tribe Flood Network (TFN) are new forms of denial of Service (DOS) attacks. attacks are designed to bring down a computer or network by overloading it with a large amount of network traffic using TCP, UDP, or ICMP. In the past, these attacks came from a single location and were easy to detect. Trinoo and TFN are distributed system intruder tools. These tools launch DoS attacks from multiple computer systems at a target system simultaneously. This makes the assault hard to detect and almost impossible to track to the original attacker. Because these attacks can be launched from hundreds of computers under the command of a single attacker, they are far more dangerous than any DoS attack launched from a single location. These distributed tools have only been seen on Solaris and Linux machines, but there is no reason why they could not be modified for UNIX machines. The target system can also be of any type because the attack is based on the TCP/IP architecture, not a flaw in any particular operating system (OS). CIAC considers the risks presented by these DoS tools to be high.

  20. Non-coding RNAs and complex distributed genetic networks

    NASA Astrophysics Data System (ADS)

    Zhdanov, Vladimir P.

    2011-08-01

    In eukaryotic cells, the mRNA-protein interplay can be dramatically influenced by non-coding RNAs (ncRNAs). Although this new paradigm is now widely accepted, an understanding of the effect of ncRNAs on complex genetic networks is lacking. To clarify what may happen in this case, we propose a mean-field kinetic model describing the influence of ncRNA on a complex genetic network with a distributed architecture including mutual protein-mediated regulation of many genes transcribed into mRNAs. ncRNA is considered to associate with mRNAs and inhibit their translation and/or facilitate degradation. Our results are indicative of the richness of the kinetics under consideration. The main complex features are found to be bistability and oscillations. One could expect to find kinetic chaos as well. The latter feature has however not been observed in our calculations. In addition, we illustrate the difference in the regulation of distributed networks by mRNA and ncRNA.

  1. Characterizing Loopy Biological Distribution Networks in Three Dimensions

    NASA Astrophysics Data System (ADS)

    Modes, Carl; Katifori, Eleni; Magnasco, Marcelo

    2014-03-01

    In order to develop useful predictive models for vascular or other biological distribution networks that include the effects of network architecture, development, and topology some set of tools must be chosen to characterize vasculature in a physically relevant, mathematically compact way. Few such tools are extant. To address this issue we have generalized the existing two dimensional leaf venation characterization to a fully three dimensional setting, from whence it may be brought to bear on many problems in human and mammalian vasculature, particularly where that vasculature is extremely complex, as in the organs. The new algorithm rests on the abstraction of the physical `tiling' from the two dimensional case to an effective, statistical tiling of an abstract surface that the network may be thought to sit in. Generically these abstract surfaces are richer than the flat plane and as a result there are now two families of fundamental units that may aggregate upon cutting weakest links - the plaquettes of the tiling and the longer `topological' cycles associated with the abstract surface. Upon sequential removal of these weakest links, two characterizing trees emerge that condense most of the relevant information from the full network.

  2. Energy efficient wireless sensor networks using asymmetric distributed source coding

    NASA Astrophysics Data System (ADS)

    Rao, Abhishek; Kulkarni, Murlidhar

    2013-01-01

    Wireless Sensor Networks (WSNs) are networks of sensor nodes deployed over a geographical area to perform a specific task. WSNs pose many design challenges. Energy conservation is one such design issue. In literature a wide range of solutions addressing this issue have been proposed. Generally WSNs are densely deployed. Thus the nodes with the close proximity are more likely to have the same data. Transmission of such non-aggregated data may lead to an inefficient energy management. Hence the data fusion has to be performed at the nodes so as to combine the edundant information into a single data unit. Distributed Source Coding is an efficient approach in achieving this task. In this paper an attempt has been made in modeling such a system. Various energy efficient codes were considered for the analysis. System performance in terms of energy efficiency has been made.

  3. Impact tolerance in mussel thread networks by heterogeneous material distribution

    NASA Astrophysics Data System (ADS)

    Qin, Zhao; Buehler, Markus J.

    2013-07-01

    The Mytilidae, generally known as marine mussels, are known to attach to most substrates including stone, wood, concrete and iron by using a network of byssus threads. Mussels are subjected to severe mechanical impacts caused by waves. However, how the network of byssus threads keeps the mussel attached in this challenging mechanical environment is puzzling, as the dynamical forces far exceed the measured strength of byssus threads and their attachment to the environment. Here we combine experiment and simulation, and show that the heterogeneous material distribution in byssus threads has a critical role in decreasing the effect of impact loading. We find that a combination of stiff and soft materials at an 80:20 ratio enables mussels to rapidly and effectively dissipate impact energy. Notably, this facilitates a significantly enhanced strength under dynamical loading over 900% that of the strength under static loading.

  4. Impact tolerance in mussel thread networks by heterogeneous material distribution.

    PubMed

    Qin, Zhao; Buehler, Markus J

    2013-01-01

    The Mytilidae, generally known as marine mussels, are known to attach to most substrates including stone, wood, concrete and iron by using a network of byssus threads. Mussels are subjected to severe mechanical impacts caused by waves. However, how the network of byssus threads keeps the mussel attached in this challenging mechanical environment is puzzling, as the dynamical forces far exceed the measured strength of byssus threads and their attachment to the environment. Here we combine experiment and simulation, and show that the heterogeneous material distribution in byssus threads has a critical role in decreasing the effect of impact loading. We find that a combination of stiff and soft materials at an 80:20 ratio enables mussels to rapidly and effectively dissipate impact energy. Notably, this facilitates a significantly enhanced strength under dynamical loading over 900% that of the strength under static loading. PMID:23880603

  5. The SECOQC quantum key distribution network in Vienna

    NASA Astrophysics Data System (ADS)

    Peev, M.; Pacher, C.; Alléaume, R.; Barreiro, C.; Bouda, J.; Boxleitner, W.; Debuisschert, T.; Diamanti, E.; Dianati, M.; Dynes, J. F.; Fasel, S.; Fossier, S.; Fürst, M.; Gautier, J.-D.; Gay, O.; Gisin, N.; Grangier, P.; Happe, A.; Hasani, Y.; Hentschel, M.; Hübel, H.; Humer, G.; Länger, T.; Legré, M.; Lieger, R.; Lodewyck, J.; Lorünser, T.; Lütkenhaus, N.; Marhold, A.; Matyus, T.; Maurhart, O.; Monat, L.; Nauerth, S.; Page, J.-B.; Poppe, A.; Querasser, E.; Ribordy, G.; Robyr, S.; Salvail, L.; Sharpe, A. W.; Shields, A. J.; Stucki, D.; Suda, M.; Tamas, C.; Themel, T.; Thew, R. T.; Thoma, Y.; Treiber, A.; Trinkler, P.; Tualle-Brouri, R.; Vannel, F.; Walenta, N.; Weier, H.; Weinfurter, H.; Wimberger, I.; Yuan, Z. L.; Zbinden, H.; Zeilinger, A.

    2009-07-01

    In this paper, we present the quantum key distribution (QKD) network designed and implemented by the European project SEcure COmmunication based on Quantum Cryptography (SECOQC) (2004-2008), unifying the efforts of 41 research and industrial organizations. The paper summarizes the SECOQC approach to QKD networks with a focus on the trusted repeater paradigm. It discusses the architecture and functionality of the SECOQC trusted repeater prototype, which has been put into operation in Vienna in 2008 and publicly demonstrated in the framework of a SECOQC QKD conference held from October 8 to 10, 2008. The demonstration involved one-time pad encrypted telephone communication, a secure (AES encryption protected) video-conference with all deployed nodes and a number of rerouting experiments, highlighting basic mechanisms of the SECOQC network functionality. The paper gives an overview of the eight point-to-point network links in the prototype and their underlying technology: three plug and play systems by id Quantique, a one way weak pulse system from Toshiba Research in the UK, a coherent one-way system by GAP Optique with the participation of id Quantique and the AIT Austrian Institute of Technology (formerly ARCAustrian Research Centers GmbH—ARC is now operating under the new name AIT Austrian Institute of Technology GmbH following a restructuring initiative.), an entangled photons system by the University of Vienna and the AIT, a continuous-variables system by Centre National de la Recherche Scientifique (CNRS) and THALES Research and Technology with the participation of Université Libre de Bruxelles, and a free space link by the Ludwig Maximillians University in Munich connecting two nodes situated in adjacent buildings (line of sight 80 m). The average link length is between 20 and 30 km, the longest link being 83 km. The paper presents the architecture and functionality of the principal networking agent—the SECOQC node module, which enables the authentic

  6. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  7. Degree distribution and assortativity in line graphs of complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Xiangrong; Trajanovski, Stojan; Kooij, Robert E.; Van Mieghem, Piet

    2016-03-01

    Topological characteristics of links of complex networks influence the dynamical processes executed on networks triggered by links, such as cascading failures triggered by links in power grids and epidemic spread due to link infection. The line graph transforms links in the original graph into nodes. In this paper, we investigate how graph metrics in the original graph are mapped into those for its line graph. In particular, we study the degree distribution and the assortativity of a graph and its line graph. Specifically, we show, both analytically and numerically, the degree distribution of the line graph of an Erdős-Rényi graph follows the same distribution as its original graph. We derive a formula for the assortativity of line graphs and indicate that the assortativity of a line graph is not linearly related to its original graph. Additionally, line graphs of various graphs, e.g. Erdős-Rényi graphs, scale-free graphs, show positive assortativity. In contrast, we find certain types of trees and non-trees whose line graphs have negative assortativity.

  8. A Rawlsian approach to distribute responsibilities in networks.

    PubMed

    Doorn, Neelke

    2010-06-01

    Due to their non-hierarchical structure, socio-technical networks are prone to the occurrence of the problem of many hands. In the present paper an approach is introduced in which people's opinions on responsibility are empirically traced. The approach is based on the Rawlsian concept of Wide Reflective Equilibrium (WRE) in which people's considered judgments on a case are reflectively weighed against moral principles and background theories, ideally leading to a state of equilibrium. Application of the method to a hypothetical case with an artificially constructed network showed that it is possible to uncover the relevant data to assess a consensus amongst people in terms of their individual WRE. It appeared that the moral background theories people endorse are not predictive for their actual distribution of responsibilities but that they indicate ways of reasoning and justifying outcomes. Two ways of ascribing responsibilities were discerned, corresponding to two requirements of a desirable responsibility distribution: fairness and completeness. Applying the method triggered learning effects, both with regard to conceptual clarification and moral considerations, and in the sense that it led to some convergence of opinions. It is recommended to apply the method to a real engineering case in order to see whether this approach leads to an overlapping consensus on a responsibility distribution which is justifiable to all and in which no responsibilities are left unfulfilled, therewith trying to contribute to the solution of the problem of many hands. PMID:19626463

  9. Logical Graphics Design Technique for Drawing Distribution Networks

    NASA Astrophysics Data System (ADS)

    Al-A`Ali, Mansoor

    Electricity distribution networks normally consist of tens of primary feeders, thousands of substations and switching stations spread over large geographical areas and thus require a complex system in order to manage them properly from within the distribution control centre. We show techniques for using Delphi Object Oriented components to automatically generate, display and manage graphically and logically the circuits of the network. The graphics components are dynamically interactive and thus the system allows switching operations as well as displays. The object oriented approach was developed to replace an older system, which used Microstation with MDL as the programming language and ORACLE as the DBMS. Before this, the circuits could only be displayed schematically, which has many inherent problems in speed and readability of large displays. Schematic graphics displays were cumbersome when adding or deleting stations; this problem is now resolved using our approach by logically generating the graphics from the database connectivity information. This paper demonstrates the method of designing these Object Oriented components and how they can be used in specially created algorithms to generate the necessary interactive graphics. Four different logical display algorithms were created and in this study we present samples of the four different outputs of these algorithms which prove that distribution engineers can work with logical display of the circuits which are aimed to speed up the switching operations and for better clarity of the display.

  10. A Rawlsian Approach to Distribute Responsibilities in Networks

    PubMed Central

    2009-01-01

    Due to their non-hierarchical structure, socio-technical networks are prone to the occurrence of the problem of many hands. In the present paper an approach is introduced in which people’s opinions on responsibility are empirically traced. The approach is based on the Rawlsian concept of Wide Reflective Equilibrium (WRE) in which people’s considered judgments on a case are reflectively weighed against moral principles and background theories, ideally leading to a state of equilibrium. Application of the method to a hypothetical case with an artificially constructed network showed that it is possible to uncover the relevant data to assess a consensus amongst people in terms of their individual WRE. It appeared that the moral background theories people endorse are not predictive for their actual distribution of responsibilities but that they indicate ways of reasoning and justifying outcomes. Two ways of ascribing responsibilities were discerned, corresponding to two requirements of a desirable responsibility distribution: fairness and completeness. Applying the method triggered learning effects, both with regard to conceptual clarification and moral considerations, and in the sense that it led to some convergence of opinions. It is recommended to apply the method to a real engineering case in order to see whether this approach leads to an overlapping consensus on a responsibility distribution which is justifiable to all and in which no responsibilities are left unfulfilled, therewith trying to contribute to the solution of the problem of many hands. PMID:19626463

  11. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

    PubMed

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

  12. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

    PubMed Central

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

  13. Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

    USGS Publications Warehouse

    Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Doug

    2004-01-01

    Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

  14. Censored Distributed Space-Time Coding for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Yiu, S.; Schober, R.

    2007-12-01

    We consider the application of distributed space-time coding in wireless sensor networks (WSNs). In particular, sensors use a common noncoherent distributed space-time block code (DSTBC) to forward their local decisions to the fusion center (FC) which makes the final decision. We show that the performance of distributed space-time coding is negatively affected by erroneous sensor decisions caused by observation noise. To overcome this problem of error propagation, we introduce censored distributed space-time coding where only reliable decisions are forwarded to the FC. The optimum noncoherent maximum-likelihood and a low-complexity, suboptimum generalized likelihood ratio test (GLRT) FC decision rules are derived and the performance of the GLRT decision rule is analyzed. Based on this performance analysis we derive a gradient algorithm for optimization of the local decision/censoring threshold. Numerical and simulation results show the effectiveness of the proposed censoring scheme making distributed space-time coding a prime candidate for signaling in WSNs.

  15. Time Synchronization and Distribution Mechanisms for Space Networks

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Gao, Jay L.; Clare, Loren P.; Mills, David L.

    2011-01-01

    This work discusses research on the problems of synchronizing and distributing time information between spacecraft based on the Network Time Protocol (NTP), where NTP is a standard time synchronization protocol widely used in the terrestrial network. The Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol was designed and developed for synchronizing spacecraft that are in proximity where proximity is less than 100,000 km distant. A particular application is synchronization between a Mars orbiter and rover. Lunar scenarios as well as outer-planet deep space mother-ship-probe missions may also apply. Spacecraft with more accurate time information functions as a time-server, and the other spacecraft functions as a time-client. PITS can be easily integrated and adaptable to the CCSDS Proximity-1 Space Link Protocol with minor modifications. In particular, PITS can take advantage of the timestamping strategy that underlying link layer functionality provides for accurate time offset calculation. The PITS algorithm achieves time synchronization with eight consecutive space network time packet exchanges between two spacecraft. PITS can detect and avoid possible errors from receiving duplicate and out-of-order packets by comparing with the current state variables and timestamps. Further, PITS is able to detect error events and autonomously recover from unexpected events that can possibly occur during the time synchronization and distribution process. This capability achieves an additional level of protocol protection on top of CRC or Error Correction Codes. PITS is a lightweight and efficient protocol, eliminating the needs for explicit frame sequence number and long buffer storage. The PITS protocol is capable of providing time synchronization and distribution services for a more general domain where multiple entities need to achieve time synchronization using a single point-to-point link.

  16. Distributed cluster management techniques for unattended ground sensor networks

    NASA Astrophysics Data System (ADS)

    Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

    2005-05-01

    Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also

  17. Distributed high-precision time transfer through passive optical networks

    NASA Astrophysics Data System (ADS)

    Wu, Guiling; Hu, Liang; Zhang, Hao; Chen, Jianping

    2014-09-01

    We propose a one-point to multipoint distributed time transfer through passive optical networks using a time division multiple access (TDMA) based two-way time transfer. The clock at each clock user node is, in turn, compared with the high-precision reference clock at a master node by a two-way time transfer during assigned subperiods. The corresponding TDMA control protocol and time transfer units for the proposed scheme are designed and implemented. A 1×8 experimental system with a 20 km single-mode fiber in each subpath is demonstrated. The results show that a standard deviation of <60 ps can be reached in each comparison subperiod.

  18. Distributed virtual worlds in high-speed networks

    NASA Astrophysics Data System (ADS)

    Schiffner, Norbert

    1998-09-01

    Recent research efforts have concentrated on determining how the distributed workplace can be transformed into a shared virtual environment. Interaction among people and process virtual worlds has to be provided and improved. To enhance the usability of our virtual collaborative environment we integrated a multicast communication environment. With the availability of global information highways, 3D graphical intercontinental collaboration will become a part of our daily work routine. This paper describes the basics of our network infrastructure and the multicast support. As a proof of concept, a virtual world scenario is also presented in this paper.

  19. Optimal Voltage Regulation for Unbalanced Distribution Networks Considering Distributed Energy Resources

    SciTech Connect

    Liu, Guodong; Ceylan, Oguzhan; Xu, Yan; Tomsovic, Kevin

    2015-01-01

    With increasing penetration of distributed generation in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative quadratic constrained quadratic programming model to minimize voltage deviations and maximize distributed energy resource (DER) active power output in a three phase unbalanced distribution system is developed. The optimization model is based on the linearized sensitivity coefficients between controlled variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DERs). To avoid the oscillation of solution when it is close to the optimum, a golden search method is introduced to control the step size. Numerical simulations on modified IEEE 13 nodes test feeders show the efficiency of the proposed model. Compared to the results solved by heuristic search (harmony algorithm), the proposed model converges quickly to the global optimum.

  20. Distributed estimation for adaptive sensor selection in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

    2014-05-01

    Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

  1. Distributed Observer Network (DON), Version 3.0, User's Guide

    NASA Technical Reports Server (NTRS)

    Mazzone, Rebecca A.; Conroy, Michael P.

    2015-01-01

    The Distributed Observer Network (DON) is a data presentation tool developed by the National Aeronautics and Space Administration (NASA) to distribute and publish simulation results. Leveraging the display capabilities inherent in modern gaming technology, DON places users in a fully navigable 3-D environment containing graphical models and allows the users to observe how those models evolve and interact over time in a given scenario. Each scenario is driven with data that has been generated by authoritative NASA simulation tools and exported in accordance with a published data interface specification. This decoupling of the data from the source tool enables DON to faithfully display a simulator's results and ensure that every simulation stakeholder will view the exact same information every time.

  2. ESIM_DSN Web-Enabled Distributed Simulation Network

    NASA Technical Reports Server (NTRS)

    Bedrossian, Nazareth; Novotny, John

    2002-01-01

    In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

  3. Simulating the Household Plug-in Hybrid Electric Vehicle Distribution and its Electric Distribution Network Impacts

    SciTech Connect

    Cui, Xiaohui; Kim, Hoe Kyoung; Liu, Cheng; Kao, Shih-Chieh; Bhaduri, Budhendra L

    2012-01-01

    This paper presents a multi agent-based simulation framework for modeling spatial distribution of plug-in hybrid electric vehicle ownership at local residential level, discovering plug-in hybrid electric vehicle hot zones where ownership may quickly increase in the near future, and estimating the impacts of the increasing plug-in hybrid electric vehicle ownership on the local electric distribution network with different charging strategies. We use Knox County, Tennessee as a case study to highlight the simulation results of the agent-based simulation framework.

  4. A Distributed Support Vector Machine Learning Over Wireless Sensor Networks.

    PubMed

    Kim, Woojin; Stanković, Milos S; Johansson, Karl H; Kim, H Jin

    2015-11-01

    This paper is about fully-distributed support vector machine (SVM) learning over wireless sensor networks. With the concept of the geometric SVM, we propose to gossip the set of extreme points of the convex hull of local data set with neighboring nodes. It has the advantages of a simple communication mechanism and finite-time convergence to a common global solution. Furthermore, we analyze the scalability with respect to the amount of exchanged information and convergence time, with a specific emphasis on the small-world phenomenon. First, with the proposed naive convex hull algorithm, the message length remains bounded as the number of nodes increases. Second, by utilizing a small-world network, we have an opportunity to drastically improve the convergence performance with only a small increase in power consumption. These properties offer a great advantage when dealing with a large-scale network. Simulation and experimental results support the feasibility and effectiveness of the proposed gossip-based process and the analysis. PMID:26470063

  5. Moving target tracking through distributed clustering in directional sensor networks.

    PubMed

    Enayet, Asma; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

    2014-01-01

    The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works. PMID:25529205

  6. Distributed user-centric scheduling for visible light communication networks.

    PubMed

    Chen, Lingjiao; Wang, Jiaheng; Zhou, Jiantao; Ng, Derrick Wing Kwan; Schober, Robert; Zhao, Chunming

    2016-07-11

    Visible light communication (VLC) networks, consisting of multiple light-emitting diodes (LEDs) acting as optical access points (APs), can provide low-cost high-rate data transmission to multiple users simultaneously in indoor environments. However, the performance of VLC networks is severely limited by the interference between different users. In this paper, we establish a distributed user-centric scheduling framework based on stable marriage theory, and propose a novel decentralized scheduling method to manage interference by forming flexible amorphous cells for all users. The proposed scheduling method has provable low computational complexity and requires only the exchange of a few 1-bit messages between the APs and the users but not the feedback of the channel state information of the entire network. We further show that the proposed method can achieve both user-wise and system-wise optimality as well as a certain level of fairness. Simulation results indicate that our decentralized user-centric scheduling method outperforms existing centralized approaches in terms of throughput, fairness, and computational complexity. PMID:27410830

  7. Real-time hierarchically distributed processing network interaction simulation

    NASA Technical Reports Server (NTRS)

    Zimmerman, W. F.; Wu, C.

    1987-01-01

    The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

  8. Gestalt-based integrity of distributed networked systems

    NASA Astrophysics Data System (ADS)

    Sapaty, Peter

    2009-09-01

    The project aims at obtaining high integrity and goal orientation of distributed dynamic systems, which may include multiple wireless sensors and mobile robots, as well as humans. The technology developed is based on the ideology of gestalt, where the whole is considered first, dominating over parts and dynamically defining their role and even existence in the context of changing goals and states of environment. Spatial mission scenarios, which may be created on the fly, are represented in a compact non-agents form collectively executed by the intelligent network of interpreters embedded into sensitive points of the system to be managed. The approach allows us to provide effective asymmetric runtime solutions to complex asymmetric problems and fulfill objectives in unpredictable environments, paving the way to massive robotization of advanced civil and military systems. The paper covers a broad spectrum of topics from philosophy and ideology to system management, to novel distributed control technology and its implementation, and to a variety of important applications. The paradigm described may be considered as the first implementation of the idea of gestalt to management of open distributed systems, as well as the first globally programmable universal super-machine dynamically covering distributed worlds and operating with both information and matter without any central resources.

  9. Online Monitor Framework for Network Distributed Data Acquisition Systems

    NASA Astrophysics Data System (ADS)

    Konno, Tomoyuki; Cabrera, Anatael; Ishitsuka, Masaki; Kuze, Masahiro; Sakamoto, Yasunobu; the Double Chooz Collaboration

    Data acquisition (DAQ) systems for recent high energy physics experiments consist of lots of subsystems distributed in the local area network. Therefore, scalability for the number of connections from subsystems and availability of access via the Internet are required. "Online monitor framework" is a general software framework for online data monitoring, which provides a way to collect monitoring information distributed in the network and pass them though the firewalls. The framework consists of two subsystems; "Monitor Sever" and "Monitor Viewer". Monitor Server is a core system of the framework. The server collects monitoring information from the DAQ subsystems to provide them to Monitor Viewer. Monitor Viewer is a graphical user interface of the monitor framework, which displays plots in itself. We adapted two types of technologies; Java and HTML5 with Google Web Toolkit, which are independent of operating systems or plugin-libraries like ROOT and contain some functionalities of communicating via the Internet and drawing graphics. The monitoring framework was developed for the Double Chooz reactor neutrino oscillation experiment but is general enough for other experiments. This document reports the structure of the online monitor framework with some examples from the adaption to the Double Chooz experiment.

  10. Radiation detection and situation management by distributed sensor networks

    SciTech Connect

    Jan, Frigo; Mielke, Angela; Cai, D Michael

    2009-01-01

    Detection of radioactive materials in an urban environment usually requires large, portal-monitor-style radiation detectors. However, this may not be a practical solution in many transport scenarios. Alternatively, a distributed sensor network (DSN) could complement portal-style detection of radiological materials through the implementation of arrays of low cost, small heterogeneous sensors with the ability to detect the presence of radioactive materials in a moving vehicle over a specific region. In this paper, we report on the use of a heterogeneous, wireless, distributed sensor network for traffic monitoring in a field demonstration. Through wireless communications, the energy spectra from different radiation detectors are combined to improve the detection confidence. In addition, the DSN exploits other sensor technologies and algorithms to provide additional information about the vehicle, such as its speed, location, class (e.g. car, truck), and license plate number. The sensors are in-situ and data is processed in real-time at each node. Relevant information from each node is sent to a base station computer which is used to assess the movement of radioactive materials.

  11. Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network

    PubMed Central

    Schilling, Lisa M.; Kwan, Bethany M.; Drolshagen, Charles T.; Hosokawa, Patrick W.; Brandt, Elias; Pace, Wilson D.; Uhrich, Christopher; Kamerick, Michael; Bunting, Aidan; Payne, Philip R.O.; Stephens, William E.; George, Joseph M.; Vance, Mark; Giacomini, Kelli; Braddy, Jason; Green, Mika K.; Kahn, Michael G.

    2013-01-01

    Introduction: Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA. Methods: The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets. Discussion: SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions. PMID:25848567

  12. 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

  13. 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. PMID:25992913

  14. 75 FR 9343 - Nomenclature Change Relating to the Network Distribution Center Transition

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-02

    ... 111 and 121 Nomenclature Change Relating to the Network Distribution Center Transition AGENCY: Postal... to the ongoing transition of USPS bulk mail centers (BMC) to network distribution centers (NDC), by... Gambhir at 202-268-6256. SUPPLEMENTARY INFORMATION: Background: The BMC network was established in...

  15. Distributed Regional Aerosol Gridded Observation Network (DRAGON) - Korea 2012 campaign

    NASA Astrophysics Data System (ADS)

    Kim, J.; Holben, B. N.; Eck, T. F.; Jeong, U.; Kim, W. V.; Choi, M.; Kim, D. S.; Kim, B.; Kim, S.; Ghim, Y.; Kim, Y. J.; Kim, J. H.; Park, R.; Seo, M.; Song, C.; Yum, S.; Woo, J.; Yoon, S.; Lee, K.; Lee, M.; Lim, J.; Chang, I.; Jeong, M. J.; Bae, M.; Sorokin, M.; Giles, D. M.; Schafer, J.; Herman, J. R.

    2013-12-01

    One of the main objectives of Distributed Regional Aerosol Gridded Observation Network (DRAGON) campaign in Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission is to understand the relationship between the column optical properties of the atmosphere and the surface level air quality in terms of aerosols and gases. Recently, with the cooperative efforts with NASA (National Aeronautics and Space Administration) / GSFC (Goddard Space Flight Center), Korean University research groups, and KME (Korea Ministry of Environment) / NIER (National Institute of Environmental Research), DRAGON-Korea 2012 campaign was successfully performed from March to May 2012. The campaign sites were divided into two groups, the National scale sites and Seoul metropolitan sites. Thirteen Cimel sunphotometers were distributed at National scale sites including two metropolitan cities and several remote sites. Nine Cimel sunphotometers were distributed at Seoul Metropolitan sites including several residential sites and traffic source areas. The measured datasets are being analyzed in diverse fields of air quality communities including in-situ measurement groups, satellite remote sensing groups, chemical modeling groups, and airplane measurement groups. We will introduce several preliminary results of the analysis and discuss the future planes and corporations in Korea.

  16. Analysis of hailstone size distributions from a hailpad network

    NASA Astrophysics Data System (ADS)

    Fraile, R.; Castro, A.; Sánchez, J. L.

    In the province of León, a network of 250 hailpads has been installed in an area of 1000 km 2. After the individual calibration of every plate, the dents are measured by a manual method which stores data in files that can be analyzed by computer. Once the hailstones are classified according to their size, difficulties may arise when fitting linearly this distribution to a function of the type log N = log N0- βx, where N is the number of hailstones in the size class x. A discussion is presented on the universal validity of parameters N0 and β, on the problem of empty classes (to which it is impossible to apply logarithms), and on the discrimination of the smallest hail classes when making such a fitting. In conclusion, statistical methods are proposed for fitting the exponential or gamma distribution. The latter of these distributions assumes the former as a particular case and offers a better fit to the experimental data.

  17. Collaborative Distributed Scheduling Approaches for Wireless Sensor Network

    PubMed Central

    Niu, Jianjun; Deng, Zhidong

    2009-01-01

    Energy constraints restrict the lifetime of wireless sensor networks (WSNs) with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs) based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes' energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs. PMID:22408491

  18. Distributed and decentralized state estimation in gas networks as distributed parameter systems.

    PubMed

    Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry

    2015-09-01

    In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline networks. In the construction of local models, due to the existence of common states and interconnections among the subsystems, the assimilation and prediction steps of the Kalman filter are modified to take the overlapping and external states into account. However, dynamic Riccati equation for each subsystem is constructed based on the local model, which introduces a maximum error of 5% in the estimated standard deviation of the states in the benchmarks studied in this paper. The performance of the proposed methodology has been shown based on the comparison of its accuracy and computational demands against their counterparts in centralized Kalman filter for two viable benchmarks. In a real life network, it is shown that while the accuracy is not significantly decreased, the real-time factor of the state estimation is increased by a factor of 10. PMID:26138354

  19. Multi-scale modularity and motif distributional effect in metabolic networks.

    PubMed

    Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

    2016-01-01

    Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks. PMID:26412791

  20. 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

  1. Distributed efficient similarity search mechanism in wireless sensor networks.

    PubMed

    Ahmed, Khandakar; Gregory, Mark A

    2015-01-01

    The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes lack optimization for similarity queries of events. In this paper, a DCS scheme with metric based similarity searching (DCSMSS) is proposed. DCSMSS takes motivation from vector distance index, called iDistance, in order to transform the issue of similarity searching into the problem of an interval search in one dimension. In addition, a sector based distance routing algorithm is used to efficiently route messages. Extensive simulation results reveal that DCSMSS is highly efficient and significantly outperforms previous approaches in processing similarity search queries. PMID:25751081

  2. Water losses dynamic modelling in water distribution networks

    NASA Astrophysics Data System (ADS)

    Puleo, Valeria; Milici, Barbara

    2015-12-01

    In the last decades, one of the main concerns of the water system managers have been the minimisation of water losses, that frequently reach values of 30% or even 70% of the volume supplying the water distribution network. The economic and social costs associated with water losses in modern water supply systems are rapidly rising to unacceptably high levels. Furthermore, the problem of the water losses assumes more and more importance mainly when periods of water scarcity occur or when not sufficient water supply takes part in areas with fast growth. In the present analysis, a dynamic model was used for estimating real and apparent losses of a real case study. A specific nodal demand model reflecting the user's tank installation and a specific apparent losses module were implemented. The results from the dynamic model were compared with the modelling estimation based on a steady-state approach.

  3. Distributed Efficient Similarity Search Mechanism in Wireless Sensor Networks

    PubMed Central

    Ahmed, Khandakar; Gregory, Mark A.

    2015-01-01

    The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes lack optimization for similarity queries of events. In this paper, a DCS scheme with metric based similarity searching (DCSMSS) is proposed. DCSMSS takes motivation from vector distance index, called iDistance, in order to transform the issue of similarity searching into the problem of an interval search in one dimension. In addition, a sector based distance routing algorithm is used to efficiently route messages. Extensive simulation results reveal that DCSMSS is highly efficient and significantly outperforms previous approaches in processing similarity search queries. PMID:25751081

  4. High speed network issues in a distributed visualization application

    NASA Technical Reports Server (NTRS)

    Krystynak, John

    1992-01-01

    The author examines the issues in creating an UltraNet TCP/IP socket-based distributed application. The visualization computation is performed on a Connection Machine, and the results are rendered using a Silicon Graphics 4D/320 VGX workstation. The UltraNet network facilitates high-bandwidth communication between the computers. Ideally, taking advantage of the UltraNet is no more complex than developing TCP/IP and UNIX BSD socket-type applications on a single machine. In practice, there are several problems in developing an application using the UltraNet. The author identifies potential problems and discusses techniques for overcoming them. The performance of UltraNet communication is measured and found to be 10 MB/s for SGI 4D/320 workstations.

  5. Classification of moving targets by a distributed sensor network

    NASA Astrophysics Data System (ADS)

    Khatri, Hiralal C.; Kirose, Getachew; Ranney, Kenneth; Innocenti, Roberto

    2004-09-01

    We present a procedure for classification of targets by a network of distributed radar sensors deployed to detect, locate and track moving targets. Estimated sensor positions and selected positions of a target under track are used to obtain the target aspect angle as seen by the sensors. This data is used to create a multi-angle profile of the target. Stored target templates are then matched in the least mean square sense with the target profile. These templates were generated from radar return signals collected from selected targets on a turntable. Probabilities of correct classification obtained by a simulation of the classification procedure are given as functions of signal-to-noise ratios and errors in estimates of target and sensor locations.

  6. A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

    PubMed Central

    Cho, Eung Jun; Hong, Choong Seon; Lee, Sungwon; Jeon, Seokhee

    2013-01-01

    The increasing use of wireless sensor networks, which normally comprise several very small sensor nodes, makes their security an increasingly important issue. They can be practically and efficiently secured using intrusion detection systems. Conventional security mechanisms are not usually applicable due to the sensor nodes having limitations of computational power, memory capacity, and battery power. Therefore, specific security systems should be designed to function under constraints of energy or memory. A partially distributed intrusion detection system with low memory and power demands is proposed here. It employs a Bloom filter, which allows reduced signature code size. Multiple Bloom filters can be combined to reduce the signature code for each Bloom filter array. The mechanism could then cope with potential denial of service attacks, unlike many previous detection systems with Bloom filters. The mechanism was evaluated and validated through analysis and simulation.

  7. Distributed Prognostics and Health Management with a Wireless Network Architecture

    NASA Technical Reports Server (NTRS)

    Goebel, Kai; Saha, Sankalita; Sha, Bhaskar

    2013-01-01

    A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the

  8. Intercomparison exercise within a distributed-dosimetry network.

    PubMed

    Romanyukha, A; Voss, S P; Benevides, L A

    2011-03-01

    The results of an intercomparison exercise within the US Navy dosimetric network (USN-DN) are presented and discussed. The USN-DN uses a commercially available LiF:Mg,Cu,P thermoluminescent dosemeter (TLD) model Harshaw 8840/8841 and TLD reader model Harshaw 8800 manufactured by Thermo Fisher Scientific. The USN-DN consists of a single calibration facility and 16 satellite dosimetry reading facilities throughout the world with ∼ 40 model 8800 TLD readers and in excess of 350 000 TLD cards in circulation. The Naval Dosimetry Center (NDC) is the primary calibration site responsible for the distribution and calibration of all TLD cards and their associated holders. In turn, each satellite facility is assigned a subpopulation of cards, which are utilised for servicing their local customers. Consistency of the NDC calibration of 150 dosemeters (calibrated at NDC) and 27 locally calibrated remote readers was evaluated in the framework of this intercomparison. Accuracy of TLDs' calibration, performed at the NDC, was found to be <3 % throughout the entire network. Accuracy of the readers' calibration, performed with the NDC issued calibration dosemeters at remote sites, was found to be better than 4 % for most readers. The worst performance was found for reader Channel 3, which is calibrated using the thinnest chip of the Harshaw 8840/8841 dosemeter. The loss of sensitivity of this chip may be caused by time-temperature profile that has been designed for all four chips without consideration of chip thickness. PMID:21088021

  9. Distributed Sensible Heat Flux Measurements for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Huwald, H.; Brauchli, T.; Lehning, M.; Higgins, C. W.

    2015-12-01

    The sensible heat flux component of the surface energy balance is typically computed using eddy covariance or two point profile measurements while alternative approaches such as the flux variance method based on convective scaling has been much less explored and applied. Flux variance (FV) certainly has a few limitations and constraints but may be an interesting and competitive method in low-cost and power limited wireless sensor networks (WSN) with the advantage of providing spatio-temporal sensible heat flux over the domain of the network. In a first step, parameters such as sampling frequency, sensor response time, and averaging interval are investigated. Then we explore the applicability and the potential of the FV method for use in WSN in a field experiment. Low-cost sensor systems are tested and compared against reference instruments (3D sonic anemometers) to evaluate the performance and limitations of the sensors as well as the method with respect to the standard calculations. Comparison experiments were carried out at several sites to gauge the flux measurements over different surface types (gravel, grass, water) from the low-cost systems. This study should also serve as an example of spatially distributed sensible heat flux measurements.

  10. Hierarchical Data Distribution Scheme for Peer-to-Peer Networks

    NASA Astrophysics Data System (ADS)

    Bhushan, Shashi; Dave, M.; Patel, R. B.

    2010-11-01

    In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.

  11. Voltage Control of Distribution Network with a Large Penetration of Photovoltaic Generations using FACTS Devices

    NASA Astrophysics Data System (ADS)

    Kondo, Taro; Baba, Jumpei; Yokoyama, Akihiko

    In recent years, there is a great deal of interest in distributed generations from viewpoints of environmental problem and energy saving measure. Thus, a lot of distributed generators will be connected to the distribution network in the future. However, increase of distributed generators, which convert natural energy into electric energy, is concerned on their adverse effects on distribution network. Therefore, control of distribution networks using Flexible AC Transmission System (FACTS) devices is considered in order to adjust the voltage profile, and as a result more distributed generations can be installed into the networks. In this paper, four types of FACTS devices, Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC), Unified Power Flow Controller (UPFC) and self-commutated Back-To-Back converter (BTB), are analyzed by comparison of required minimum capacity of the inverters in a residential distribution network with a large penetration of photovoltaic generations.

  12. A New Linearization Method of Unbalanced Electrical Distribution Networks

    SciTech Connect

    Liu, Guodong; Xu, Yan; Ceylan, Oguzhan; Tomsovic, Kevin

    2014-01-01

    Abstract--- With increasing penetration of distributed generation in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. As DN control and operation strategies are mostly based on the linearized sensitivity coefficients between controlled variables (e.g., node voltages, line currents, power loss) and control variables (e.g., power injections, transformer tap positions), efficient and precise calculation of these sensitivity coefficients, i.e. linearization of DN, is of fundamental importance. In this paper, the derivation of the node voltages and power loss as functions of the nodal power injections and transformers' tap-changers positions is presented, and then solved by a Gauss-Seidel method. Compared to other approaches presented in the literature, the proposed method takes into account different load characteristics (e.g., constant PQ, constant impedance, constant current and any combination of above) of a generic multi-phase unbalanced DN and improves the accuracy of linearization. Numerical simulations on both IEEE 13 and 34 nodes test feeders show the efficiency and accuracy of the proposed method.

  13. Structure Learning and Statistical Estimation in Distribution Networks - Part I

    SciTech Connect

    Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

    2015-02-13

    Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and management, and improved load-monitoring. In this two part paper, inspired by proliferation of the metering technology, we discuss estimation problems in structurally loopy but operationally radial distribution grids from measurements, e.g. voltage data, which are either already available or can be made available with a relatively minor investment. In Part I, the objective is to learn the operational layout of the grid. Part II of this paper presents algorithms that estimate load statistics or line parameters in addition to learning the grid structure. Further, Part II discusses the problem of structure estimation for systems with incomplete measurement sets. Our newly suggested algorithms apply to a wide range of realistic scenarios. The algorithms are also computationally efficient – polynomial in time– which is proven theoretically and illustrated computationally on a number of test cases. The technique developed can be applied to detect line failures in real time as well as to understand the scope of possible adversarial attacks on the grid.

  14. Distributed visual-target-surveillance system in wireless sensor networks.

    PubMed

    Wang, Xue; Wang, Sheng; Bi, Daowei

    2009-10-01

    A wireless sensor network (WSN) is a powerful unattended distributed measurement system, which is widely used in target surveillance because of its outstanding performance in distributed sensing and signal processing. This paper introduces a multiview visual-target-surveillance system in WSN, which can autonomously implement target classification and tracking with collaborative online learning and localization. The proposed system is a hybrid system of single-node and multinode fusion. It is constructed on a peer-to-peer (P2P)-based computing paradigm and consists of some simple but feasible methods for target detection and feature extraction. Importantly, a support-vector-machine-based semisupervised learning method is used to achieve online classifier learning with only unlabeled samples. To reduce the energy consumption and increase the accuracy, a novel progressive data-fusion paradigm is proposed for online learning and localization, where a feasible routing method is adopted to implement information transmission with the tradeoff between performance and cost. Experiment results verify that the proposed surveillance system is an effective, energy-efficient, and robust system for real-world application. Furthermore, the P2P-based progressive data-fusion paradigm can improve the energy efficiency and robustness of target surveillance. PMID:19336319

  15. Distributed Denial of Service Tools, Trin00, Tribe Flood Network, Tribe Flood Network 2000 and Stacheldraht.

    SciTech Connect

    Criscuolo, P. J.

    2000-02-14

    One type of attack on computer systems is know as a Denial of Service (DoS) attack. A DoS attack is designed to prevent legitimate users from using a system. Traditional Denial of Service attacks are done by exploiting a buffer overflow, exhausting system resources, or exploiting a system bug that results in a system that is no longer functional. In the summer of 1999, a new breed of attack has been developed called Distributed Denial of Service (DDoS) attack. Several educational and high capacity commercial sites have been affected by these DDoS attacks. A DDoS attack uses multiple machines operating in concert to attack a network or site. There is very little that can be done if you are the target of a DDoS. The nature of these attacks cause so much extra network traffic that it is difficult for legitimate traffic to reach your site while blocking the forged attacking packets. The intent of this paper is to help sites not be involved in a DDoS attack. The first tools developed to perpetrate the DDoS attack were Trin00 and Tribe Flood Network (TFN). They spawned the next generation of tools called Tribe Flood Network 2000 (TFN2K) and Stacheldraht (German for Barb Wire). These DDoS attack tools are designed to bring one or more sites down by flooding the victim with large amounts of network traffic originating at multiple locations and remotely controlled by a single client. This paper discusses how these DDoS tools work, how to detect them, and specific technical information on each individual tool. It is written with the system administrator in mind. It assumes that the reader has basic knowledge of the TCP/IP Protocol.

  16. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing.

    PubMed

    Fujiwara, M; Waseda, A; Nojima, R; Moriai, S; Ogata, W; Sasaki, M

    2016-01-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir's (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

  17. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    NASA Astrophysics Data System (ADS)

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-07-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

  18. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    PubMed Central

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-01-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

  19. Modelling Framework and the Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks

    NASA Astrophysics Data System (ADS)

    Han, Xue; Sandels, Claes; Zhu, Kun; Nordström, Lars

    2013-08-01

    There has been a large body of statements claiming that the large-scale deployment of Distributed Energy Resources (DERs) could eventually reshape the future distribution grid operation in numerous ways. Thus, it is necessary to introduce a framework to measure to what extent the power system operation will be changed by various parameters of DERs. This article proposed a modelling framework for an overview analysis on the correlation between DERs. Furthermore, to validate the framework, the authors described the reference models of different categories of DERs with their unique characteristics, comprising distributed generation, active demand and electric vehicles. Subsequently, quantitative analysis was made on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. Simulations are performed in two typical distribution network models for four seasons. The simulation results show that in general the DER deployment brings in the possibilities to reduce the power losses and voltage drops by compensating power from the local generation and optimizing the local load profiles.

  20. Enhancements for distributed certificate authority approaches for mobile wireless ad hoc networks.

    SciTech Connect

    Van Leeuwen, Brian P.; Michalski, John T.; Anderson, William Erik

    2003-12-01

    Mobile wireless ad hoc networks that are resistant to adversarial manipulation are necessary for distributed systems used in military and security applications. Critical to the successful operation of these networks, which operate in the presence of adversarial stressors, are robust and efficient information assurance methods. In this report we describe necessary enhancements for a distributed certificate authority (CA) used in secure wireless network architectures. Necessary cryptographic algorithms used in distributed CAs are described and implementation enhancements of these algorithms in mobile wireless ad hoc networks are developed. The enhancements support a network's ability to detect compromised nodes and facilitate distributed CA services. We provide insights to the impacts the enhancements will have on network performance with timing diagrams and preliminary network simulation studies.

  1. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

    PubMed Central

    Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

  2. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

    PubMed

    Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

  3. Comparison of piezoelectronic networks acting as distributed vibration absorbers

    NASA Astrophysics Data System (ADS)

    Maurini, Corrado; dell'Isola, Francesco; Del Vescovo, Dionisio

    2004-09-01

    Electric vibration absorbers made of distributed piezoelectric devices for the control of beam vibrations are studied. The absorbers are obtained by interconnecting an array of piezoelectric transducers uniformly distributed on a beam with different modular electric networks. Five different topologies are considered and their damping performance is analysed and compared. Their optimal parameters are found by adopting a criterion for critical damping of k¯-waves: the parameters are suitably chosen to have the quickest temporal vibration decay for a single wave number k¯. The analysis is based on homogenized models of the modular piezo-electromechanical systems, i.e. they are regarded as continuous systems by assuming that the number of modules per unit length is high enough with respect to the considered wave numbers. Calling k¯ -absorbers the corresponding optimal absorbers, we show that: (i) k¯-waves are damped in k¯-absorbers with an optimal decay time which is independent of the absorber interconnecting topology, while it depends only on the piezoelectric coupling coefficient; (ii) the efficiency of k¯-absorbers depends significantly on the absorber interconnecting topology for k different from k¯; (iii) one of the proposed absorbers (which is made of a fourth-order electric transmission line with a second-order electric dissipation) equally performs for all the wave numbers and accomplishes an effective multi-modal damping for the mechanically forced response; (iv) the optimal values of the electric parameters differently depend on the number n of used circuit modules for different interconnecting topologies and, in particular, the optimal inductance per module needed in a fourth-order electric transmission line is proportional 1/ n3.

  4. Reduction of chemical reaction networks through delay distributions

    NASA Astrophysics Data System (ADS)

    Barrio, Manuel; Leier, André; Marquez-Lago, Tatiana T.

    2013-03-01

    Accurate modelling and simulation of dynamic cellular events require two main ingredients: an adequate description of key chemical reactions and simulation of such chemical events in reasonable time spans. Quite logically, posing the right model is a crucial step for any endeavour in Computational Biology. However, more often than not, it is the associated computational costs which actually limit our capabilities of representing complex cellular behaviour. In this paper, we propose a methodology aimed at representing chains of chemical reactions by much simpler, reduced models. The abridgement is achieved by generation of model-specific delay distribution functions, consecutively fed to a delay stochastic simulation algorithm. We show how such delay distributions can be analytically described whenever the system is solely composed of consecutive first-order reactions, with or without additional "backward" bypass reactions, yielding an exact reduction. For models including other types of monomolecular reactions (constitutive synthesis, degradation, or "forward" bypass reactions), we discuss why one must adopt a numerical approach for its accurate stochastic representation, and propose two alternatives for this. In these cases, the accuracy depends on the respective numerical sample size. Our model reduction methodology yields significantly lower computational costs while retaining accuracy. Quite naturally, computational costs increase alongside network size and separation of time scales. Thus, we expect our model reduction methodologies to significantly decrease computational costs in these instances. We anticipate the use of delays in model reduction will greatly alleviate some of the current restrictions in simulating large sets of chemical reactions, largely applicable in pharmaceutical and biological research.

  5. A Distributed Network for Social Cognition Enriched for Oxytocin Receptors

    PubMed Central

    Mitre, Mariela; Marlin, Bianca J.; Schiavo, Jennifer K.; Morina, Egzona; Norden, Samantha E.; Hackett, Troy A.; Aoki, Chiye J.

    2016-01-01

    Oxytocin is a neuropeptide important for social behaviors such as maternal care and parent–infant bonding. It is believed that oxytocin receptor signaling in the brain is critical for these behaviors, but it is unknown precisely when and where oxytocin receptors are expressed or which neural circuits are directly sensitive to oxytocin. To overcome this challenge, we generated specific antibodies to the mouse oxytocin receptor and examined receptor expression throughout the brain. We identified a distributed network of female mouse brain regions for maternal behaviors that are especially enriched for oxytocin receptors, including the piriform cortex, the left auditory cortex, and CA2 of the hippocampus. Electron microscopic analysis of the cerebral cortex revealed that oxytocin receptors were mainly expressed at synapses, as well as on axons and glial processes. Functionally, oxytocin transiently reduced synaptic inhibition in multiple brain regions and enabled long-term synaptic plasticity in the auditory cortex. Thus modulation of inhibition may be a general mechanism by which oxytocin can act throughout the brain to regulate parental behaviors and social cognition. SIGNIFICANCE STATEMENT Oxytocin is an important peptide hormone involved in maternal behavior and social cognition, but it has been unclear what elements of neural circuits express oxytocin receptors due to the paucity of suitable antibodies. Here, we developed new antibodies to the mouse oxytocin receptor. Oxytocin receptors were found in discrete brain regions and at cortical synapses for modulating excitatory-inhibitory balance and plasticity. These antibodies should be useful for future studies of oxytocin and social behavior. PMID:26911697

  6. Deployable Overlay Network for Defense against Distributed SYN Flood Attacks

    NASA Astrophysics Data System (ADS)

    Ohsita, Yuichi; Ata, Shingo; Murata, Masayuki

    Distributed denial-of-service attacks on public servers have recently become more serious. Most of them are SYN flood attacks, since the malicious attackers can easily exploit the TCP specification to generate traffic making public servers unavailable. We need a defense method which can protect legitimate traffic so that end users can connect the target servers during such attacks. In this paper, we propose a new framework, in which all of the TCP connections to the victim servers from a domain are maintained at the gateways of the domain (i. e., near the clients). We call the nodes maintaining the TCP connection defense nodes. The defense nodes check whether arriving packets are legitimate or not by maintaining the TCP connection. That is, the defense nodes delegate reply packets to the received connection request packets and identify the legitimate packets by checking whether the clients reply to the reply packets. Then, only identified traffic are relayed via overlay networks. As a result, by deploying the defense nodes at the gateways of a domain, the legitimate packets from the domain are relayed apart from other packets including attack packets and protected. Our simulation results show that our method can protect legitimate traffic from the domain deploying our method. We also describe the deployment scenario of our defense mechanism.

  7. Distributed density estimation in sensor networks based on variational approximations

    NASA Astrophysics Data System (ADS)

    Safarinejadian, Behrooz; Menhaj, Mohammad B.

    2011-09-01

    This article presents a peer-to-peer (P2P) distributed variational Bayesian (P2PDVB) algorithm for density estimation and clustering in sensor networks. It is assumed that measurements of the nodes can be statistically modelled by a common Gaussian mixture model. The variational approach allows the simultaneous estimate of the component parameters and the model complexity. In this algorithm, each node independently calculates local sufficient statistics first by using local observations. A P2P averaging approach is then used to diffuse local sufficient statistics to neighbours and estimate global sufficient statistics in each node. Finally, each sensor node uses the estimated global sufficient statistics to estimate the model order as well as the parameters of this model. Because the P2P averaging approach only requires that each node communicate with its neighbours, the P2PDVB algorithm is scalable and robust. Diffusion speed and convergence of the proposed algorithm are also studied. Finally, simulated and real data sets are used to verify the remarkable performance of proposed algorithm.

  8. Distributed Coding/Decoding Complexity in Video Sensor Networks

    PubMed Central

    Cordeiro, Paulo J.; Assunção, Pedro

    2012-01-01

    Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality. PMID:22736972

  9. Cyber-Physical Trade-Offs in Distributed Detection Networks

    SciTech Connect

    Rao, Nageswara S; Yao, David K. Y.; Chin, J. C.; Ma, Chris Y. T.; Madan, Rabinder

    2010-01-01

    We consider a network of sensors that measure the scalar intensity due to the background or a source combined with background, inside a two-dimensional monitoring area. The sensor measurements may be random due to the underlying nature of the source and background or due to sensor errors or both. The detection problem is infer the presence of a source of unknown intensity and location based on sensor measurements. In the conventional approach, detection decisions are made at the individual sensors, which are then combined at the fusion center, for example using the majority rule. With increased communication and computation costs, we show that a more complex fusion algorithm based on measurements achieves better detection performance under smooth and non-smooth source intensity functions, Lipschitz conditions on probability ratios and a minimum packing number for the state-space. We show that these conditions for trade-offs between the cyber costs and physical detection performance are applicable for two detection problems: (i) point radiation sources amidst background radiation, and (ii) sources and background with Gaussian distributions.

  10. Distributed reinforcement learning for adaptive and robust network intrusion response

    NASA Astrophysics Data System (ADS)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  11. A Distributed Network for Social Cognition Enriched for Oxytocin Receptors.

    PubMed

    Mitre, Mariela; Marlin, Bianca J; Schiavo, Jennifer K; Morina, Egzona; Norden, Samantha E; Hackett, Troy A; Aoki, Chiye J; Chao, Moses V; Froemke, Robert C

    2016-02-24

    Oxytocin is a neuropeptide important for social behaviors such as maternal care and parent-infant bonding. It is believed that oxytocin receptor signaling in the brain is critical for these behaviors, but it is unknown precisely when and where oxytocin receptors are expressed or which neural circuits are directly sensitive to oxytocin. To overcome this challenge, we generated specific antibodies to the mouse oxytocin receptor and examined receptor expression throughout the brain. We identified a distributed network of female mouse brain regions for maternal behaviors that are especially enriched for oxytocin receptors, including the piriform cortex, the left auditory cortex, and CA2 of the hippocampus. Electron microscopic analysis of the cerebral cortex revealed that oxytocin receptors were mainly expressed at synapses, as well as on axons and glial processes. Functionally, oxytocin transiently reduced synaptic inhibition in multiple brain regions and enabled long-term synaptic plasticity in the auditory cortex. Thus modulation of inhibition may be a general mechanism by which oxytocin can act throughout the brain to regulate parental behaviors and social cognition. PMID:26911697

  12. Applying a service-based architecture to autonomous distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Patrone, David M.; Patrone, Dennis S.; Wenstrand, Doug S.; Smith, Dexter G.

    2004-04-01

    Traditional distributed architectures are not sufficient when developing an autonomous, distributed sensor network. In order to be truly autonomous, a distributed sensor network must be able to survive and reconfigure in-the-field without manual intervention. A limitation of traditional distributed architectures, such as client/server or peer-to-peer, within an autonomous network is that the distributed devices and applications are tightly coupled by their communication protocols prior to implementation and deployment. The introduction of new devices and applications in the field is difficult due to this coupling. Also, autonomous reconfiguration of the devices on the network due to faults or addition of new devices is extremely difficult unless the devices are homogeneous. A service-based architecture is proposed as an alternative architecture for creating autonomous, distributed sensor networks. The service-based approach provides the ability to create a scalable, self-configuring, and self-healing network for building and maintaining large, emerging and ad-hoc virtual networks of devices and applications. New devices can be automatically discovered by current devices on the network and automatically integrated into the system without manual intervention. This paper will explain the benefits and limitations of applying a service-based architecture to autonomous, distributed sensor networks and compare this approach with traditional architectures such as client/server and peer-to-peer. A description will be given of a prototype system developed using service-enabled seismic, acoustic, and visual sensors.

  13. Analysis of Road Network Pattern Considering Population Distribution and Central Business District

    PubMed Central

    Zhao, Fangxia; Sun, Huijun; Wu, Jianjun; Gao, Ziyou; Liu, Ronghui

    2016-01-01

    This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the characteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks. PMID:26981857

  14. Using fuzzy sets to model the uncertainty in the fault location process of distribution networks

    SciTech Connect

    Jaerventausta, P.; Verho, P.; Partanen, J. )

    1994-04-01

    In the computerized fault diagnosis of distribution networks the heuristic knowledge of the control center operators can be combined with the information obtained from the network data base and SCADA system. However, the nature of the heuristic knowledge is inexact and uncertain. Also the information obtained from the remote control system contains uncertainty and may be incorrect, conflicting or inadequate. This paper proposes a method based on fuzzy set theory to deal with the uncertainty involved in the process of locating faults in distribution networks. The method is implemented in a prototype version of the distribution network operation support system.

  15. Distributed Network and Multiprocessing Minicomputer State-of-the-Art Capabilities.

    ERIC Educational Resources Information Center

    Theis, Douglas J.

    An examination of the capabilities of minicomputers and midicomputers now on the market reveals two basic items which users should evaluate when selecting computers for their own applications: distributed networking systems and multiprocessing architectures. Variables which should be considered in evaluating a distributed networking system…

  16. Stiffness threshold of randomly distributed carbon nanotube networks

    NASA Astrophysics Data System (ADS)

    Chen, Yuli; Pan, Fei; Guo, Zaoyang; Liu, Bin; Zhang, Jianyu

    2015-11-01

    For carbon nanotube (CNT) networks, with increasing network density, there may be sudden changes in the properties, such as the sudden change in electrical conductivity at the electrical percolation threshold. In this paper, the change in stiffness of the CNT networks is studied and especially the existence of stiffness threshold is revealed. Two critical network densities are found to divide the stiffness behavior into three stages: zero stiffness, bending dominated and stretching dominated stages. The first critical network density is a criterion to judge whether or not the network is capable of carrying load, defined as the stiffness threshold. The second critical network density is a criterion to measure whether or not most of the CNTs in network are utilized effectively to carry load, defined as bending-stretching transitional threshold. Based on the geometric probability analysis, a theoretical methodology is set up to predict the two thresholds and explain their underlying mechanisms. The stiffness threshold is revealed to be determined by the statical determinacy of CNTs in the network, and can be estimated quantitatively by the stabilization fraction of network, a newly proposed parameter in this paper. The other threshold, bending-stretching transitional threshold, which signs the conversion of dominant deformation mode, is verified to be well evaluated by the proposed defect fraction of network. According to the theoretical analysis as well as the numerical simulation, the average intersection number on each CNT is revealed as the only dominant factor for the electrical percolation and the stiffness thresholds, it is approximately 3.7 for electrical percolation threshold, and 5.2 for the stiffness threshold of 2D networks. For 3D networks, they are 1.4 and 4.4. And it also affects the bending-stretching transitional threshold, together with the CNT aspect ratio. The average intersection number divided by the fourth root of CNT aspect ratio is found to be

  17. Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

    NASA Astrophysics Data System (ADS)

    Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

    2011-06-01

    For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

  18. Software-Enabled Distributed Network Governance: The PopMedNet Experience

    PubMed Central

    Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

    2016-01-01

    Introduction: The expanded availability of electronic health information has led to increased interest in distributed health data research networks. Distributed Research Network Model: The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. Software Enabled Governance: PopMedNet: The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Selected Case Studies: Four case studies describe how PopMedNet is used to enforce network governance models. Issues and Challenges: Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. Conclusions: The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders. PMID:27141522

  19. Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

    NASA Technical Reports Server (NTRS)

    Wang, Shin-Ywan

    2012-01-01

    The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

  20. Simulation of quantum key distribution in a 16x16 optical fiber network

    NASA Astrophysics Data System (ADS)

    Lin, Hsin-Hung; Tsao, Shyh-Lin

    2004-10-01

    In this paper, we propose a 16x16 optical communication wavelength-switching network with quantum key distribution. We analyze the quantum ke distribution with considering the relationship betwee wavelength-switch bandwidth and distortion for 16x16 Dilated Benes optical wavelength-switching networks. We compare the performance of the quantum key distribution for wavelength-switching bandwidth in a 16x16 optical communication system, based on 2.5 Gbps, 10Gbps and 40Gbps, respectively.

  1. Extracting Hidden Hierarchies in 3D Distribution Networks

    NASA Astrophysics Data System (ADS)

    Modes, Carl; Magnasco, Marcelo; Katifori, Eleni

    2015-03-01

    Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks - the topology and edge weights - determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, we have developed a new algorithm that rests on an abstraction of the physical `tiling' in the case of a two dimensional network to an effective tiling of an abstract surface in space that the network may be thought to sit in. Generically these abstract surfaces are richer than the plane and upon sequential removal of the weakest links by edge weight, neighboring tiles merge and a tree characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models. This new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as mammalian vasculature in the organs, the root networks of clonal colonies like quaking aspen, or the force networks in jammed granular matter.

  2. Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

    ERIC Educational Resources Information Center

    Yu, Chao

    2013-01-01

    In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

  3. Research on social communication network evolution based on topology potential distribution

    NASA Astrophysics Data System (ADS)

    Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

    2011-12-01

    Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

  4. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.

    PubMed

    Navlakha, Saket; Barth, Alison L; Bar-Joseph, Ziv

    2015-07-01

    Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. PMID:26217933

  5. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks

    PubMed Central

    Navlakha, Saket; Barth, Alison L.; Bar-Joseph, Ziv

    2015-01-01

    Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. PMID:26217933

  6. Extracting Hidden Hierarchies in 3D Distribution Networks

    NASA Astrophysics Data System (ADS)

    Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

    2016-07-01

    Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks, as defined by the topology and edge weights, determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, we have developed a new algorithm that rests on an abstraction of the physical "tiling" in the case of a two-dimensional network to an effective tiling of an abstract surface in 3-space that the network may be thought to sit in. Generically, these abstract surfaces are richer than the flat plane because there are now two families of fundamental units that may aggregate upon cutting weakest links—the plaquettes of the tiling and the longer "topological" cycles associated with the abstract surface itself. Upon sequential removal of the weakest links, as determined by a physically relevant edge weight, such as flow volume or capacity, neighboring plaquettes merge and a new tree graph characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models. The new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as mammalian vasculature in the organs or the force networks in jammed granular matter.

  7. Data on the distribution of physical activities in the Shenzhen greenway network with volunteered geographic information.

    PubMed

    Liu, Kun; Siu, Kin Wai Michael; Gong, Yong Xi; Gao, Yuan; Lu, Dan

    2016-09-01

    This data presents the distribution of physical activities in the Shenzhen greenway network (GN) in January, April and July, 2014. The volunteered geographic on physical activity is overlaid with the greenways data, to describe the distribution of physical activities in the greenways. The data are summarized to show the distribution characteristics geographically from different aspects in Shenzhen, China. Data were used to explore the effect of the Shenzhen GN on supporting physical activities, "Where do networks really work? The effects of Shenzhen greenway network on supporting physical activities" (Liu et al., 2016) [2]. PMID:27257616

  8. Method and apparatus for reducing the harmonic currents in alternating-current distribution networks

    DOEpatents

    Beverly, L.H.; Hance, R.D.; Kristalinski, A.L.; Visser, A.T.

    1996-11-19

    An improved apparatus and method reduce the harmonic content of AC line and neutral line currents in polyphase AC source distribution networks. The apparatus and method employ a polyphase Zig-Zag transformer connected between the AC source distribution network and a load. The apparatus and method also employs a mechanism for increasing the source neutral impedance of the AC source distribution network. This mechanism can consist of a choke installed in the neutral line between the AC source and the Zig-Zag transformer. 23 figs.

  9. Method and apparatus for reducing the harmonic currents in alternating-current distribution networks

    DOEpatents

    Beverly, Leon H.; Hance, Richard D.; Kristalinski, Alexandr L.; Visser, Age T.

    1996-01-01

    An improved apparatus and method reduce the harmonic content of AC line and neutral line currents in polyphase AC source distribution networks. The apparatus and method employ a polyphase Zig-Zag transformer connected between the AC source distribution network and a load. The apparatus and method also employs a mechanism for increasing the source neutral impedance of the AC source distribution network. This mechanism can consist of a choke installed in the neutral line between the AC source and the Zig-Zag transformer.

  10. Distributive Computer Networking: Making It Work on a Regional Basis: Effective sharing through a network requires new management and resource distribution techniques.

    PubMed

    Cornew, R W; Morse, P M

    1975-08-15

    After 4 years of operation the NERComP network is now a self-supporting success. Some of the reasons for its success are that (i) the network started small and built up utilization; (ii) the members, through monthly trustee meetings, practiced "participatory management" from the outset; (iii) unlike some networks, NERComP appealed to individual academic and research users who were terminal-oriented and who controlled their own budgets; (iv) the compactness of the New England region made it an ideal laboratory for testing networking concepts; and (v) a dedicated staff was willing to work hard in the face of considerable uncertainty. While the major problems were "political, organizational and economic" (1) we have found that they can be solved if the network meets real needs. We have also found that it is difficult to proceed beyond a certain point without investing responsibility and authority in the networking organization. Conversely, there is a need to distribute some responsibilities such as marketing and user services back to the member institutions. By adopting a modest starting point and achieving limited goals the necessary trust and working relationships between institutions can be built. In our case the necessary planning has been facilitated by recognizing three distinct network functions: governance, user services, and technical operations. Separating out the three essential networing tasks and dealing with each individually through advisory committees, each with its own staff coordinator, has overcome a distracting tendency to address all issues at once. It has also provided an element of feedback between the end user and the supplier not usually present in networking activity. The success of NERComP demonstrates that a distributive-type network can work. Our experiences in New England-which, because of its numerous colleges and universities free from domination by any single institution, is a microcosm for academic computing in the United States

  11. Distributed learning automata-based algorithm for community detection in complex networks

    NASA Astrophysics Data System (ADS)

    Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza

    2016-03-01

    Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.

  12. Comparison of Lauritzen-Spiegelhalter and successive restrictions algorithms for computing probability distributions in Bayesian networks

    NASA Astrophysics Data System (ADS)

    Smail, Linda

    2016-06-01

    The basic task of any probabilistic inference system in Bayesian networks is computing the posterior probability distribution for a subset or subsets of random variables, given values or evidence for some other variables from the same Bayesian network. Many methods and algorithms have been developed to exact and approximate inference in Bayesian networks. This work compares two exact inference methods in Bayesian networks-Lauritzen-Spiegelhalter and the successive restrictions algorithm-from the perspective of computational efficiency. The two methods were applied for comparison to a Chest Clinic Bayesian Network. Results indicate that the successive restrictions algorithm shows more computational efficiency than the Lauritzen-Spiegelhalter algorithm.

  13. Implementation of a tactical voice/data network over FDDI. [Fiber Distributed Data Interface

    NASA Technical Reports Server (NTRS)

    Bergman, L. A.; Halloran, F.; Martinez, J.

    1988-01-01

    An asynchronous high-speed fiber-optic local-area network is described that simultaneously supports packet data traffic with synchronous TI voice traffic over a standard asynchronous FDDI (fiber distributed data interface) token-ring channel. A voice interface module was developed that parses, buffers, and resynchronizes the voice data to the packet network. The technique is general, however, and can be applied to any deterministic class of networks, including multitier backbones. In addition, the higher layer packet data protocols may operate independently of those for the voice, thereby permitting great flexibility in reconfiguring the network. Voice call setup and switching functions are performed external to the network with PABX equipment.

  14. NetWall distributed firewall in the use of campus network

    NASA Astrophysics Data System (ADS)

    He, Junhua; Zhang, Pengshuai

    2011-10-01

    Internet provides a modern means of education but also non-mainstream consciousness and poor dissemination of information opens the door, network and moral issues have become prominent, poor dissemination of information and network spread rumors and negative effects of new problems, ideological and political education in schools had a huge impact, poses a severe challenge. This paper presents a distributed firewall will NetWall deployed in a campus network solution. The characteristics of the campus network, using technology to filter out bad information on the means of control, of sensitive information related to the record, establish a complete information security management platform for the campus network.

  15. Geometry of river networks. II. Distributions of component size and number

    SciTech Connect

    Dodds, Peter Sheridan; Rothman, Daniel H.

    2001-01-01

    The structure of a river network may be seen as a discrete set of nested subnetworks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon, and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power-law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.

  16. Recent advances on distributed filtering for stochastic systems over sensor networks

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Wang, Zidong; Shen, Bo

    2014-05-01

    Sensor networks comprising of tiny, power-constrained nodes with sensing, computation, and wireless communication capabilities are gaining popularity due to their potential application in a wide variety of environments like monitoring of environmental attributes and various military and civilian applications. Considering the limited power and communication resources of the sensor nodes, the strategy of the distributed information processing is widely exploited. Therefore, it would be interesting to examine how the topology, network-induced phenomena, and power constraints influence the distributed filtering performance and to obtain some suitable schemes in order to solve the addressed distributed filter design problem. In this paper, we aim to survey some recent advances on the distributed filtering and distributed state estimation problems over the sensor networks with various performance requirements and/or randomly occurring network-induced phenomena. First, some practical filter structures are addressed in detail. Then, the developments of the distributed Kalman filtering, distributed state estimation based on the stability or mean-square error analysis, and distributed ? filtering are systematically reviewed. In addition, latest results on the distributed filtering or state estimation over sensor networks are discussed in great detail and some challenges are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out.

  17. Scaling of nearest neighbors' connectivity distribution for scale-free networks

    NASA Astrophysics Data System (ADS)

    Wei, Zong-Wen; Zhang, Wen-Yao; li, Yu-Jian; Wang, Bing-Hong

    2015-09-01

    Most of real-world networks are called scale-free networks, since the degree distribution follows a power law. However, observing from a node, its nearest neighbors' degree distribution expressed by conditional probability P(k'|k) lacks definite studies and conclusions. Here, we provide a systematic study combined with theoretical and empirical demonstrations, which reveal the inherent connectivity profile of real-world networks. We show that P(k'|k) in the regime k' and k'>k can be approximated by different power laws. One is strongly determined by the degree correlation, and the other depends on both degree distribution and correlation. Based on this result, we propose a degree correlation spectra approach beyond the widely used Pearson correlation coefficient, finding that some networks exhibit sophisticated hybrid correlation patterns. Our results represent a step forward in understanding the structure of complex networks.

  18. Patient Informed Governance of Distributed Research Networks: Results and Discussion from Six Patient Focus Groups

    PubMed Central

    Mamo, Laura A.; Browe, Dennis K.; Logan, Holly C.; Kim, Katherine K.

    2013-01-01

    Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients’ views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes. PMID:24551383

  19. The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons.

    PubMed

    Roxin, Alex

    2011-01-01

    Neuronal network models often assume a fixed probability of connection between neurons. This assumption leads to random networks with binomial in-degree and out-degree distributions which are relatively narrow. Here I study the effect of broad degree distributions on network dynamics by interpolating between a binomial and a truncated power-law distribution for the in-degree and out-degree independently. This is done both for an inhibitory network (I network) as well as for the recurrent excitatory connections in a network of excitatory and inhibitory neurons (EI network). In both cases increasing the width of the in-degree distribution affects the global state of the network by driving transitions between asynchronous behavior and oscillations. This effect is reproduced in a simplified rate model which includes the heterogeneity in neuronal input due to the in-degree of cells. On the other hand, broadening the out-degree distribution is shown to increase the fraction of common inputs to pairs of neurons. This leads to increases in the amplitude of the cross-correlation (CC) of synaptic currents. In the case of the I network, despite strong oscillatory CCs in the currents, CCs of the membrane potential are low due to filtering and reset effects, leading to very weak CCs of the spike-count. In the asynchronous regime of the EI network, broadening the out-degree increases the amplitude of CCs in the recurrent excitatory currents, while CC of the total current is essentially unaffected as are pairwise spiking correlations. This is due to a dynamic balance between excitatory and inhibitory synaptic currents. In the oscillatory regime, changes in the out-degree can have a large effect on spiking correlations and even on the qualitative dynamical state of the network. PMID:21556129

  20. Innovation of laboratory exercises in course Distributed systems and computer networks

    NASA Astrophysics Data System (ADS)

    Souček, Pavel; Slavata, Oldřich; Holub, Jan

    2013-09-01

    This paper is focused on innovation of laboratory exercises in course Distributed Systems and Computer Networks. These exercises were introduced in November of 2012 and replaced older exercises in order to reflect real life applications.

  1. Epidemic spreading on complex networks with general degree and weight distributions

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Tang, Ming; Zhang, Hai-Feng; Gao, Hui; Do, Younghae; Liu, Zong-Hua

    2014-10-01

    The spread of disease on complex networks has attracted wide attention in the physics community. Recent works have demonstrated that heterogeneous degree and weight distributions have a significant influence on the epidemic dynamics. In this study, a novel edge-weight-based compartmental approach is developed to estimate the epidemic threshold and epidemic size (final infected density) on networks with general degree and weight distributions, and a remarkable agreement with numerics is obtained. Even in complex networks with the strong heterogeneous degree and weight distributions, this approach is used. We then propose an edge-weight-based removal strategy with different biases and find that such a strategy can effectively control the spread of epidemic when the highly weighted edges are preferentially removed, especially when the weight distribution of a network is extremely heterogenous. The theoretical results from the suggested method can accurately predict the above removal effectiveness.

  2. Energy Efficiency of Distributed Signal Processing in Wireless Networks: A Cross-Layer Analysis

    NASA Astrophysics Data System (ADS)

    Geraci, Giovanni; Wildemeersch, Matthias; Quek, Tony Q. S.

    2016-02-01

    In order to meet the growing mobile data demand, future wireless networks will be equipped with a multitude of access points (APs). Besides the important implications for the energy consumption, the trend towards densification requires the development of decentralized and sustainable radio resource management techniques. It is critically important to understand how the distribution of signal processing operations affects the energy efficiency of wireless networks. In this paper, we provide a cross-layer framework to evaluate and compare the energy efficiency of wireless networks under different levels of distribution of the signal processing load: (i) hybrid, where the signal processing operations are shared between nodes and APs, (ii) centralized, where signal processing is entirely implemented at the APs, and (iii) fully distributed, where all operations are performed by the nodes. We find that in practical wireless networks, hybrid signal processing exhibits a significant energy efficiency gain over both centralized and fully distributed approaches.

  3. Distributed Transforms for Efficient Data Gathering in Sensor Networks

    NASA Technical Reports Server (NTRS)

    Ortega, Antonio (Inventor); Narang, Sunil K. (Inventor); Shen, Godwin (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.

  4. The values of the parameters of some multilayer distributed RC null networks

    NASA Technical Reports Server (NTRS)

    Huelsman, L. P.; Raghunath, S.

    1974-01-01

    In this correspondence, the values of the parameters of some multilayer distributed RC notch networks are determined, and the usually accepted values are shown to be in error. The magnitude of the error is illustrated by graphs of the frequency response of the networks.

  5. Wavelength-division-multiplexed distributed optical fiber amplifier bus network for data and sensors

    NASA Astrophysics Data System (ADS)

    Lopez-Amo, Manuel; Blair, Loudon T.; Urquhart, Paul

    1993-07-01

    A wavelength division multiplexed data gathering network is reported by using a distributed fiber amplifier bus. Using lightly doped erbium fiber and fiber Bragg gratings, a prototype has been constructed. A suitable network topology is considered for simultaneous transmission of data and wavelength multiplexing of sensors.

  6. Distributed Teaching Presence and Communicative Patterns in Asynchronous Learning: Name versus Reply Networks

    ERIC Educational Resources Information Center

    Engel, Anna; Coll, Cesar; Bustos, Alfonso

    2013-01-01

    This work explores some methodological challenges in the application of Social Network Analysis (SNA) to the study of "Asynchronous Learning Networks" (ALN). Our interest in the SNA is situated within the framework of the study of Distributed Teaching Presence (DTP), understood as the exercise of educational influence, through a multi-method…

  7. Simulation based flow distribution network optimization for vacuum assisted resin transfer moulding process

    NASA Astrophysics Data System (ADS)

    Hsiao, Kuang-Ting; Devillard, Mathieu; Advani, Suresh G.

    2004-05-01

    In the vacuum assisted resin transfer moulding (VARTM) process, using a flow distribution network such as flow channels and high permeability fabrics can accelerate the resin infiltration of the fibre reinforcement during the manufacture of composite parts. The flow distribution network significantly influences the fill time and fill pattern and is essential for the process design. The current practice has been to cover the top surface of the fibre preform with the distribution media with the hope that the resin will flood the top surface immediately and penetrate through the thickness. However, this approach has some drawbacks. One is when the resin finds its way to the vent before it has penetrated the preform entirely, which results in a defective part or resin wastage. Also, if the composite structure contains ribs or inserts, this approach invariably results in dry spots. Instead of this intuitive approach, we propose a science-based approach to design the layout of the distribution network. Our approach uses flow simulation of the resin into the network and the preform and a genetic algorithm to optimize the flow distribution network. An experimental case study of a co-cured rib structure is conducted to demonstrate the design procedure and validate the optimized flow distribution network design. Good agreement between the flow simulations and the experimental results was observed. It was found that the proposed design algorithm effectively optimized the flow distribution network of the part considered in our case study and hence should prove to be a useful tool to extend the VARTM process to manufacture of complex structures with effective use of the distribution network layup.

  8. Distributed Finite Element Analysis Using a Transputer Network

    NASA Technical Reports Server (NTRS)

    Watson, James; Favenesi, James; Danial, Albert; Tombrello, Joseph; Yang, Dabby; Reynolds, Brian; Turrentine, Ronald; Shephard, Mark; Baehmann, Peggy

    1989-01-01

    The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

  9. Multisensory integration substantiates distributed and overlapping neural networks.

    PubMed

    Pasqualotto, Achille

    2016-01-01

    The hypothesis that highly overlapping networks underlie brain functions (neural reuse) is decisively supported by three decades of multisensory research. Multisensory areas process information from more than one sensory modality and therefore represent the best examples of neural reuse. Recent evidence of multisensory processing in primary visual cortices further indicates that neural reuse is a basic feature of the brain. PMID:27562234

  10. Space Networking Demonstrated for Distributed Human-Robotic Planetary Exploration

    NASA Technical Reports Server (NTRS)

    Bizon, Thomas P.; Seibert, Marc A.

    2003-01-01

    Communications and networking experts from the NASA Glenn Research Center designed and implemented an innovative communications infrastructure for a simulated human-robotic planetary mission. The mission, which was executed in the Arizona desert during the first 2 weeks of September 2002, involved a diverse team of researchers from several NASA centers and academic institutions.

  11. How breadth of degree distribution influences network robustness: Comparing localized and random attacks

    NASA Astrophysics Data System (ADS)

    Yuan, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo

    2015-09-01

    The stability of networks is greatly influenced by their degree distributions and in particular by their breadth. Networks with broader degree distributions are usually more robust to random failures but less robust to localized attacks. To better understand the effect of the breadth of the degree distribution we study two models in which the breadth is controlled and compare their robustness against localized attacks (LA) and random attacks (RA). We study analytically and by numerical simulations the cases where the degrees in the networks follow a bi-Poisson distribution, P (k ) =α e-λ1λ/1kk ! +(1 -α ) e-λ2λ/2kk ! ,α ∈[0 ,1 ] , and a Gaussian distribution, P (k ) =A exp(-(k/-μ) 22 σ2 ), with a normalization constant A where k ≥0 . In the bi-Poisson distribution the breadth is controlled by the values of α , λ1, and λ2, while in the Gaussian distribution it is controlled by the standard deviation, σ . We find that only when α =0 or α =1 , i.e., degrees obeying a pure Poisson distribution, are LA and RA the same. In all other cases networks are more vulnerable under LA than under RA. For a Gaussian distribution with an average degree μ fixed, we find that when σ2 is smaller than μ the network is more vulnerable against random attack. When σ2 is larger than μ , however, the network becomes more vulnerable against localized attack. Similar qualitative results are also shown for interdependent networks.

  12. Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

    PubMed

    Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

    2016-05-01

    Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed. PMID:25956002

  13. A Topology Visualization Early Warning Distribution Algorithm for Large-Scale Network Security Incidents

    PubMed Central

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology. PMID:24191145

  14. A topology visualization early warning distribution algorithm for large-scale network security incidents.

    PubMed

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology. PMID:24191145

  15. The Study of Development Strategy for Bank Distribution Network through the Analysis of Inter-regional Financial Transaction Network

    NASA Astrophysics Data System (ADS)

    Hong, Jae Weon; Hong, Won Eui; Kwak, Yoon Sik

    This study attempts to shed light on the factors that influence the locations of bank branches in establishing a bank's distribution network from the angle of the network analysis. Whereas the previous studies analyzed the locations of bank branches on the basis of their geographical characteristics and image, the significance of this study rests upon the fact that it endeavors to explore the location factors from a new perspective of the movement path of financial customers. For this analysis, the network between administrative districts, which form the fundamental unit of a location, was analyzed based on the financial transactional data. The important findings of this study are as follows. First, in conformity with the previous studies, the income level, the spending level, the number of businesses, and the size of workforce in the pertinent region were all found to influence the size of a bank's market. Second, the centrality index extracted from the analysis of the network was found to have a significant effect on the locations of bank branches. In particular, the degree centrality was revealed to have a greater influence on the size of a bank's market than does the closeness centrality. Such results of this study clearly suggest the needs for a new approach from the perspective of network in furtherance of other factors that have been considered important in the previous studies of the distribution network strategies.

  16. Improving Power Quality in Low-Voltage Networks Containing Distributed Energy Resources

    NASA Astrophysics Data System (ADS)

    Mazumder, Sumit; Ghosh, Arindam; Zare, Firuz

    2013-05-01

    Severe power quality problems can arise when a large number of single-phase distributed energy resources (DERs) are connected to a low-voltage power distribution system. Due to the random location and size of DERs, it may so happen that a particular phase generates excess power than its load demand. In such an event, the excess power will be fed back to the distribution substation and will eventually find its way to the transmission network, causing undesirable voltage-current unbalance. As a solution to this problem, the article proposes the use of a distribution static compensator (DSTATCOM), which regulates voltage at the point of common coupling (PCC), thereby ensuring balanced current flow from and to the distribution substation. Additionally, this device can also support the distribution network in the absence of the utility connection, making the distribution system work as a microgrid. The proposals are validated through extensive digital computer simulation studies using PSCADTM.

  17. Distributed Microprocessor Automation Network for Synthesizing Radiotracers Used in Positron Emission Tomography [PET

    DOE R&D Accomplishments Database

    Russell, J. A. G.; Alexoff, D. L.; Wolf, A. P.

    1984-09-01

    This presentation describes an evolving distributed microprocessor network for automating the routine production synthesis of radiotracers used in Positron Emission Tomography. We first present a brief overview of the PET method for measuring biological function, and then outline the general procedure for producing a radiotracer. The paper identifies several reasons for our automating the syntheses of these compounds. There is a description of the distributed microprocessor network architecture chosen and the rationale for that choice. Finally, we speculate about how this network may be exploited to extend the power of the PET method from the large university or National Laboratory to the biomedical research and clinical community at large. (DT)

  18. Experiences on integration of network management and a distributed computing platform

    NASA Astrophysics Data System (ADS)

    Rahkila, Sakari; Stenberg, Susanne

    1997-09-01

    The integration of the two recognized network management protocol standards, common management information protocol, and simple network management protocol, and common object request broker architecture (CORBA) technology, allows management applications to take advantage of distributed object computing as well as the standardized network management protocols. This paper describes the distributed computing platform (DCP) prototype developed at the Nokia Research Center. The DCP prototype is a framework, including tools, compilers and gateways, built to support both Internet and open systems interconnection management through a CORBA infrastructure.

  19. Better understanding of water quality evolution in water distribution networks using data clustering.

    PubMed

    Mandel, Pierre; Maurel, Marie; Chenu, Damien

    2015-12-15

    The complexity of water distribution networks raises challenges in managing, monitoring and understanding their behavior. This article proposes a novel methodology applying data clustering to the results of hydraulic simulation to define quality zones, i.e. zones with the same dynamic water origin. The methodology is presented on an existing Water Distribution Network; a large dataset of conductivity measurements measured by 32 probes validates the definition of the quality zones. The results show how quality zones help better understanding the network operation and how they can be used to analyze water quality events. Moreover, a statistical comparison with 158,230 conductivity measurements validates the definition of the quality zones. PMID:26378733

  20. Distribution Tolerant Network Technology Flight Validation Report: DINET

    NASA Technical Reports Server (NTRS)

    Jones, Ross M.

    2009-01-01

    In October and November of 2008, the Jet Propulsion Laboratory installed and tested essential elements of Delay/Disruption Tolerant Networking (DTN) technology on the Deep Impact spacecraft. This experiment, called Deep Impact Network Experiment (DINET), was performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. During DINET some 300 images were transmitted from the JPL nodes to the spacecraft. Then, they were automatically forwarded from the spacecraft back to the JPL nodes, exercising DTN's bundle origination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days. All transmitted bundles were successfully received, without corruption. The DINET experiment demonstrated DTN readiness for operational use in space missions.

  1. Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

    NASA Astrophysics Data System (ADS)

    Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

    2016-06-01

    In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

  2. Overview of the human brain as a distributed computing network

    SciTech Connect

    Gevins, A.S.

    1983-01-01

    The hierarchically organized human brain is viewed as a prime example of a massively parallel, adaptive information processing and process control system. A brief overview of the human brain is provided for computer architects, in hopes that the principles of massive parallelism, dense connectivity and self-organization of assemblies of processing elements will prove relevant to the design of fifth generation VLSI computing networks. 6 references.

  3. Wavelength-division-multiplexed distributed optical fiber amplifier bus network for data and sensors

    NASA Astrophysics Data System (ADS)

    Lopez-Amo, Manuel; Blair, Loudon T.; Urquhart, Paul

    1993-07-01

    A wavelength-division-multiplexed distributed optical fiber amplifier bus network was constructed, using five 150-m sections of lightly doped Er fiber to provide signal amplification and four 1 x 2 directional couplers to tap the signal to four Bragg reflectors. The performance of the bus network was studied at different signal wavelengths, and the network topology suitable for simultaneous transmission of data and wavelength multiplexing of sensors was considered. Such an approach can increase the use of fiber-based local-area networks in intelligent (smart) structures.

  4. The effect of structural and rheological properties on blood flow distributions in capillary networks

    NASA Astrophysics Data System (ADS)

    Goldman, Daniel

    2001-11-01

    In various tissues microvascular structure, both geometric and topological, has been shown to be an important determinant of microcirculatory hemodynamics. In addition, blood rheology affects flow and hematocrit distributions in the microcirculation. Here we study steady-state hemodynamics in capillary networks modeled on the three-dimensional structure of the hamster cheek pouch retractor muscle. Capillary diameter is fixed while other structural properties are varied and an ensemble of similar random networks is generated for each parameter set. Using an experimentally derived two-phase continuum model for the flow of blood plasma and red cells, we investigate the effects of network size and topology on blood flow distributions and their variability. We also use typical capillary network structures to examine the importance of rheological effects under varying conditions. Our results indicate the relative importance of microvascular structure and blood rheology in determining the hemodynamic properties of capillary networks in striated muscle.

  5. 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.

  6. Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

    PubMed Central

    Takahashi, Daniel Yasumasa; Sato, João Ricardo; Ferreira, Carlos Eduardo; Fujita, André

    2012-01-01

    The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a “fingerprint”. Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the “uncertainty” of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed. PMID:23284629

  7. Field and long-term demonstration of a wide area quantum key distribution network.

    PubMed

    Wang, Shuang; Chen, Wei; Yin, Zhen-Qiang; Li, Hong-Wei; He, De-Yong; Li, Yu-Hu; Zhou, Zheng; Song, Xiao-Tian; Li, Fang-Yi; Wang, Dong; Chen, Hua; Han, Yun-Guang; Huang, Jing-Zheng; Guo, Jun-Fu; Hao, Peng-Lei; Li, Mo; Zhang, Chun-Mei; Liu, Dong; Liang, Wen-Ye; Miao, Chun-Hua; Wu, Ping; Guo, Guang-Can; Han, Zheng-Fu

    2014-09-01

    A wide area quantum key distribution (QKD) network deployed on communication infrastructures provided by China Mobile Ltd. is demonstrated. Three cities and two metropolitan area QKD networks were linked up to form the Hefei-Chaohu-Wuhu wide area QKD network with over 150 kilometers coverage area, in which Hefei metropolitan area QKD network was a typical full-mesh core network to offer all-to-all interconnections, and Wuhu metropolitan area QKD network was a representative quantum access network with point-to-multipoint configuration. The whole wide area QKD network ran for more than 5000 hours, from 21 December 2011 to 19 July 2012, and part of the network stopped until last December. To adapt to the complex and volatile field environment, the Faraday-Michelson QKD system with several stability measures was adopted when we designed QKD devices. Through standardized design of QKD devices, resolution of symmetry problem of QKD devices, and seamless switching in dynamic QKD network, we realized the effective integration between point-to-point QKD techniques and networking schemes. PMID:25321550

  8. Network robustness to targeted attacks. The interplay of expansibility and degree distribution

    NASA Astrophysics Data System (ADS)

    Estrada, E.

    2006-08-01

    We study the property of certain complex networks of being both sparse and highly connected, which is known as “good expansion” (GE). A network has GE properties if every subset S of nodes (up to 50% of the nodes) has a neighborhood that is larger than some “expansion factor” φ multiplied by the number of nodes in S. Using a graph spectral method we introduce here a new parameter measuring the good expansion character of a network. By means of this parameter we are able to classify 51 real-world complex networks — technological, biological, informational, biological and social — as GENs or non-GENs. Combining GE properties and node degree distribution (DD) we classify these complex networks in four different groups, which have different resilience to intentional attacks against their nodes. The simultaneous existence of GE properties and uniform degree distribution contribute significantly to the robustness in complex networks. These features appear solely in 14% of the 51 real-world networks studied here. At the other extreme we find that ˜40% of all networks are very vulnerable to targeted attacks. They lack GE properties, display skewed DD — exponential or power-law — and their topologies are changed more dramatically by targeted attacks directed at bottlenecks than by the removal of network hubs.

  9. Analysis and synthesis of distributed-lumped-active networks by digital computer

    NASA Technical Reports Server (NTRS)

    1973-01-01

    The use of digital computational techniques in the analysis and synthesis of DLA (distributed lumped active) networks is considered. This class of networks consists of three distinct types of elements, namely, distributed elements (modeled by partial differential equations), lumped elements (modeled by algebraic relations and ordinary differential equations), and active elements (modeled by algebraic relations). Such a characterization is applicable to a broad class of circuits, especially including those usually referred to as linear integrated circuits, since the fabrication techniques for such circuits readily produce elements which may be modeled as distributed, as well as the more conventional lumped and active ones.

  10. Three Phase Probabilistic Load Flow in Radial Distribution Networks

    SciTech Connect

    Melhorn, Alexander C; Dimitrovski, Aleksandar D; Tomsovic, Kevin L

    2012-01-01

    Probabilistic load flow is a helpful tool in accounting for inconsistent or unknown loads and generation. This is especially true with the push for renewable generation and demand response. This paper proposes an improved version of the probabilistic load flow solution for balanced distribution systems and takes the next step by applying it to unbalanced three phase systems. It is validated by comparing the solutions to that obtained by Monte Carlo simulation. The proposed method provides an accurate and practical way for finding the solution to the stochastic problems occurring in power distribution system analysis today.

  11. Lifetime optimization of wireless sensor network by a better nodes positioning and energy distribution

    NASA Astrophysics Data System (ADS)

    Lebreton, J. M.; Murad, N. M.

    2014-10-01

    The purpose of this paper is to propose a method of energy distribution on a Wireless Sensor Network (WSN). Nodes are randomly positioned and the sink is placed at the centre of the surface. Simulations show that relay nodes around the sink are too much requested to convey data, which substantially reduces their lifetime. So, several algorithmic solutions are presented to optimize the energy distribution on each node, compared to the classical uniform energy distribution. Their performance is discussed in terms of failure rate of data transmission and network lifetime. Moreover, the total energy distributed on all nodes before the deployment is invariable and some non-uniform energy distributions are created. Finally, simulations show that every energy distributions greatly improve the WSN lifetime and decrease the failure rate of data transmission.

  12. Apparatus and method for data communication in an energy distribution network

    DOEpatents

    Hussain, Mohsin; LaPorte, Brock; Uebel, Udo; Zia, Aftab

    2014-07-08

    A system for communicating information on an energy distribution network is disclosed. In one embodiment, the system includes a local supervisor on a communication network, wherein the local supervisor can collect data from one or more energy generation/monitoring devices. The system also includes a command center on the communication network, wherein the command center can generate one or more commands for controlling the one or more energy generation devices. The local supervisor can periodically transmit a data signal indicative of the data to the command center via a first channel of the communication network at a first interval. The local supervisor can also periodically transmit a request for a command to the command center via a second channel of the communication network at a second interval shorter than the first interval. This channel configuration provides effective data communication without a significant increase in the use of network resources.

  13. Stability of weighted spectral distribution in a pseudo tree-like network model

    NASA Astrophysics Data System (ADS)

    Bo, Jiao; Yuan-ping, Nie; Cheng-dong, Huang; Jing, Du; Rong-hua, Guo; Fei, Huang; Jian-mai, Shi

    2016-05-01

    The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution (i.e., a spectral graph feature) as the network order increases. First, we use deterministic scale-free networks generated by a pseudo tree-like model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system. Project supported by the National Natural Science Foundation of China (Grant Nos. 61402485, 61303061, and 71201169).

  14. Distributed power allocation for sink-centric clusters in multiple sink wireless sensor networks.

    PubMed

    Cao, Lei; Xu, Chen; Shao, Wei; Zhang, Guoan; Zhou, Hui; Sun, Qiang; Guo, Yuehua

    2010-01-01

    Due to the battery resource constraints, saving energy is a critical issue in wireless sensor networks, particularly in large sensor networks. One possible solution is to deploy multiple sink nodes simultaneously. Another possible solution is to employ an adaptive clustering hierarchy routing scheme. In this paper, we propose a multiple sink cluster wireless sensor networks scheme which combines the two solutions, and propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink wireless sensor networks, denoted as MSCWSNs-PC. It is a distributed, scalable, self-organizing, adaptive system, and the sensor nodes do not require knowledge of the global network and their location. All sinks effectively work out a representative view of a monitored region, after which power control is employed to optimize network topology. The simulations demonstrate the advantages of our new protocol. PMID:22294911

  15. Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

    PubMed Central

    Murata, Masayuki

    2013-01-01

    The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

  16. Noise-assisted concurrent multipath traffic distribution in ad hoc networks.

    PubMed

    Asvarujanon, Narun; Leibnitz, Kenji; Wakamiya, Naoki; Murata, Masayuki

    2013-01-01

    The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

  17. High Speed Quantum Key Distribution Over Optical Fiber Network System1

    PubMed Central

    Ma, Lijun; Mink, Alan; Tang, Xiao

    2009-01-01

    The National Institute of Standards and Technology (NIST) has developed a number of complete fiber-based high-speed quantum key distribution (QKD) systems that includes an 850 nm QKD system for a local area network (LAN), a 1310 nm QKD system for a metropolitan area network (MAN), and a 3-node quantum network controlled by a network manager. This paper discusses the key techniques used to implement these systems, which include polarization recovery, noise reduction, frequency up-conversion detection based on a periodically polled lithium nitrate (PPLN) waveguide, custom high-speed data handling boards and quantum network management. Using our quantum network, a QKD secured video surveillance application has been demonstrated. Our intention is to show the feasibility and sophistication of QKD systems based on current technology.

  18. Supervised learning of probability distributions by neural networks

    NASA Technical Reports Server (NTRS)

    Baum, Eric B.; Wilczek, Frank

    1988-01-01

    Supervised learning algorithms for feedforward neural networks are investigated analytically. The back-propagation algorithm described by Werbos (1974), Parker (1985), and Rumelhart et al. (1986) is generalized by redefining the values of the input and output neurons as probabilities. The synaptic weights are then varied to follow gradients in the logarithm of likelihood rather than in the error. This modification is shown to provide a more rigorous theoretical basis for the algorithm and to permit more accurate predictions. A typical application involving a medical-diagnosis expert system is discussed.

  19. Distributed process manager for an engineering network computer

    SciTech Connect

    Gait, J.

    1987-08-01

    MP is a manager for systems of cooperating processes in a local area network of engineering workstations. MP supports transparent continuation by maintaining multiple copies of each process on different workstations. Computational bandwidth is optimized by executing processes in parallel on different workstations. Responsiveness is high because workstations compete among themselves to respond to requests. The technique is to select a master from among a set of replicates of a process by a competitive election between the copies. Migration of the master when a fault occurs or when response slows down is effected by inducing the election of a new master. Competitive response stabilizes system behavior under load, so MP exhibits realtime behaviors.

  20. A Streaming Content Distribution Network for E-Learning Support

    ERIC Educational Resources Information Center

    Esteve, M.; Molina, B.; Palau, C.; Fortino, G.

    2006-01-01

    To date e-Learning material has usually been accessed and delivered through a central web server. As the number of users, the amount of information, the frequency of accesses and the volume of data increase, together with the introduction of multimedia streaming applications, a decentralized content distribution architecture is necessary. In this…

  1. Distributed estimation of sensors position in underwater wireless sensor network

    NASA Astrophysics Data System (ADS)

    Zandi, Rahman; Kamarei, Mahmoud; Amiri, Hadi

    2016-05-01

    In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.

  2. Distributed multifunctional sensor network for composite structural state sensing

    NASA Astrophysics Data System (ADS)

    Qing, Xinlin P.; Wang, Yishou; Gao, Limin; Kumar, Amrita

    2012-04-01

    Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and strong designability. In order to take full advantages of composite materials, there is a need to develop an embeddable multifunctional sensing system to allow a structure to "feel" and "think" its structural state. In this paper, the concept of multifunctional sensor network integrated with a structure, similar to the human nervous system, has been developed. Different types of network sensors are permanently integrated within a composite structure to sense structural strain, temperature, moisture, aerodynamic pressure; monitor external impact on the structure; and detect structural damages. Utilizing this revolutionary concept, future composite structures can be designed and manufactured to provide multiple modes of information, so that the structures have the capabilities for intelligent sensing, environmental adaptation and multi-functionality. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the paper.

  3. Deployment of Distributed Applications in Wireless Sensor Networks

    PubMed Central

    Pilloni, Virginia; Atzori, Luigi

    2011-01-01

    The increase in computation and sensing capabilities as well as in battery duration of commercially available Wireless Sensors Network (WSN) nodes are making the paradigm of an horizontal ambient intelligence infrastructure feasible. Accordingly, the sensing, computing and communicating infrastructure is set with a programmable middleware that allows for quickly deploying different applications running on top of it so as to follow the changing ambient needs. In this scenario, we face the problem of setting up the desired application in complex scenarios with hundreds of nodes, which consists of identifying which actions should be performed by each of the nodes so as to satisfy the ambient needs while minimizing the application impact on the infrastructure battery lifetime. Accordingly, we approach the problem by considering every possible decomposition of the application’s sensing and computing operations into tasks to be assigned to each infrastructure component. The contribution of energy consumption due to the performance of each task is then considered to compute a cost function, allowing us to evaluate the viability of each deployment solution. Simulation results show that our framework results in considerable energy conservation with respect to sink-oriented or cluster-oriented deployment approaches, particularly for networks with high node densities, non-uniform energy consumption and initial energy, and complex actions. PMID:22164024

  4. Space-time signal processing for distributed pattern detection in sensor networks

    NASA Astrophysics Data System (ADS)

    Paffenroth, Randy C.; Du Toit, Philip C.; Scharf, Louis L.; Jayasumana, Anura P.; Banadara, Vidarshana; Nong, Ryan

    2012-05-01

    We present a theory and algorithm for detecting and classifying weak, distributed patterns in network data that provide actionable information with quantiable measures of uncertainty. Our work demonstrates the eectiveness of space-time inference on graphs, robust matrix completion, and second order analysis for the detection of distributed patterns that are not discernible at the level of individual nodes. Motivated by the importance of the problem, we are specically interested in detecting weak patterns in computer networks related to Cyber Situational Awareness. Our focus is on scenarios where the nodes (terminals, routers, servers, etc.) are sensors that provide measurements (of packet rates, user activity, central processing unit usage, etc.) that, when viewed independently, cannot provide a denitive determination of the underlying pattern, but when fused with data from across the network both spatially and temporally, the relevant patterns emerge. The approach is applicable to many types of sensor networks including computer networks, wireless networks, mobile sensor networks, and social networks, as well as in contexts such as databases and disease outbreaks.

  5. A simulation-optimisation approach for designing water distribution networks under multiple objectives

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Pham Van, Tinh; Müller, Ruben; Schütze, Niels

    2014-05-01

    Especially in arid and semi-arid regions, water distribution networks are of major importance for an integrated water resources management in order to convey water over long distances from sources to consumers. However, to design a network optimally is still a challenge which requires an appropriate determination of: (1) pipe/pump/tank characteristics - decision variables (2) cost/network reliability - objective functions including (3) a given set of constraints. Thereby, objective functions are contradicting, which means that by minimising costs network reliability is decreasing resulting in a higher risk of network failures. For solving this multi-objective design problem, a simulation-optimisation approach is developed. The approach couples a hydraulic network model (Epanet) with an optimiser, namely the covariance matrix adaptation evolution strategy (CMAES). The simulation-optimisation model is applied on international published benchmark cases for single and multi-objective optimisation and simultaneous optimisation of above mentioned decision variables as well as network layout. Results are encouraging. The proposed model performs with similar or better results, which means smaller costs and higher network reliability. Subsequently, the new model is applied for an optimal design and operation of a water distribution system to supply the coastal arid region of Al-Batinah (North of Oman) with water for agricultural production.

  6. Structure Learning and Statistical Estimation in Distribution Networks - Part II

    SciTech Connect

    Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

    2015-02-13

    Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/or line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.

  7. Epidemic threshold determined by the first moments of network with alternating degree distributions

    NASA Astrophysics Data System (ADS)

    Li, Kezan; Zhang, Haifeng; Fu, Xinchu; Ding, Yong; Small, Michael

    2015-02-01

    During the alternating day-night cycle, people have differing behavior and hence different connection patterns-such as going to work or home, shopping and so on. Hence, the true topological structure of human contact networks are not only time-varying but also exhibit certain distribution regularity. In this paper, we will investigate epidemic spreading on time-varying human contact networks, which follow one degree distribution during daytime, but another at night. Based on SIS (susceptible/infected/susceptible) propagation mechanism, we study the epidemic threshold of this network with alternating distributions. A surprising result is that for the discrete-time case the epidemic threshold is determined only by the first moments of the two alternating degree distributions, if the degree of each node is constant for all nights. A similar result is valid for the continuous-time case if the duration is sufficiently small. This work shows that the spreading dynamics of time-varying networks with alternating distributions is completely different from the widely studied case of static spreading networks.

  8. Impact Assessment of V2G on the Power Loss of Unbalanced Radial Distribution Network

    NASA Astrophysics Data System (ADS)

    Chukwu, Uwakwe Christian; Mahajan, Satish M.

    2013-08-01

    Electric distribution feeders are inherently unbalanced and therefore have potential for severe power loss. The penetration of vehicle-to-grid (V2G) into the distribution feeders is expected to impact the power losses in the system. This is a pressing issue since power loss affects the operations, economics, and quality of service for the electric power systems. In this article, the impact of V2G parking lots on power losses of a radial distribution network is investigated. Two test networks were used in the study, namely: IEEE 13 and IEEE 123 Node test feeder networks. The test feeders and the V2G facilities were modeled in Radial Distribution Analysis Package (RDAP). Load flow results provided information on the power losses of the network. Results show that for a given penetration level, the impact of 3-phase and system-wide V2G integration on the power loss results in less power losses than 1-phase V2G integration. Results also indicate that operating the entire system such that V2G facilities will not compromise "near-balanced" state of operation and will have an improved impact on the power loss than highly unbalanced operation. The results obtained will be a useful tool for studying the impact of V2G on the power loss of a distribution network.

  9. Flow distribution in parallel microfluidic networks and its effect on concentration gradient.

    PubMed

    Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N

    2015-09-01

    The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow

  10. System-wide power management control via clock distribution network

    DOEpatents

    Coteus, Paul W.; Gara, Alan; Gooding, Thomas M.; Haring, Rudolf A.; Kopcsay, Gerard V.; Liebsch, Thomas A.; Reed, Don D.

    2015-05-19

    An apparatus, method and computer program product for automatically controlling power dissipation of a parallel computing system that includes a plurality of processors. A computing device issues a command to the parallel computing system. A clock pulse-width modulator encodes the command in a system clock signal to be distributed to the plurality of processors. The plurality of processors in the parallel computing system receive the system clock signal including the encoded command, and adjusts power dissipation according to the encoded command.

  11. Application of a distributed network in computational fluid dynamic simulations

    NASA Technical Reports Server (NTRS)

    Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.; Deshpande, Ashish

    1994-01-01

    A general-purpose 3-D, incompressible Navier-Stokes algorithm is implemented on a network of concurrently operating workstations using parallel virtual machine (PVM) and compared with its performance on a CRAY Y-MP and on an Intel iPSC/860. The problem is relatively computationally intensive, and has a communication structure based primarily on nearest-neighbor communication, making it ideally suited to message passing. Such problems are frequently encountered in computational fluid dynamics (CDF), and their solution is increasingly in demand. The communication structure is explicitly coded in the implementation to fully exploit the regularity in message passing in order to produce a near-optimal solution. Results are presented for various grid sizes using up to eight processors.

  12. Global Observation Information Networking: Using the Distributed Image Spreadsheet (DISS)

    NASA Technical Reports Server (NTRS)

    Hasler, Fritz

    1999-01-01

    The DISS and many other tools will be used to present visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 ....... to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI Onyx Graphics-Supercomputers are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science and used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS.

  13. Robustness in Network Protocols and Distributed Applications of the Internet

    NASA Astrophysics Data System (ADS)

    Vogel, Jürgen; Widmer, Jörg

    The Internet connects computers from all over the world for a fast and reliable exchange of data, e.g., from e-mail or Web applications. Considering its sheer size and heterogeneity, the Internet is the most complex computer system ever built. It has coped with a tremendous growth, has handled many critical situations, and, overall, does work quite well. This is because robustness was a major goal from the very beginning, which led to a network design that is self-regulatory, redundant, scalable, and updatable. In this chapter, we will discuss these design principles and the Internet's architecture, the core protocols IP and TCP, protocols for wireless communication, and applications such as the popular BitTorrent file exchange.

  14. Efficiently passing messages in distributed spiking neural network simulation

    PubMed Central

    Thibeault, Corey M.; Minkovich, Kirill; O'Brien, Michael J.; Harris, Frederick C.; Srinivasa, Narayan

    2013-01-01

    Efficiently passing spiking messages in a neural model is an important aspect of high-performance simulation. As the scale of networks has increased so has the size of the computing systems required to simulate them. In addition, the information exchange of these resources has become more of an impediment to performance. In this paper we explore spike message passing using different mechanisms provided by the Message Passing Interface (MPI). A specific implementation, MVAPICH, designed for high-performance clusters with Infiniband hardware is employed. The focus is on providing information about these mechanisms for users of commodity high-performance spiking simulators. In addition, a novel hybrid method for spike exchange was implemented and benchmarked. PMID:23772213

  15. Autonomous Distributed Congestion Control Scheme in WCDMA Network

    NASA Astrophysics Data System (ADS)

    Ahmad, Hafiz Farooq; Suguri, Hiroki; Choudhary, Muhammad Qaisar; Hassan, Ammar; Liaqat, Ali; Khan, Muhammad Umer

    Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.

  16. Investigation of transient overvoltages in heavily meshed low-voltage underground distribution networks

    NASA Astrophysics Data System (ADS)

    Salcedo Ulerio, Reynaldo Odalis

    The analysis of overvoltages in electrical distribution networks is of considerable significance since they may damage the power system infrastructure and the associated electrical equipment. Overvoltages in distribution networks arise due to switching transients, resonance, lightning strikes and ground faults, among other causes. The operation of network protectors (NWP), low voltage circuit breakers with directional power relay, in a secondary network prevents the continuous flow of reverse power. There are three modes of operation for the network protectors: sensitive, time delayed, and insensitive. In case of a fault, although all of the network protectors sense the fault at the same time, their operation is not simultaneous. Many of them open very quickly with opening times similar to those of the feeder breaker. However, some operate a few cycles later, others take several seconds to open and a few might even fail to operate. Therefore, depending on the settings of the network protectors, faults can last for significantly long time due to backfeeding of current from the low voltage (LV) network into the medium voltage (MV) network. In this work, low voltages are defined as 208V/460V and medium voltage are defined as 25kV/35kV. This thesis presents overvoltages which arise because of the occurrence of a single-line-to-ground (SLG) fault on the MV side (connected in delta) of the system. The thesis reveals that overvoltage stresses are imposed on insulation, micro-processor controlled equipment, and switching devices by overvoltages during current backfeeding. Also, it establishes a relationship between overvoltage magnitude, its duration, and the network loading conditions. Overvoltages above 3 p.u. may be developed as a result of a simultaneous occurrence of three phenomena: neutral displacement, Ferranti effect, and magnetic current chopping. Furthermore, this thesis exposes the possibility of occurrence of the ferro-resonance phenomena in a distribution

  17. Correlation between weighted spectral distribution and average path length in evolving networks.

    PubMed

    Jiao, Bo; Shi, Jianmai; Wu, Xiaoqun; Nie, Yuanping; Huang, Chengdong; Du, Jing; Zhou, Ying; Guo, Ronghua; Tao, Yerong

    2016-02-01

    The weighted spectral distribution (WSD) is a metric defined on the normalized Laplacian spectrum. In this study, synchronic random graphs are first used to rigorously analyze the metric's scaling feature, which indicates that the metric grows sublinearly as the network size increases, and the metric's scaling feature is demonstrated to be common in networks with Gaussian, exponential, and power-law degree distributions. Furthermore, a deterministic model of diachronic graphs is developed to illustrate the correlation between the slope coefficient of the metric's asymptotic line and the average path length, and the similarities and differences between synchronic and diachronic random graphs are investigated to better understand the correlation. Finally, numerical analysis is presented based on simulated and real-world data of evolving networks, which shows that the ratio of the WSD to the network size is a good indicator of the average path length. PMID:26931591

  18. A compensation-based power flow method for weakly meshed distribution and transmission networks

    SciTech Connect

    Shirmohammadi, D.; Hong, H.W.; Semlyen, A.; Luo, G.X.

    1988-05-01

    This paper describes a new power flow method for solving weakly meshed distribution and transmission networks, using a multi-port compensation technique and basic formulation of Kirchhoff's laws. This method has excellent convergence characteristics and is very robust. A computer program implementing this power flow solution scheme was developed and successfully applied to several practical distribution networks with radial and weakly meshed structure. This program was also successfully used for solving radial and weakly meshed transmission networks. The method can be applied to the solution of both the three-phase (unbalanced) and single-phase (balanced) representation of the network. In this paper, however, only the single phase representation is treated in detail.

  19. Correlation between weighted spectral distribution and average path length in evolving networks

    NASA Astrophysics Data System (ADS)

    Jiao, Bo; Shi, Jianmai; Wu, Xiaoqun; Nie, Yuanping; Huang, Chengdong; Du, Jing; Zhou, Ying; Guo, Ronghua; Tao, Yerong

    2016-02-01

    The weighted spectral distribution (WSD) is a metric defined on the normalized Laplacian spectrum. In this study, synchronic random graphs are first used to rigorously analyze the metric's scaling feature, which indicates that the metric grows sublinearly as the network size increases, and the metric's scaling feature is demonstrated to be common in networks with Gaussian, exponential, and power-law degree distributions. Furthermore, a deterministic model of diachronic graphs is developed to illustrate the correlation between the slope coefficient of the metric's asymptotic line and the average path length, and the similarities and differences between synchronic and diachronic random graphs are investigated to better understand the correlation. Finally, numerical analysis is presented based on simulated and real-world data of evolving networks, which shows that the ratio of the WSD to the network size is a good indicator of the average path length.

  20. Fibre optical measuring network based on quasi-distributed amplitude sensors for detecting deformation loads

    SciTech Connect

    Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S

    2013-02-28

    A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 - 10 kg with a sensitivity of 0.043 kg{sup -1}. (laser optics 2012)

  1. Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models

    PubMed Central

    Krivitsky, Pavel N.; Handcock, Mark S.; Raftery, Adrian E.; Hoff, Peter D.

    2009-01-01

    Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does. PMID:20191087

  2. Space Network Time Distribution and Synchronization Protocol Development for Mars Proximity Link

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Gao, Jay L.; Mills, David

    2010-01-01

    Time distribution and synchronization in deep space network are challenging due to long propagation delays, spacecraft movements, and relativistic effects. Further, the Network Time Protocol (NTP) designed for terrestrial networks may not work properly in space. In this work, we consider the time distribution protocol based on time message exchanges similar to Network Time Protocol (NTP). We present the Proximity-1 Space Link Interleaved Time Synchronization (PITS) algorithm that can work with the CCSDS Proximity-1 Space Data Link Protocol. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and duplication which underlying protocol mechanisms provide.

  3. Optimal design of water distribution networks by a discrete state transition algorithm

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaojun; Gao, David Y.; Simpson, Angus R.

    2016-04-01

    In this study it is demonstrated that, with respect to model formulation, the number of linear and nonlinear equations involved in water distribution networks can be reduced to the number of closed simple loops. Regarding the optimization technique, a discrete state transition algorithm (STA) is introduced to solve several cases of water distribution networks. Firstly, the focus is on a parametric study of the 'restoration probability and risk probability' in the dynamic STA. To deal effectively with head pressure constraints, the influence is then investigated of the penalty coefficient and search enforcement on the performance of the algorithm. Based on the experience gained from training the Two-Loop network problem, a discrete STA has successfully achieved the best known solutions for the Hanoi, triple Hanoi and New York network problems.

  4. Stiffening of Individual Fibrin Fibers Equitably Distributes Strain and Strengthens Networks

    PubMed Central

    Hudson, Nathan E.; Houser, John R.; O'Brien, E. Timothy; Taylor, Russell M.; Superfine, Richard; Lord, Susan T.; Falvo, Michael R.

    2010-01-01

    Abstract As the structural backbone of blood clots, fibrin networks carry out the mechanical task of stemming blood flow at sites of vascular injury. These networks exhibit a rich set of remarkable mechanical properties, but a detailed picture relating the microscopic mechanics of the individual fibers to the overall network properties has not been fully developed. In particular, how the high strain and failure characteristics of single fibers affect the overall strength of the network is not known. Using a combined fluorescence/atomic force microscope nanomanipulation system, we stretched 2-D fibrin networks to the point of failure, while recording the strain of individual fibers. Our results were compared to a pair of model networks: one composed of linearly responding elements and a second of nonlinear, strain-stiffening elements. We find that strain-stiffening of the individual fibers is necessary to explain the pattern of strain propagation throughout the network that we observe in our experiments. Fiber strain-stiffening acts to distribute strain more equitably within the network, reduce strain maxima, and increase network strength. Along with its physiological implications, a detailed understanding of this strengthening mechanism may lead to new design strategies for engineered polymeric materials. PMID:20409484

  5. A Network-Aware Distributed Storage Cache for Data Intensive Environments

    SciTech Connect

    Tierney, B.L.; Lee, J.R.; Johnston, W.E.; Crowley, B.; Holding, M.

    1999-12-23

    Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data at multiple sites around the world. The technologies, the middleware services, and the architectures that are used to build useful high-speed, wide area distributed systems, constitute the field of data intensive computing. In this paper the authors describe an architecture for data intensive applications where they use a high-speed distributed data cache as a common element for all of the sources and sinks of data. This cache-based approach provides standard interfaces to a large, application-oriented, distributed, on-line, transient storage system. They describe their implementation of this cache, how they have made it network aware, and how they do dynamic load balancing based on the current network conditions. They also show large increases in application throughput by access to knowledge of the network conditions.

  6. The European ALMA Regional Centre Network: A Geographically Distributed User Support Model

    NASA Astrophysics Data System (ADS)

    Hatziminaoglou, E.; Zwaan, M.; Andreani, P.; Barta, M.; Bertoldi, F.; Brand, J.; Gueth, F.; Hogerheijde, M.; Maercker, M.; Massardi, M.; Muehle, S.; Muxlow, Th.; Richards, A.; Schilke, P.; Tilanus, R.; Vlemmings, W.; Afonso, J.; Messias, H.

    2015-12-01

    In recent years there has been a paradigm shift from centralised to geographically distributed resources. Individual entities are no longer able to host or afford the necessary expertise in-house, and, as a consequence, society increasingly relies on widespread collaborations. Although such collaborations are now the norm for scientific projects, more technical structures providing support to a distributed scientific community without direct financial or other material benefits are scarce. The network of European ALMA Regional Centre (ARC) nodes is an example of such an internationally distributed user support network. It is an organised effort to provide the European ALMA user community with uniform expert support to enable optimal usage and scientific output of the ALMA facility. The network model for the European ARC nodes is described in terms of its organisation, communication strategies and user support.

  7. Distributed Grooming in Multi-Domain IP/MPLS-DWDM Networks

    SciTech Connect

    Liu, Qing

    2009-12-01

    This paper studies distributed multi-domain, multilayer provisioning (grooming) in IP/MPLS-DWDM networks. Although many multi-domain studies have emerged over the years, these have primarily considered 'homogeneous' network layers. Meanwhile, most grooming studies have assumed idealized settings with 'global' link state across all layers. Hence there is a critical need to develop practical distributed grooming schemes for real-world networks consisting of multiple domains and technology layers. Along these lines, a detailed hierarchical framework is proposed to implement inter-layer routing, distributed grooming, and setup signaling. The performance of this solution is analyzed in detail using simulation studies and future work directions are also high-lighted.

  8. Diffusion-Based EM Algorithm for Distributed Estimation of Gaussian Mixtures in Wireless Sensor Networks

    PubMed Central

    Weng, Yang; Xiao, Wendong; Xie, Lihua

    2011-01-01

    Distributed estimation of Gaussian mixtures has many applications in wireless sensor network (WSN), and its energy-efficient solution is still challenging. This paper presents a novel diffusion-based EM algorithm for this problem. A diffusion strategy is introduced for acquiring the global statistics in EM algorithm in which each sensor node only needs to communicate its local statistics to its neighboring nodes at each iteration. This improves the existing consensus-based distributed EM algorithm which may need much more communication overhead for consensus, especially in large scale networks. The robustness and scalability of the proposed approach can be achieved by distributed processing in the networks. In addition, we show that the proposed approach can be considered as a stochastic approximation method to find the maximum likelihood estimation for Gaussian mixtures. Simulation results show the efficiency of this approach. PMID:22163956

  9. Data fusion on a distributed heterogeneous sensor network

    NASA Astrophysics Data System (ADS)

    Lamborn, Peter; Williams, Pamela J.

    2006-04-01

    Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials' decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials' responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

  10. A cognitive information processing framework for distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Wang, Feiyi; Qi, Hairong

    2004-09-01

    In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

  11. Data fusion on a distributed heterogeneous sensor network.

    SciTech Connect

    Lamborn, Peter; Williams, Pamela J.

    2006-02-01

    Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

  12. Distributed sensor network for local-area atmospheric modeling

    NASA Astrophysics Data System (ADS)

    French, Patrick D.; Lovell, John S.; Seaman, Nelson L.

    2003-09-01

    In the event of a Weapons of Mass Destruction (WMD) chemical or radiological release, quick identification of the nature and source of the release can support efforts to warn, protect and evacuate threatened populations downwind; mitigate the release; provide more accurate plume forecasting; and collect critical transient evidence to help identify the perpetrator(s). Although there are systems available to assist in tracking a WMD release and then predicting where a plume may be traveling, there are no reliable systems available to determine the source location of that release. This would typically require the timely deployment of a remote sensing capability, a grid of expendable air samplers, or a surface sampling plan if the plume has dissipated. Each of these typical solutions has major drawbacks (i.e.: excessive cost, technical feasibility, duration to accomplish, etc...). This paper presents data to support the use of existing rapid-response meteorological modeling coupled with existing transport and diffusion modeling along with a prototype cost-effective situational awareness monitor which would reduce the sensor network requirements while still accomplishing the overall mission of having a 95% probability in converging on a source location within 100 meters.

  13. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

    PubMed

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

  14. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks

    PubMed Central

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S.

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the “critical degree” (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

  15. Network effects across the earnings distribution: payoffs to visible and invisible job finding assistance.

    PubMed

    McDonald, Steve

    2015-01-01

    This study makes three critical contributions to the "Do Contacts Matter?" debate. First, the widely reported null relationship between informal job searching and wages is shown to be mostly the artifact of a coding error and sample selection restrictions. Second, previous analyses examined only active informal job searching without fully considering the benefits derived from unsolicited network assistance (the "invisible hand of social capital") - thereby underestimating the network effect. Third, wage returns to networks are examined across the earnings distribution. Longitudinal data from the NLSY reveal significant wage returns for network-based job finding over formal job searching, especially for individuals who were informally recruited into their jobs (non-searchers). Fixed effects quantile regression analyses show that contacts generate wage premiums among middle and high wage jobs, but not low wage jobs. These findings challenge conventional wisdom on contact effects and advance understanding of how social networks affect wage attainment and inequality. PMID:25432620

  16. A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Srivastava, Ashok N.

    2009-01-01

    This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

  17. Modeling solute transport in distribution networks with variable demand and time step sizes.

    SciTech Connect

    Peyton, Chad E.; Bilisoly, Roger Lee; Buchberger, Steven G.; McKenna, Sean Andrew; Yarrington, Lane

    2004-06-01

    The effect of variable demands at short time scales on the transport of a solute through a water distribution network has not previously been studied. We simulate flow and transport in a small water distribution network using EPANET to explore the effect of variable demand on solute transport across a range of hydraulic time step scales from 1 minute to 2 hours. We show that variable demands at short time scales can have the following effects: smoothing of a pulse of tracer injected into a distribution network and increasing the variability of both the transport pathway and transport timing through the network. Variable demands are simulated for these different time step sizes using a previously developed Poisson rectangular pulse (PRP) demand generator that considers demand at a node to be a combination of exponentially distributed arrival times with log-normally distributed intensities and durations. Solute is introduced at a tank and at three different network nodes and concentrations are modeled through the system using the Lagrangian transport scheme within EPANET. The transport equations within EPANET assume perfect mixing of the solute within a parcel of water and therefore physical dispersion cannot occur. However, variation in demands along the solute transport path contribute to both removal and distortion of the injected pulse. The model performance measures examined are the distribution of the Reynolds number, the variation in the center of mass of the solute across time, and the transport path and timing of the solute through the network. Variation in all three performance measures is greatest at the shortest time step sizes. As the scale of the time step increases, the variability in these performance measures decreases. The largest time steps produce results that are inconsistent with the results produced by the smaller time steps.

  18. Exponential stability preservation in discrete-time analogues of artificial neural networks with distributed delays

    NASA Astrophysics Data System (ADS)

    Mohamad, Sannay

    2008-05-01

    This paper demonstrates that there is a discrete-time analogue which does not require any restriction on the size of the time-step in order to preserve the exponential stability of an artificial neural network with distributed delays. The analysis exploits an appropriate Lyapunov sequence and a discrete-time system of Halanay inequalities, and also either a Young inequality or a geometric-arithmetic mean inequality, to derive several sufficient conditions on the network parameters for the exponential stability of the analogue. The sufficiency conditions are independent of the time-step, and they correspond to those that establish the exponential stability of the continuous-time network.

  19. Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven

    2010-05-01

    Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.

  20. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

    PubMed

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states. PMID:26283956

  1. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states

    PubMed Central

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states. PMID:26283956

  2. Management Intelligence in Service-Level Reconfiguration of Distributed Network Applications

    NASA Astrophysics Data System (ADS)

    Ravindran, K.

    The paper is on generic service-level management tools that enable the reconfiguration of a distributed network application whenever there are resource-level changes or failures in the underlying network sub-systems. A network service is provided to applications through a protocol module, with the latter exercising network infrastructure resources in a manner to meet the application-level QoS specs. Application requests for a network service instantiate the protocol module with parameters specified at the service interface level, along with a prescription of critical properties to be enforced. At run-time, a management module monitors the service compliance to application-prescribed requirements, and notifies the application if a QoS degradation is detected. In our model, the management entity uses policy scripts and rules to coordinate the application-level reconfigurations and adaptations in response to the changes/outages in underlying network services. Our management model is independent of the specifics of problem-domain, which lowers the software development costs of distributed applications through 'reuse' of the management module. The paper presents a case study of rate-adaptive video multicast over IP networks, to demonstrate the usefulness of our model.

  3. OCEAN-PC and a distributed network for ocean data

    NASA Technical Reports Server (NTRS)

    Mclain, Douglas R.

    1992-01-01

    The Intergovernmental Oceanographic Commission (IOC) wishes to develop an integrated software package for oceanographic data entry and access in developing countries. The software, called 'OCEAN-PC', would run on low cost PC microcomputers and would encourage and standardize: (1) entry of local ocean observations; (2) quality control of the local data; (3) merging local data with historical data; (4) improved display and analysis of the merged data; and (5) international data exchange. OCEAN-PC will link existing MS-DOS oceanographic programs and data sets with table-driven format conversions. Since many ocean data sets are now being distributed on optical discs (Compact Discs - Read Only Memory, CD-ROM, Mass et al. 1987), OCEAN-PC will emphasize access to CD-ROMs.

  4. Degree Distribution of Position-Dependent Ball-Passing Networks in Football Games

    NASA Astrophysics Data System (ADS)

    Narizuka, Takuma; Yamamoto, Ken; Yamazaki, Yoshihiro

    2015-08-01

    We propose a simple stochastic model describing the position-dependent ball-passing network in football (soccer) games. In this network, a player in a certain area in a divided field is a node, and a pass between two nodes corresponds to an edge. Our stochastic process model is characterized by the consecutive choice of a node depending on its intrinsic fitness. We derive an explicit expression for the degree distribution and find that the derived distribution reproduces that for actual data reasonably well.

  5. Characterizing short-term stability for Boolean networks over any distribution of transfer functions

    NASA Astrophysics Data System (ADS)

    Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; Mayo, Jackson R.; Armstrong, Robert C.

    2016-07-01

    We present a characterization of short-term stability of Kauffman's N K (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness.

  6. Subcarrier Wave Quantum Key Distribution in Telecommunication Network with Bitrate 800 kbit/s

    NASA Astrophysics Data System (ADS)

    Gleim, A. V.; Nazarov, Yu. V.; Egorov, V. I.; Smirnov, S. V.; Bannik, O. I.; Chistyakov, V. V.; Kynev, S. M.; Anisimov, A. A.; Kozlov, S. A.; Vasiliev, V. N.

    2015-09-01

    In the course of work on creating the first quantum communication network in Russia we demonstrated quantum key distribution in metropolitan optical network infrastructure. A single-pass subcarrier wave quantum cryptography scheme was used in the experiments. BB84 protocol with strong reference was chosen for performing key distribution. The registered sifted key rate in an optical cable with 1.5 dB loss was 800 Kbit/s. Signal visibility exceeded 98%, and quantum bit error rate value was 1%. The achieved result is a record for this type of systems.

  7. Broadband ubiquitous femto-cell network with MIMO distributed antenna system over WDM-PON

    NASA Astrophysics Data System (ADS)

    Iwatsuki, Katsumi; Tashiro, Takayoshi; Hara, Kazutaka; Taniguchi, Tomohiro; Kani, Jun-ichi; Yoshimoto, Naoto; Miyamoto, Kenji; Nishiumi, Tatsuya; Higashino, Takeshi; Tsukamoto, Katsutoshi; Komaki, Shozo

    2011-01-01

    We describe a novel architecture of broadband ubiquitous femto-cell network with MIMO distributed antenna systems accommodated in WDM-PON. A technical convergence of WDM-PON and time division multiplexed RoF techniques can realize the universality of base stations with various types of broadband air interfaces, the increase of wireless access throughput, and the scalability of service area covered by MIMO distributed antenna systems. We discuss the configuration of MIMO antenna systems, transmission scheme of MIMO RF signals over WDM-PON, and configurations of center station and base stations. The preliminary experiments of proposed network architecture are demonstrated.

  8. Characterizing short-term stability for Boolean networks over any distribution of transfer functions.

    PubMed

    Seshadhri, C; Smith, Andrew M; Vorobeychik, Yevgeniy; Mayo, Jackson R; Armstrong, Robert C

    2016-07-01

    We present a characterization of short-term stability of Kauffman's NK (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness. PMID:27575142

  9. Optical-network-connected multi-channel 96-GHz-band distributed radar system

    NASA Astrophysics Data System (ADS)

    Kanno, Atsushi; Kuri, Toshiaki; Kawanishi, Tetsuya

    2015-05-01

    The millimeter-wave (MMW) radar is a promising candidate for high-precision imaging because of its short wavelength and broad range of available bandwidths. In particular in the frequency range of 92-100 GHz, which is regulated for radiolocation, an atmospheric attenuation coefficient less than 1 dB/km limits the imaging range. Therefore, a combination of MMW radar and distributed antenna system directly connected to optical fiber networks can realize both high-precision imaging and large-area surveillance. In this paper, we demonstrate a multi-channel MMW frequency-modulated continuous-wave distributed radar system connected to an analog radio-over-fiber network.

  10. Distributed Permafrost Observation Network in Western Alaska: the First Results

    NASA Astrophysics Data System (ADS)

    Romanovsky, V. E.; Cable, W.; Marchenko, S. S.; Panda, S. K.

    2014-12-01

    The area of Western Alaska including the Selawik National Wildlife Refuge (SNWR) is generally underrepresented in terms of permafrost thermal monitoring. Thus, the main objective of this study was to establish a permafrost monitoring network in Western Alaska in order to understand the spatial variability in permafrost thermal regime in the area and to have a baseline in order to detect future change. Present and future thawing of permafrost in the region will have a dramatic effect on the ecosystems and infrastructure because the permafrost here generally has a high ice content, as a result of preservation of old ground ice in these relatively cold regions even during the warmer time intervals of the Holocene. Over the summers of 2011 and 2012 a total of 26 automated monitoring stations were established to collect temperature data from the active layer and near-surface permafrost. While most of these stations were basic and only measured the temperature down to 1.5 m at 4 depths, three of the stations had higher vertical temperature resolution down to 3 m. The sites were selected using an ecotype (basic vegetation groups) map of very high resolution (30 m) that had been created for the area in 2009. We found the Upland Dwarf Birch-Tussock Shrub ecotype to be the coldest with a mean annual ground temperature at 1 meter (MAGT1.0) of -3.9 °C during the August 1st, 2012 to July 31st, 2013 measurement period. This is also the most widespread ecotype in the SNWR, covering approximately 28.4% by area. The next widespread ecotype in the SNWR is the Lowland and Upland Birch-Ericaceous Low Shrub. This ecotype had higher ground temperatures with an average MAGT1.0 of -2.4 °C during the same measurement period. We also found that within some ecotypes (White Spruce and Alder-Willow Shrub) the presence or absence of moss on the surface seems to indicate the presence or absence of near surface permafrost. In general, we found good agreement between ecotype classes and

  11. A Distributed Transmission Rate Adjustment Algorithm in Heterogeneous CSMA/CA Networks

    PubMed Central

    Xie, Shuanglong; Low, Kay Soon; Gunawan, Erry

    2015-01-01

    Distributed transmission rate tuning is important for a wide variety of IEEE 802.15.4 network applications such as industrial network control systems. Such systems often require each node to sustain certain throughput demand in order to guarantee the system performance. It is thus essential to determine a proper transmission rate that can meet the application requirement and compensate for network imperfections (e.g., packet loss). Such a tuning in a heterogeneous network is difficult due to the lack of modeling techniques that can deal with the heterogeneity of the network as well as the network traffic changes. In this paper, a distributed transmission rate tuning algorithm in a heterogeneous IEEE 802.15.4 CSMA/CA network is proposed. Each node uses the results of clear channel assessment (CCA) to estimate the busy channel probability. Then a mathematical framework is developed to estimate the on-going heterogeneous traffics using the busy channel probability at runtime. Finally a distributed algorithm is derived to tune the transmission rate of each node to accurately meet the throughput requirement. The algorithm does not require modifications on IEEE 802.15.4 MAC layer and it has been experimentally implemented and extensively tested using TelosB nodes with the TinyOS protocol stack. The results reveal that the algorithm is accurate and can satisfy the throughput demand. Compared with existing techniques, the algorithm is fully distributed and thus does not require any central coordination. With this property, it is able to adapt to traffic changes and re-adjust the transmission rate to the desired level, which cannot be achieved using the traditional modeling techniques. PMID:25822140

  12. A model for the distribution of watermarked digital content on mobile networks

    NASA Astrophysics Data System (ADS)

    Frattolillo, Franco; D'Onofrio, Salvatore

    2006-10-01

    Although digital watermarking can be considered one of the key technologies to implement the copyright protection of digital contents distributed on the Internet, most of the content distribution models based on watermarking protocols proposed in literature have been purposely designed for fixed networks and cannot be easily adapted to mobile networks. On the contrary, the use of mobile devices currently enables new types of services and business models, and this makes the development of new content distribution models for mobile environments strategic in the current scenario of the Internet. This paper presents and discusses a distribution model of watermarked digital contents for such environments able to achieve a trade-off between the needs of efficiency and security.

  13. Size distribution and waiting times for the avalanches of the Cell Network Model of Fracture

    NASA Astrophysics Data System (ADS)

    Villalobos, Gabriel; Kun, Ferenc; Linero, Dorian L.; Muñoz, José D.

    2011-09-01

    The Cell Network Model is a fracture model recently introduced that resembles the microscopical structure and drying process of the parenchymatous tissue of the Bamboo Guadua angustifolia. The model exhibits a power-law distribution of avalanche sizes, with exponent -3.0 when the breaking thresholds are randomly distributed with uniform probability density. Hereby we show that the same exponent also holds when the breaking thresholds obey a broad set of Weibull distributions, and that the humidity decrements between successive avalanches (the equivalent to waiting times for this model) follow in all cases an exponential distribution. Moreover, the fraction of remaining junctures shows an exponential decay in time. In addition, introducing partial breakings and cumulative damages induces a crossover behavior between two power-laws in the histogram of avalanche sizes. This results support the idea that the Cell Network Model may be in the same universality class as the Random Fuse Model.

  14. A Study of Economical Incentives for Voltage Profile Control Method in Future Distribution Network

    NASA Astrophysics Data System (ADS)

    Tsuji, Takao; Sato, Noriyuki; Hashiguchi, Takuhei; Goda, Tadahiro; Tange, Seiji; Nomura, Toshio

    In a future distribution network, it is difficult to maintain system voltage because a large number of distributed generators are introduced to the system. The authors have proposed “voltage profile control method” using power factor control of distributed generators in the previous work. However, the economical disbenefit is caused by the active power decrease when the power factor is controlled in order to increase the reactive power. Therefore, proper incentives must be given to the customers that corporate to the voltage profile control method. Thus, in this paper, we develop a new rules which can decide the economical incentives to the customers. The method is tested in one feeder distribution network model and its effectiveness is shown.

  15. Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

    NASA Technical Reports Server (NTRS)

    Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

    2005-01-01

    Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

  16. An adaptive distributed data aggregation based on RCPC for wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Hua, Guogang; Chen, Chang Wen

    2006-05-01

    One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

  17. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    NASA Technical Reports Server (NTRS)

    Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

    2011-01-01

    Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

  18. Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

    PubMed

    Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

    2015-01-01

    Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

  19. Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

    PubMed Central

    Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

    2015-01-01

    Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

  20. States of mind: Emotions, body feelings, and thoughts share distributed neural networks

    PubMed Central

    Oosterwijk, Suzanne; Lindquist, Kristen A.; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

    2012-01-01

    Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. PMID:22677148

  1. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    NASA Technical Reports Server (NTRS)

    Rahmani, Amirreza; Mesbahi, Mehran; Fathpour, Nanaz; Hadaegh, Fred Y.

    2008-01-01

    In this work, we develop an approach to formation estimation by explicitly characterizing formation's system-theoretic attributes in terms of the underlying inter-spacecraft information-exchange network. In particular, we approach the formation observer/estimator design by relaxing the accessibility to the global state information by a centralized observer/estimator- and in turn- providing an analysis and synthesis framework for formation observers/estimators that rely on local measurements. The noveltyof our approach hinges upon the explicit examination of the underlying distributed spacecraft network in the realm of guidance, navigation, and control algorithmic analysis and design. The overarching goal of our general research program, some of whose results are reported in this paper, is the development of distributed spacecraft estimation algorithms that are scalable, modular, and robust to variations inthe topology and link characteristics of the formation information exchange network. In this work, we consider the observability of a spacecraft formation from a single observation node and utilize the agreement protocol as a mechanism for observing formation states from local measurements. Specifically, we show how the symmetry structure of the network, characterized in terms of its automorphism group, directly relates to the observability of the corresponding multi-agent system The ramification of this notion of observability over networks is then explored in the context of distributed formation estimation.

  2. Innovation flow through social networks: productivity distribution in France and Italy

    NASA Astrophysics Data System (ADS)

    di Matteo, T.; Aste, T.; Gallegati, M.

    2005-10-01

    From a detailed empirical analysis of the productivity of non financial firms across several countries and years we show that productivity follows a non-Gaussian distribution with `fat tails' in the large productivity region which are well mimicked by power law behaviors. We discuss how these empirical findings can be linked to a mechanism of exchanges in a social network where firms improve their productivity by direct innovation and/or by imitation of other firm's technological and organizational solutions. The type of network-connectivity determines how fast and how efficiently information can diffuse and how quickly innovation will permeate or behaviors will be imitated. From a model for innovation flow through a complex network we show that the expectation values of the productivity of each firm are proportional to its connectivity in the network of links between firms. The comparison with the empirical distributions in France and Italy reveals that in this model, such a network must be of a scale-free type with a power-law degree distribution in the large connectivity range.

  3. Fundamentally Distributed Information Processing Integrates the Motor Network into the Mental Workspace during Mental Rotation.

    PubMed

    Schlegel, Alexander; Konuthula, Dedeepya; Alexander, Prescott; Blackwood, Ethan; Tse, Peter U

    2016-08-01

    The manipulation of mental representations in the human brain appears to share similarities with the physical manipulation of real-world objects. In particular, some neuroimaging studies have found increased activity in motor regions during mental rotation, suggesting that mental and physical operations may involve overlapping neural populations. Does the motor network contribute information processing to mental rotation? If so, does it play a similar computational role in both mental and manual rotation, and how does it communicate with the wider network of areas involved in the mental workspace? Here we used multivariate methods and fMRI to study 24 participants as they mentally rotated 3-D objects or manually rotated their hands in one of four directions. We find that information processing related to mental rotations is distributed widely among many cortical and subcortical regions, that the motor network becomes tightly integrated into a wider mental workspace network during mental rotation, and that motor network activity during mental rotation only partially resembles that involved in manual rotation. Additionally, these findings provide evidence that the mental workspace is organized as a distributed core network that dynamically recruits specialized subnetworks for specific tasks as needed. PMID:27054403

  4. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. PMID:25683347

  5. A Novel Searching Method for Distribution Network Topology to Maximize Outputs of PV Clusters

    NASA Astrophysics Data System (ADS)

    Sato, Tsunaki; Saitoh, Hiroumi

    This paper proposes a novel searching method for radial distribution network to maximize outputs of PV generators. When a lot of PV generators are connected to distribution network, it is necessary to control PV outputs to keep the voltage within the regulated range of power quality. The aim of the paper is to find the optimal topology, that is the state of section switches so as to maximize the total PV outputs. This problem becomes a combinatorial optimization one and the exhaustive search results in enormous computation time. In this paper, a novel searching method is proposed which is based on the replacement of the complex combinatorial optimization problem with a minimization problem regarding with voltage profile of distribution network. The features of the proposed method are to utilize the relation between the total outputs of PV generators and the voltage profile, the superposition of radial electric circuit and a sequential algorithm for search in an optimal topology. In order to verify the proposed method, the comparison study has been done by using two distribution network models. As the result, there is possibility that the proposed method can find sub optimal topology in a short time compared with tabu search approach.

  6. Unified Framework for Deriving Simultaneous Equation Algorithms for Water Distribution Networks

    EPA Science Inventory

    The known formulations for steady state hydraulics within looped water distribution networks are re-derived in terms of linear and non-linear transformations of the original set of partly linear and partly non-linear equations that express conservation of mass and energy. All of ...

  7. LandScape Command Set: Local Area Network Distributed Supervisory Control and Programming Environment

    SciTech Connect

    Burchard, R.L.; Small, D.E.

    1999-01-01

    This paper presents the Local Area Network Distributed Supervisory Control and Programming Environment (LandScape) commands set that provides a Generic Device Subsystem Application Programmers Interface (API). These commands are implemented using the Common Object Request Broker Architecture (CORBA) specification with Orbix from Iona Technologies.

  8. Developing A Modeling Tool for Flow Profiling in Irrigation Distribution Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Efforts are underway to rehabilitate the irrigation districts, such as in the Rio Grande River Basin in Texas. Water distribution network models are needed to help prioritize and analyze various rehabilitation options, as well as to scientifically quantify irrigation water demands, usages, and losse...

  9. Modeling Multiple Human-Automation Distributed Systems using Network-form Games

    NASA Technical Reports Server (NTRS)

    Brat, Guillaume

    2012-01-01

    The paper describes at a high-level the network-form game framework (based on Bayes net and game theory), which can be used to model and analyze safety issues in large, distributed, mixed human-automation systems such as NextGen.

  10. TALON - The Telescope Alert Operation Network System : intelligent linking of distributed autonomous robotic telescopes

    SciTech Connect

    White, R. R.; Wren, J.; Davis, H. R.; Galassi, M. C.; Starr, D. L.; Vestrand, W. T.; Wozniak, P. R.

    2004-01-01

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in instrumentation. Utilizing the internet for communicating between distributed astronomical systems is still in its infancy, but it already shows great potential. Here we present an example of a distributed network of telescopes that performs more efficienfiy in synchronous operation than as individual instruments. RAPid Telescopes for Optical Response (RAPTOR) is a system of telescopes at LANL that has intelligent intercommunication, combined with wide-field optics, temporal monitoring software, and deep-field follow-up capability all working in closed-loop real-time operation. The Telescope ALert Operations Network (TALON) is a network server that allows intercommunication of alert triggers from external and internal resources and controls the distribution of these to each of the telescopes on the network. TALON is designed to grow, allowing any number of telescopes to be linked together and communicate. Coupled with an intelligent alert client at each telescope, it can analyze and respond to each distributed TALON alert based on the telescopes needs and schedule.

  11. Variable-Length Message Transmission for Distributed Loop Computer Networks (Part I).

    ERIC Educational Resources Information Center

    Reames, C. C.; Liu, M. T.

    An introduction to the problems of variable-length message transmission in distributed loop computer networks, with a summary of previous accomplishments in the area, begins this technically-oriented document. An improved technique, overcoming some of the inadequacies in presently used techniques, is proposed together with a conceptual model of…

  12. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks

    EPA Science Inventory

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Wate...

  13. Scatter search heuristic for least-cost design of water distribution networks

    NASA Astrophysics Data System (ADS)

    Lin, Min-Der; Liu, Yu-Hsin; Liu, Gee-Fon; Chu, Chien-Wei

    2007-10-01

    The optimization problems of water distribution networks are complex, multi-modal and discrete-variable problems that cannot be easily solved with conventional optimization algorithms. Heuristic algorithms such as genetic algorithms, simulated annealing, tabu search and ant colony optimization have been extensively employed over the last decade. This article proposed an optimization procedure based on the scatter search (SS) framework, which is also a heuristic algorithm, to obtain the least-cost designs of three well-known looped water distribution networks (two-loop, Hanoi and New York networks). The computational results obtained with the three benchmark instances indicate that SS is able to find solutions comparable to those provided by some of the most competitive algorithms published in the literature.

  14. Video distribution techniques over WiMAX networks for m-Health applications.

    PubMed

    Markarian, Garik; Mihaylova, Lyudmila; Tsitserov, Dmitry V; Zvikhachevskaya, A

    2012-01-01

    In this paper, we propose a novel approach for video distribution over IEEE 802.16 networks for mobile Healthcare (m-Health) applications. The technique incorporates resource distribution, scheduling, and content-aware video streaming taking advantage of a flexible quality of service functionality offered by IEEE 802.16/WiMAX technology. The proposed technique is thoroughly investigated using network simulator software under various real-life m-Health scenarios, which include streaming video over medium access control layer service connections. It is shown that the technique is fully compatible with the WiMAX standard specification and allows a 9-16% increase in the overall network throughput, which is dependent upon the initial system configuration and the selection of WiMAX user parameters. PMID:22057065

  15. An extended clique degree distribution and its heterogeneity in cooperation-competition networks

    NASA Astrophysics Data System (ADS)

    Feng, Ai-Xia; Fu, Chun-Hua; Xu, Xiu-Lian; Zhou, Yue-Ping; Chang, Hui; Wang, Jian; He, Da-Ren; Feng, Guo-Lin

    2012-04-01

    After Xiao et al. [W.-K. Xiao, J. Ren, F. Qi, Z.W. Song, M.X. Zhu, H.F. Yang, H.Y. Jin, B.-H. Wang, Tao Zhou, Empirical study on clique-degree distribution of networks, Phys. Rev. E 76 (2007) 037102], in this article we present an investigation on so-called k-cliques, which are defined as complete subgraphs of k (k>1) nodes, in the cooperation-competition networks described by bipartite graphs. In the networks, the nodes named actors are taking part in events, organizations or activities, named acts. We mainly examine a property of a k-clique called “k-clique act degree”, q, defined as the number of acts, in which the k-clique takes part. Our analytic treatment on a cooperation-competition network evolution model demonstrates that the distribution of k-clique act degrees obeys Mandelbrot distribution, P(q)∝(. To validate the analytical model, we have further studied 13 different empirical cooperation-competition networks with the clique numbers k=2 and k=3. Empirical investigation results show an agreement with the analytic derivations. We propose a new “heterogeneity index”, H, to describe the heterogeneous degree distributions of k-clique and heuristically derive the correlation between H and α and γ. We argue that the cliques, which take part in the largest number of acts, are the most important subgraphs, which can provide a new criterion to distinguish important cliques in the real world networks.

  16. Field demonstration of a continuous-variable quantum key distribution network.

    PubMed

    Huang, Duan; Huang, Peng; Li, Huasheng; Wang, Tao; Zhou, Yingming; Zeng, Guihua

    2016-08-01

    We report on what we believe is the first field implementation of a continuous-variable quantum key distribution (CV-QKD) network with point-to-point configuration. Four QKD nodes are deployed on standard communication infrastructures connected with commercial telecom optical fiber. Reliable key exchange is achieved in the wavelength-division-multiplexing CV-QKD network. The impact of a complex and volatile field environment on the excess noise is investigated, since excess noise controlling and reduction is arguably the major issue pertaining to distance and the secure key rate. We confirm the applicability and verify the maturity of the CV-QKD network in a metropolitan area, thus paving the way for a next-generation global secure communication network. PMID:27472606

  17. Distributed coupling complexity in a weakly coupled oscillatory network with associative properties

    NASA Astrophysics Data System (ADS)

    Kostorz, Kathrin; Hölzel, Robert W.; Krischer, Katharina

    2013-08-01

    We present a novel architecture of an oscillatory neural network capable of performing pattern recognition tasks. Two established strategies for obtaining associative properties in oscillatory networks invoke either a physical, time constant or a global, dynamical all-to-all coupling. Our network distributes the complexity of the coupling between the spatial and the temporal domain. Instead of {O}(N^2) physical connections or a global connection with {O}(N^2) frequency components, each of the N oscillators receives an individual coupling signal which is composed of N - 1 frequency components. We demonstrate that such a network can be built with analog electronic oscillators and possesses reliable pattern recognition properties. Theoretical analysis shows that the scalability is in fact superior to the dynamic global coupling approach, while its physical complexity is greatly reduced compared to the individual time constant coupling.

  18. Measurement-Device-Independent Quantum Key Distribution over Untrustful Metropolitan Network

    NASA Astrophysics Data System (ADS)

    Tang, Yan-Lin; Yin, Hua-Lei; Zhao, Qi; Liu, Hui; Sun, Xiang-Xiang; Huang, Ming-Qi; Zhang, Wei-Jun; Chen, Si-Jing; Zhang, Lu; You, Li-Xing; Wang, Zhen; Liu, Yang; Lu, Chao-Yang; Jiang, Xiao; Ma, Xiongfeng; Zhang, Qiang; Chen, Teng-Yun; Pan, Jian-Wei

    2016-01-01

    Quantum cryptography holds the promise to establish an information-theoretically secure global network. All field tests of metropolitan-scale quantum networks to date are based on trusted relays. The security critically relies on the accountability of the trusted relays, which will break down if the relay is dishonest or compromised. Here, we construct a measurement-device-independent quantum key distribution (MDIQKD) network in a star topology over a 200-square-kilometer metropolitan area, which is secure against untrustful relays and against all detection attacks. In the field test, our system continuously runs through one week with a secure key rate 10 times larger than previous results. Our results demonstrate that the MDIQKD network, combining the best of both worlds—security and practicality, constitutes an appealing solution to secure metropolitan communications.

  19. Belief-propagation algorithm and the Ising model on networks with arbitrary distributions of motifs

    NASA Astrophysics Data System (ADS)

    Yoon, S.; Goltsev, A. V.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2011-10-01

    We generalize the belief-propagation algorithm to sparse random networks with arbitrary distributions of motifs (triangles, loops, etc.). Each vertex in these networks belongs to a given set of motifs (generalization of the configuration model). These networks can be treated as sparse uncorrelated hypergraphs in which hyperedges represent motifs. Here a hypergraph is a generalization of a graph, where a hyperedge can connect any number of vertices. These uncorrelated hypergraphs are treelike (hypertrees), which crucially simplifies the problem and allows us to apply the belief-propagation algorithm to these loopy networks with arbitrary motifs. As natural examples, we consider motifs in the form of finite loops and cliques. We apply the belief-propagation algorithm to the ferromagnetic Ising model with pairwise interactions on the resulting random networks and obtain an exact solution of this model. We find an exact critical temperature of the ferromagnetic phase transition and demonstrate that with increasing the clustering coefficient and the loop size, the critical temperature increases compared to ordinary treelike complex networks. However, weak clustering does not change the critical behavior qualitatively. Our solution also gives the birth point of the giant connected component in these loopy networks.

  20. Estimating interevent time distributions from finite observation periods in communication networks

    NASA Astrophysics Data System (ADS)

    Kivelä, Mikko; Porter, Mason A.

    2015-11-01

    A diverse variety of processes—including recurrent disease episodes, neuron firing, and communication patterns among humans—can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.

  1. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC.

    PubMed

    Anandaraj, M; Ganeshkumar, P; Vijayakumar, K P; Selvaraj, K

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10-15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  2. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC

    PubMed Central

    Anandaraj, M.; Ganeshkumar, P.; Vijayakumar, K. P.; Selvaraj, K.

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10–15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  3. A Rule-Based and Hypertextual Electronic Mail System for Electronic Learning Environments: Applying the Distributed Network Learning Framework.

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Levin, James A.

    This paper discusses issues related to the design of software tools that support learners in their participation in network-based learning activities. To guide the development and use of a new class of educationally-oriented network tools, this paper proposes a cognitively-based, distributed network learning framework (DNLF). This framework has…

  4. Development, Testing and Installation of a Superconducting Fault Current Limiter for Medium Voltage Distribution Networks

    NASA Astrophysics Data System (ADS)

    Martini, Luciano; Bocchi, Marco; Ascade, Massimo; Valzasina, Angelo; Rossi, Valerio; Angeli, Giuliano; Ravetta, Cesare

    Since 2009 Ricerca sul Sistema Energetico (RSE S.p.A.) has been involved in the design of resistive-type Superconducting Fault Current Limiter (SFCL) for MV applications to be installed in the A2A Reti Elettriche S.p.A distribution grid in the Milano area. The project started with simulations, design and testing activities for a singlephase device; in this paper we report on the successive step, which is concerned with developing, testing and installation at the hosting utility of the final three-phase SFCL prototype. The result of this research activity is a resistive-type 9 kV/3.4 MVA SFCL device, based on first generation (1G) BSCCO tapes, developed by RSE in the framework of a R&D national project. Owing to the positive test results of partial discharge, dielectric and shortcircuit results the three-phase SFCL device is being to be installed in the A2A distribution grid in the Milano area and it is going to be soon energized starting a one-year long field-testing activity.

  5. 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.

  6. DCPVP: distributed clustering protocol using voting and priority for wireless sensor networks.

    PubMed

    Hematkhah, Hooman; Kavian, Yousef S

    2015-01-01

    This paper presents a new clustering protocol for designing energy-efficient hierarchical wireless sensor networks (WSNs) by dividing the distributed sensor network into virtual sensor groups to satisfy the scalability and prolong the network lifetime in large-scale applications. The proposed approach is a distributed clustering protocol called DCPVP, which is based on voting and priority ideas. In the DCPVP protocol, the size of clusters is based on the distance of nodes from the data link such as base station (BS) and the local node density. The cluster heads are elected based on the mean distance from neighbors, remaining energy and the times of being elected as cluster head. The performance of the DCPVP protocol is compared with some well-known clustering protocols in literature such as the LEACH, HEED, WCA, GCMRA and TCAC protocols. The simulation results confirm that the prioritizing- and voting-based election ideas decrease the construction time and the energy consumption of clustering progress in sensor networks and consequently improve the lifetime of networks with limited resources and battery powered nodes in harsh and inaccessible environments. PMID:25763646

  7. Report on NSF/ARO/ONR Workshop on Distributed Camera Networks: Research Challenges and Future Directions

    NASA Astrophysics Data System (ADS)

    Bhanu, Bir; Roy Chowdhury, Amit

    Large-scale video networks are becoming increasingly important for a wide range of critical applications. The development of automated techniques for aggregating and interpreting information from multiple video streams in large-scale networks in real-life scenarios is very challenging. Research in video sensor networks is highly interdisciplinary and requires expertise from a variety of fields. The goal of this effort was to organize a two-day nationally recognized workshop in the domain of camera networks that brings together leading researchers from academia, industry and the government. The workshop was held at the University of California at Riverside on May 11-12, 2009. The workshop was attended by 75 participants. The workshop was sponsored by the US National Science Foundation, US Army Research Office and US Office of Naval Research. The workshop addressed critical interdisciplinary challenges at the intersection of large-scale video camera networks and distributed sensing, processing, communication and control; distributed video understanding; embedded real-time systems; graphics and simulation; and education. The recommendations of the workshop are summarized in the following order of topics: Video Processing and Video Understanding

  8. A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks.

    PubMed

    Xu, Yang; Hu, Xuemei; Hu, Haixiao; Liu, Ming

    2016-01-01

    In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors' local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption. PMID:27537891

  9. DCPVP: Distributed Clustering Protocol Using Voting and Priority for Wireless Sensor Networks

    PubMed Central

    Hematkhah, Hooman; Kavian, Yousef S.

    2015-01-01

    This paper presents a new clustering protocol for designing energy-efficient hierarchical wireless sensor networks (WSNs) by dividing the distributed sensor network into virtual sensor groups to satisfy the scalability and prolong the network lifetime in large-scale applications. The proposed approach is a distributed clustering protocol called DCPVP, which is based on voting and priority ideas. In the DCPVP protocol, the size of clusters is based on the distance of nodes from the data link such as base station (BS) and the local node density. The cluster heads are elected based on the mean distance from neighbors, remaining energy and the times of being elected as cluster head. The performance of the DCPVP protocol is compared with some well-known clustering protocols in literature such as the LEACH, HEED, WCA, GCMRA and TCAC protocols. The simulation results confirm that the prioritizing- and voting-based election ideas decrease the construction time and the energy consumption of clustering progress in sensor networks and consequently improve the lifetime of networks with limited resources and battery powered nodes in harsh and inaccessible environments. PMID:25763646

  10. Distributed estimation based on covariances under network-induced phenomena described by random measurement matrices

    NASA Astrophysics Data System (ADS)

    Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

    2016-07-01

    Recursive distributed filtering and fixed-point smoothing algorithms are proposed from measurements through sensor networks perturbed by random parameter matrices and additive noises. The proposed observation model provides a unified framework to consider some network-induced random phenomena. Using an innovation approach, intermediate distributed optimal least-squares (LS) linear estimators are firstly obtained at each sensor node, processing the available output measurements, not only from the own sensor but also from its neighbouring sensors according to the network topology. After that, the proposed distributed estimators are designed at each node as the LS matrix-weighted linear combination of the intermediate estimators within its neighbourhood. The proposed algorithms use only covariance information and do not require the state-space model of the signal. To compare the accuracy of the estimators, recursive expressions for the estimation error covariance matrices are also derived. A simulation example shows the effectiveness of the proposed estimation algorithms and some of the network-induced uncertainties covered by the observation model with random parameter matrices considered in this paper.

  11. Multiagent systems and neural networks of a distributed architecture for target identification of air images

    NASA Astrophysics Data System (ADS)

    Cozien, Roger F.; Rosenberger, Christophe; Eyherabide, Partrick; Rossettini, Joaquim; Ceyrolle, Arnaud

    2000-10-01

    Our purpose is, in medium term, to detect in air images, characteristic shapes and objects such as airports, industrial plants, planes, tanks, truck, ... with great accuracy and low rate of mistakes. However, we also want to value whether the link between neural networks and multi- agents systems is relevant and effective. If it appears to be really effective, we hope to use this kind of technology in other fields. That would be an easy and convenient way to depict and to use the agents' knowledge which is distributed and fragmented. After a first phase of preliminary tests to know if agents are able to give relevant information to a neural network, we verify that only a few agents running on an image are enough to inform the network and let it generalize the agents' distributed and fragmented knowledge. In a second phase, we developed a distributed architecture allowing several multi- agents systems running at the same time on different computers with different images. All those agents send information to a multi neural networks system whose job is to identify the shapes detected by the agents. The name we gave to our project is Jarod.

  12. Convergence dynamics of hybrid bidirectional associative memory neural networks with distributed delays

    NASA Astrophysics Data System (ADS)

    Liao, Xiaofeng; Wong, Kwok-Wo; Yang, Shizhong

    2003-09-01

    In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results.

  13. Establish a Data Transmission Platform of the Rig Based on the Distributed Network

    NASA Astrophysics Data System (ADS)

    Bao, Zefu; Li, Tao

    In order to control in real-time ,closed-loop feedback the information, saving the money and labor,we distribute a platform of network data. It through the establishment of the platform in the oil drilling to achieve the easiest route of each device of the rig that conveying timely. The design proposed the platform to transfer networking data by PA which allows the rig control for optimal use. Against the idea,achieving first through on-site cabling and the establishment of data transmission module in the rig monitoring system. The results of standard field application show that the platform solve the problem of rig control.

  14. Robustness of a distributed neural network controller for locomotion in a hexapod robot

    NASA Technical Reports Server (NTRS)

    Chiel, Hillel J.; Beer, Randall D.; Quinn, Roger D.; Espenschied, Kenneth S.

    1992-01-01

    A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

  15. A growth model for directed complex networks with power-law shape in the out-degree distribution

    NASA Astrophysics Data System (ADS)

    Esquivel-Gómez, J.; Stevens-Navarro, E.; Pineda-Rico, U.; Acosta-Elias, J.

    2015-01-01

    Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1.

  16. A growth model for directed complex networks with power-law shape in the out-degree distribution.

    PubMed

    Esquivel-Gómez, J; Stevens-Navarro, E; Pineda-Rico, U; Acosta-Elias, J

    2015-01-01

    Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1. PMID:25567141

  17. A growth model for directed complex networks with power-law shape in the out-degree distribution

    PubMed Central

    Esquivel-Gómez, J.; Stevens-Navarro, E.; Pineda-Rico, U.; Acosta-Elias, J.

    2015-01-01

    Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1. PMID:25567141

  18. Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks

    PubMed Central

    Meller, Laura; Cabeza, Mar; Pironon, Samuel; Barbet-Massin, Morgane; Maiorano, Luigi; Georges, Damien; Thuiller, Wilfried

    2014-01-01

    Aim Conservation planning exercises increasingly rely on species distributions predicted either from one particular statistical model or, more recently, from an ensemble of models (i.e. ensemble forecasting). However, it has not yet been explored how different ways of summarizing ensemble predictions affect conservation planning outcomes. We evaluate these effects and compare commonplace consensus methods, applied before the conservation prioritization phase, to a novel method that applies consensus after reserve selection. Location Europe. Methods We used an ensemble of predicted distributions of 146 Western Palaearctic bird species in alternative ways: four different consensus methods, as well as distributions discounted with variability, were used to produce inputs for spatial conservation prioritization. In addition, we developed and tested a novel method, in which we built 100 datasets by sampling the ensemble of predicted distributions, ran a conservation prioritization analysis on each of them and averaged the resulting priority ranks. We evaluated the conservation outcome against three controls: (i) a null control, based on random ranking of cells; (2) the reference solution, based on an expert-refined dataset; and (3) the independent solution, based on an independent dataset. Results Networks based on predicted distributions were more representative of rare species than randomly selected networks. Alternative methods to summarize ensemble predictions differed in representativeness of resulting reserve networks. Our novel method resulted in better representation of rare species than pre-selection consensus methods. Main conclusions Retaining information about the variation in the predicted distributions throughout the conservation prioritization seems to provide better results than summarizing the predictions before conservation prioritization. Our results highlight the need to understand and consider model-based uncertainty when using predicted

  19. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    PubMed Central

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  20. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.

    PubMed

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  1. Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

    PubMed Central

    Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

    2016-01-01

    Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

  2. Numerical simulation of fibrous biomaterials with randomly distributed fiber network structure.

    PubMed

    Jin, Tao; Stanciulescu, Ilinca

    2016-08-01

    This paper presents a computational framework to simulate the mechanical behavior of fibrous biomaterials with randomly distributed fiber networks. A random walk algorithm is implemented to generate the synthetic fiber network in 2D used in simulations. The embedded fiber approach is then adopted to model the fibers as embedded truss elements in the ground matrix, which is essentially equivalent to the affine fiber kinematics. The fiber-matrix interaction is partially considered in the sense that the two material components deform together, but no relative movement is considered. A variational approach is carried out to derive the element residual and stiffness matrices for finite element method (FEM), in which material and geometric nonlinearities are both included. Using a data structure proposed to record the network geometric information, the fiber network is directly incorporated into the FEM simulation without significantly increasing the computational cost. A mesh sensitivity analysis is conducted to show the influence of mesh size on various simulation results. The proposed method can be easily combined with Monte Carlo (MC) simulations to include the influence of the stochastic nature of the network and capture the material behavior in an average sense. The computational framework proposed in this work goes midway between homogenizing the fiber network into the surrounding matrix and accounting for the fully coupled fiber-matrix interaction at the segment length scale, and can be used to study the connection between the microscopic structure and the macro-mechanical behavior of fibrous biomaterials with a reasonable computational cost. PMID:26342926

  3. Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks.

    PubMed

    Guo, Kehua; Zhang, Ping; Ma, Jianhua

    2016-01-01

    Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

  4. Volitional regulation of emotions produces distributed alterations in connectivity between visual, attention control, and default networks.

    PubMed

    Sripada, Chandra; Angstadt, Michael; Kessler, Daniel; Phan, K Luan; Liberzon, Israel; Evans, Gary W; Welsh, Robert C; Kim, Pilyoung; Swain, James E

    2014-04-01

    The ability to volitionally regulate emotions is critical to health and well-being. While patterns of neural activation during emotion regulation have been well characterized, patterns of connectivity between regions remain less explored. It is increasingly recognized that the human brain is organized into large-scale intrinsic connectivity networks (ICNs) whose interrelationships are altered in characteristic ways during psychological tasks. In this fMRI study of 54 healthy individuals, we investigated alterations in connectivity within and between ICNs produced by the emotion regulation strategy of reappraisal. In order to gain a comprehensive picture of connectivity changes, we utilized connectomic psychophysiological interactions (PPI), a whole-brain generalization of standard single-seed PPI methods. In particular, we quantified PPI connectivity pair-wise across 837 ROIs placed throughout the cortex. We found that compared to maintaining one's emotional responses, engaging in reappraisal produced robust and distributed alterations in functional connections involving visual, dorsal attention, frontoparietal, and default networks. Visual network in particular increased connectivity with multiple ICNs including dorsal attention and default networks. We interpret these findings in terms of the role of these networks in mediating critical constituent processes in emotion regulation, including visual processing, stimulus salience, attention control, and interpretation and contextualization of stimuli. Our results add a new network perspective to our understanding of the neural underpinnings of emotion regulation, and highlight that connectomic methods can play a valuable role in comprehensively investigating modulation of connectivity across task conditions. PMID:24246489

  5. Distributed Information Compression for Target Tracking in Cluster-Based Wireless Sensor Networks.

    PubMed

    Liao, Shi-Kuan; Lai, Kai-Jay; Tsai, Hsiao-Ping; Wen, Chih-Yu

    2016-01-01

    Target tracking is a critical wireless sensor application, which involves signal and information processing technologies. In conventional target position estimation methods, an estimate is usually demonstrated by an average target position. In contrast, this work proposes a distributed information compression method to describe the measurement uncertainty of tracking problems in cluster-based wireless sensor networks. The leader-based information processing scheme is applied to perform target positioning and energy conservation. A two-level hierarchical network topology is adopted for energy-efficient target tracking with information compression. A Level 1 network architecture is a cluster-based network topology for managing network operations. A Level 2 network architecture is an event-based and leader-based topology, utilizing the concept of information compression to process the estimates of sensor nodes. The simulation results show that compared to conventional schemes, the proposed data processing scheme has a balanced system performance in terms of tracking accuracy, data size for transmission and energy consumption. PMID:27338417

  6. Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation.

    PubMed

    Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D; Halko, Mark

    2016-01-01

    Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

  7. Distributive routing and congestion control in wireless multihop ad hoc communication networks

    NASA Astrophysics Data System (ADS)

    Glauche, Ingmar; Krause, Wolfram; Sollacher, Rudolf; Greiner, Martin

    2004-10-01

    Due to their inherent complexity, engineered wireless multihop ad hoc communication networks represent a technological challenge. Having no mastering infrastructure the nodes have to selforganize themselves in such a way that for example network connectivity, good data traffic performance and robustness are guaranteed. In this contribution the focus is on routing and congestion control. First, random data traffic along shortest path routes is studied by simulations as well as theoretical modeling. Measures of congestion like end-to-end time delay and relaxation times are given. A scaling law of the average time delay with respect to network size is revealed and found to depend on the underlying network topology. In the second step, a distributive routing and congestion control is proposed. Each node locally propagates its routing cost estimates and information about its congestion state to its neighbors, which then update their respective cost estimates. This allows for a flexible adaptation of end-to-end routes to the overall congestion state of the network. Compared to shortest-path routing, the critical network load is significantly increased.

  8. Distributed Information Compression for Target Tracking in Cluster-Based Wireless Sensor Networks

    PubMed Central

    Liao, Shi-Kuan; Lai, Kai-Jay; Tsai, Hsiao-Ping; Wen, Chih-Yu

    2016-01-01

    Target tracking is a critical wireless sensor application, which involves signal and information processing technologies. In conventional target position estimation methods, an estimate is usually demonstrated by an average target position. In contrast, this work proposes a distributed information compression method to describe the measurement uncertainty of tracking problems in cluster-based wireless sensor networks. The leader-based information processing scheme is applied to perform target positioning and energy conservation. A two-level hierarchical network topology is adopted for energy-efficient target tracking with information compression. A Level 1 network architecture is a cluster-based network topology for managing network operations. A Level 2 network architecture is an event-based and leader-based topology, utilizing the concept of information compression to process the estimates of sensor nodes. The simulation results show that compared to conventional schemes, the proposed data processing scheme has a balanced system performance in terms of tracking accuracy, data size for transmission and energy consumption. PMID:27338417

  9. Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks

    PubMed Central

    Guo, Kehua; Zhang, Ping; Ma, Jianhua

    2016-01-01

    Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

  10. Distributed hydrological modeling with channel network flow of a forestry drained peatland site

    NASA Astrophysics Data System (ADS)

    Haahti, Kersti; Warsta, Lassi; Kokkonen, Teemu; Younis, Bassam A.; Koivusalo, Harri

    2016-01-01

    Peatland drainage has been an important component of forestry management in the boreal zone and the resulting ditch networks are maintained regularly to sustain forest productivity. In Finland, this is recognized as the most detrimental forestry practice increasing diffuse loads of suspended solids. Alongside forestry management on peatlands, interest in peatland restoration has grown lately. Distributed hydrological modeling has the potential to address these matters by recognizing relevant physical mechanisms and identifying most suitable strategies for mitigating undesired outcomes. This study investigates the utility of such a modeling approach in a drained peatland forest environment. To provide a suitable tool for this purpose, we coupled channel network flow to the three-dimensional distributed hydrological model FLUSH. The resulting model was applied to a 5.2 ha drained peatland forest catchment in Eastern Finland. The model was calibrated and validated using field measurements obtained over frost-free periods of five months. The application showed that distributed modeling can disentangle the importance of spatial factors on local soil moisture conditions, which is significant as peatland drainage aims to control these conditions. In our application, we limited the spatial aspect to the topography and the drainage network, and found that the drainage configuration had a clear effect on the spatial soil moisture patterns but that the effect was less pronounced during the wetter summer. Future applications of distributed modeling in this field comprises investigating the impacts of other spatial factors, modeling channel erosion and solid transport to address strategies for their mitigation, and evaluating restoration schemes.

  11. Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications

    PubMed Central

    2015-01-01

    Background Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. Objectives The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. Methods Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. Results All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R 2 values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). Conclusions This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns

  12. MaxEnt analysis of a water distribution network in Canberra, ACT, Australia

    NASA Astrophysics Data System (ADS)

    Waldrip, Steven H.; Niven, Robert K.; Abel, Markus; Schlegel, Michael; Noack, Bernd R.

    2015-01-01

    A maximum entropy (MaxEnt) method is developed to infer the state of a pipe flow network, for situations in which there is insufficient information to form a closed equation set. This approach substantially extends existing deterministic methods for the analysis of engineered flow networks (e.g. Newton's method or the Hardy Cross scheme). The network is represented as an undirected graph structure, in which the uncertainty is represented by a continuous relative entropy on the space of internal and external flow rates. The head losses (potential differences) on the network are treated as dependent variables, using specified pipe-flow resistance functions. The entropy is maximised subject to "observable" constraints on the mean values of certain flow rates and/or potential differences, and also "physical" constraints arising from the frictional properties of each pipe and from Kirchhoff's nodal and loop laws. A numerical method is developed in Matlab for solution of the integral equation system, based on multidimensional quadrature. Several nonlinear resistance functions (e.g. power-law and Colebrook) are investigated, necessitating numerical solution of the implicit Lagrangian by a double iteration scheme. The method is applied to a 1123-node, 1140-pipe water distribution network for the suburb of Torrens in the Australian Capital Territory, Australia, using network data supplied by water authority ACTEW Corporation Limited. A number of different assumptions are explored, including various network geometric representations, prior probabilities and constraint settings, yielding useful predictions of network demand and performance. We also propose this methodology be used in conjunction with in-flow monitoring systems, to obtain better inferences of user consumption without large investments in monitoring equipment and maintenance.

  13. Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing

    NASA Astrophysics Data System (ADS)

    Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.

    2006-05-01

    Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.

  14. Scaling of weighted spectral distribution in deterministic scale-free networks

    NASA Astrophysics Data System (ADS)

    Jiao, Bo; Nie, Yuan-ping; Shi, Jian-mai; Huang, Cheng-dong; Zhou, Ying; Du, Jing; Guo, Rong-hua; Tao, Ye-rong

    2016-06-01

    Scale-free networks are abundant in the real world. In this paper, we investigate the scaling properties of the weighted spectral distribution in several deterministic and stochastic models of evolving scale-free networks. First, we construct a new deterministic scale-free model whose node degrees have a unified format. Using graph structure features, we derive a precise formula for the spectral metric in this model. This formula verifies that the spectral metric grows sublinearly as network size (i.e., the number of nodes) grows. Additionally, the mathematical reasoning of the precise formula theoretically provides detailed explanations for this scaling property. Finally, we validate the scaling properties of the spectral metric using some stochastic models. The experimental results show that this scaling property can be retained regardless of local world, node deleting and assortativity adjustment.

  15. Techniques for selecting topology and implementing the distributed control system network

    NASA Astrophysics Data System (ADS)

    Chernyi, S.

    2016-04-01

    On grounds of reviews devoted to flows analysis methods in the data processing networks within the automated control systems for the technological process and assessment of these methods by the selected set of requirements, one may make conclusion about expediency of using the combination of graph flow algorithms and the queuing theory. The outputs of the research concerning the impact of network dynamics on the drilling platform distributed system control quality prove the fact that the quality of the transient depends upon the frequency of discretization and intensity of flows. With increasing the intensity of flows, the static error of the control enlarges. It was concluded that in order to control the automation objects in the real-time mode it is required to minimize the delays in transmitting packets in the network.

  16. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network

    PubMed Central

    Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users. PMID:27367610

  17. A design testbed for distributed V/UHF networks with mobile terminals

    NASA Astrophysics Data System (ADS)

    Carnegie, Andrew

    A flexible design tool for mobile radio networks was implemented. Both low level areas such as modulation, coding, and synchronization, and high level techniques involving protocol details can be analyzed simultaneously. The simulation software is based on a Rayleigh fading channel model with a network layer protocol implementation. Described here is how a Rayleigh distribution can be generated and how it is used to implement the channel simulation by a conversion to a probability of error based on the modulation technique required. The network model is discussed with reference to the OSI Open Systems Interconnection reference model, and the variable configuration is described. To access the success of the system, an investigation into the use of variable, optimum length packets is illustrated.

  18. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

    PubMed

    Yoon, Young; Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users. PMID:27367610

  19. Examining the Distribution, Modularity, and Community Structure in Article Networks for Systematic Reviews.

    PubMed

    Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

    2015-01-01

    Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization. PMID:26958292

  20. Intrusion-aware alert validation algorithm for cooperative distributed intrusion detection schemes of wireless sensor networks.

    PubMed

    Shaikh, Riaz Ahmed; Jameel, Hassan; d'Auriol, Brian J; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

    2009-01-01

    Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

  1. Design constraints for third-order PLL nodes in master-slave clock distribution networks

    NASA Astrophysics Data System (ADS)

    Bueno, A. M.; Rigon, A. G.; Ferreira, A. A.; Piqueira, José R. C.

    2010-09-01

    Clock signal distribution in telecommunication commercial systems usually adopts a master-slave architecture, with a precise time basis generator as a master and phase-locked loops (PLLs) as slaves. In the majority of the networks, second-order PLLs are adopted due to their simplicity and stability. Nevertheless, in some applications better transient responses are necessary and, consequently, greater order PLLs need to be used, in spite of the possibility of bifurcations and chaotic attractors. Here a master-slave network with third-order PLLs is analyzed and conditions for the stability of the synchronous state are derived, providing design constraints for the node parameters, in order to guarantee stability and reachability of the synchronous state for the whole network. Numerical simulations are carried out in order to confirm the analytical results.

  2. Examining the Distribution, Modularity, and Community Structure in Article Networks for Systematic Reviews

    PubMed Central

    Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

    2015-01-01

    Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization. PMID:26958292

  3. Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

    NASA Astrophysics Data System (ADS)

    Li, Peng; Olmi, Claudio; Song, Gangbing

    2010-04-01

    Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data

  4. Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks

    NASA Astrophysics Data System (ADS)

    Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang

    2016-01-01

    The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.

  5. Evolutionary prisoner's dilemma on Newman-Watts social networks with an asymmetric payoff distribution mechanism

    NASA Astrophysics Data System (ADS)

    Du, Wen-Bo; Cao, Xian-Bin; Yang, Han-Xin; Hu, Mao-Bin

    2010-01-01

    In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner's dilemma game (PDG) on Newman-Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α: if α > 0, the rich will exploit the poor to get richer; if α < 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with α and is remarkably promoted when α > 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system's wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.

  6. Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

    PubMed Central

    Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

    2014-01-01

    Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

  7. Optimal epidemic spreading on complex networks with heterogeneous waiting time distribution

    NASA Astrophysics Data System (ADS)

    Yang, Guan-Ling; Yang, Xinsong

    2016-04-01

    In this paper, the effects of heterogeneous waiting time on spreading dynamics is studied based on network-dependent information. A new non-Markovian susceptible-infected-susceptible (SIS) model is first proposed, in which node's waiting time is dependent on its degree and may be different from each other. Every node tries to transmit the epidemic to its neighbors after the waiting time. Moreover, by using the mean-field theory and numerical simulations, it is discovered that the epidemic threshold is correlated to the network topology and the distribution of the waiting time. Furthermore, our results reveal that an optimal distribution of the heterogeneous waiting time can suppress the epidemic spreading.

  8. XNsim: Internet-Enabled Collaborative Distributed Simulation via an Extensible Network

    NASA Technical Reports Server (NTRS)

    Novotny, John; Karpov, Igor; Zhang, Chendi; Bedrossian, Nazareth S.

    2007-01-01

    In this paper, the XNsim approach to achieve Internet-enabled, dynamically scalable collaborative distributed simulation capabilities is presented. With this approach, a complete simulation can be assembled from shared component subsystems written in different formats, that run on different computing platforms, with different sampling rates, in different geographic locations, and over singlelmultiple networks. The subsystems interact securely with each other via the Internet. Furthermore, the simulation topology can be dynamically modified. The distributed simulation uses a combination of hub-and-spoke and peer-topeer network topology. A proof-of-concept demonstrator is also presented. The XNsim demonstrator can be accessed at http://www.jsc.draver.corn/xn that hosts various examples of Internet enabled simulations.

  9. Knowledge-base browsing: an application of hybrid distributed/local connectionist networks

    NASA Astrophysics Data System (ADS)

    Samad, Tariq; Israel, Peggy

    1990-08-01

    We describe a knowledge base browser based on a connectionist (or neural network) architecture that employs both distributed and local representations. The distributed representations are used for input and output thereby enabling associative noise-tolerant interaction with the environment. Internally all representations are fully local. This simplifies weight assignment and facilitates network configuration for specific applications. In our browser concepts and relations in a knowledge base are represented using " microfeatures. " The microfeatures can encode semantic attributes structural features contextual information etc. Desired portions of the knowledge base can then be associatively retrieved based on a structured cue. An ordered list of partial matches is presented to the user for selection. Microfeatures can also be used as " bookmarks" they can be placed dynamically at appropriate points in the knowledge base and subsequently used as retrieval cues. A proof-of-concept system has been implemented for an internally developed Honeywell-proprietary knowledge acquisition tool. 1.

  10. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays.

    PubMed

    Guodong Zhang; Yi Shen; Quan Yin; Junwei Sun

    2015-01-01

    In this paper, based on the knowledge of memristor and recurrent neural networks (RNNs), the model of the memristor-based RNNs with discrete and distributed delays is established. By constructing proper Lyapunov functionals and using inequality technique, several sufficient conditions are given to ensure the passivity of the memristor-based RNNs with discrete and distributed delays in the sense of Filippov solutions. The passivity conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. In addition, the results of this paper complement and extend the earlier publications. Finally, numerical simulations are employed to illustrate the effectiveness of the obtained results. PMID:25462633

  11. The origin of the criticality in meme popularity distribution on complex networks

    NASA Astrophysics Data System (ADS)

    Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

    2016-03-01

    Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks.

  12. The origin of the criticality in meme popularity distribution on complex networks

    PubMed Central

    Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

    2016-01-01

    Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks. PMID:27009399

  13. The origin of the criticality in meme popularity distribution on complex networks.

    PubMed

    Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

    2016-01-01

    Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks. PMID:27009399

  14. Local Community Mining on Distributed and Dynamic Networks From a Multiagent Perspective.

    PubMed

    Bu, Zhan; Wu, Zhiang; Cao, Jie; Jiang, Yichuan

    2016-04-01

    Distributed and dynamic networks are ubiquitous in many real-world applications. Due to the huge-scale, decentralized, and dynamic characteristics, the global topological view is either too hard to obtain or even not available. So, most existing community detection methods working on the global view fail to handle such decentralized and dynamic large networks. In this paper, we propose a novel autonomy-oriented computing-based method for community mining (AOCCM) from the multiagent perspective in the distributed environment. In particular, AOCCM utilizes reactive agents to pick the neighborhood node with the largest structural similarity as the candidate node, and thus determine whether it should be added into local community based on the modularity gain. We further improve AOCCM to a more efficient incremental version named AOCCM-i for mining communities from dynamic networks. AOCCM and AOCCM-i can be easily expanded to detect both nonoverlapping and overlapping global community structures. Experimental results on real-life networks demonstrate that the proposed methods can reduce the computational cost by avoiding repeated structural similarity calculation and can still obtain the high-quality communities. PMID:26087512

  15. A Distributed Multiagent System Architecture for Body Area Networks Applied to Healthcare Monitoring

    PubMed Central

    Laza, Rosalía; Pereira, António

    2015-01-01

    In the last years the area of health monitoring has grown significantly, attracting the attention of both academia and commercial sectors. At the same time, the availability of new biomedical sensors and suitable network protocols has led to the appearance of a new generation of wireless sensor networks, the so-called wireless body area networks. Nowadays, these networks are routinely used for continuous monitoring of vital parameters, movement, and the surrounding environment of people, but the large volume of data generated in different locations represents a major obstacle for the appropriate design, development, and deployment of more elaborated intelligent systems. In this context, we present an open and distributed architecture based on a multiagent system for recognizing human movements, identifying human postures, and detecting harmful activities. The proposed system evolved from a single node for fall detection to a multisensor hardware solution capable of identifying unhampered falls and analyzing the users' movement. The experiments carried out contemplate two different scenarios and demonstrate the accuracy of our proposal as a real distributed movement monitoring and accident detection system. Moreover, we also characterize its performance, enabling future analyses and comparisons with similar approaches. PMID:25874202

  16. SHD digital cinema distribution over a long distance network of Internet2

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Takahiro; Shirai, Daisuke; Fujii, Tatsuya; Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

    2003-06-01

    We have developed a prototype SHD (Super High Definition) digital cinema distribution system that can store, transmit and display eight-million-pixel motion pictures that have the image quality of a 35-mm film movie. The system contains a video server, a real-time decoder, and a D-ILA projector. Using a gigabit Ethernet link and TCP/IP, the server transmits JPEG2000 compressed motion picture data streams to the decoder at transmission speeds as high as 300 Mbps. The received data streams are decompressed by the decoder, and then projected onto a screen via the projector. With this system, digital cinema contents can be distributed over a wide-area optical gigabit IP network. However, when digital cinema contents are delivered over long distances by using a gigabit IP network and TCP, the round-trip time increases and network throughput either stops rising or diminishes. In a long-distance SHD digital cinema transmission experiment performed on the Internet2 network in October 2002, we adopted enlargement of the TCP window, multiple TCP connections, and shaping function to control the data transmission quantity. As a result, we succeeded in transmitting the SHD digital cinema content data at about 300 Mbps between Chicago and Los Angeles, a distance of more than 3000 km.

  17. A high performance long-reach passive optical network with a novel excess bandwidth distribution scheme

    NASA Astrophysics Data System (ADS)

    Chao, I.-Fen; Zhang, Tsung-Min

    2015-06-01

    Long-reach passive optical networks (LR-PONs) have been considered to be promising solutions for future access networks. In this paper, we propose a distributed medium access control (MAC) scheme over an advantageous LR-PON network architecture that reroutes the control information from and back to all ONUs through an (N + 1) × (N + 1) star coupler (SC) deployed near the ONUs, thereby overwhelming the extremely long propagation delay problem in LR-PONs. In the network, the control slot is designed to contain all bandwidth requirements of all ONUs and is in-band time-division-multiplexed with a number of data slots within a cycle. In the proposed MAC scheme, a novel profit-weight-based dynamic bandwidth allocation (P-DBA) scheme is presented. The algorithm is designed to efficiently and fairly distribute the amount of excess bandwidth based on a profit value derived from the excess bandwidth usage of each ONU, which resolves the problems of previously reported DBA schemes that are either unfair or inefficient. The simulation results show that the proposed decentralized algorithms exhibit a nearly three-order-of-magnitude improvement in delay performance compared to the centralized algorithms over LR-PONs. Moreover, the newly proposed P-DBA scheme guarantees low delay performance and fairness even when under attack by the malevolent ONU irrespective of traffic loads and burstiness.

  18. Distributed Signal Decorrelation and Detection in Multi View Camera Networks Using the Vector Sparse Matrix Transform.

    PubMed

    Bachega, Leonardo R; Hariharan, Srikanth; Bouman, Charles A; Shroff, Ness B

    2015-12-01

    This paper introduces the vector sparse matrix transform (vector SMT), a new decorrelating transform suitable for performing distributed processing of high-dimensional signals in sensor networks. We assume that each sensor in the network encodes its measurements into vector outputs instead of scalar ones. The proposed transform decorrelates a sequence of pairs of vector outputs, until these vectors are decorrelated. In our experiments, we simulate distributed anomaly detection by a network of cameras, monitoring a spatial region. Each camera records an image of the monitored environment from its particular viewpoint and outputs a vector encoding the image. Our results, with both artificial and real data, show that the proposed vector SMT transform effectively decorrelates image measurements from the multiple cameras in the network while maintaining low overall communication energy consumption. Since it enables joint processing of the multiple vector outputs, our method provides significant improvements to anomaly detection accuracy when compared with the baseline case when the images are processed independently. PMID:26415179

  19. A location-routing-inventory model for designing multisource distribution networks

    NASA Astrophysics Data System (ADS)

    Ahmadi-Javid, Amir; Seddighi, Amir Hossein

    2012-06-01

    This article studies a ternary-integration problem that incorporates location, inventory and routing decisions in designing a multisource distribution network. The objective of the problem is to minimize the total cost of location, routing and inventory. A mixed-integer programming formulation is first presented, and then a three-phase heuristic is developed to solve large-sized instances of the problem. The numerical study indicates that the proposed heuristic is both effective and efficient.

  20. A Lego Mindstorms NXT based test bench for multiagent exploratory systems and distributed network partitioning

    NASA Astrophysics Data System (ADS)

    Patil, Riya Raghuvir

    Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for selfpartitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the LegoRTM Mindstorms' NXT on a graphical programming platform using National Instruments' LabVIEW(TM) forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

  1. OpenSim: A Flexible Distributed Neural Network Simulator with Automatic Interactive Graphics.

    PubMed

    Jarosch, Andreas; Leber, Jean Francois

    1997-06-01

    An object-oriented simulator called OpenSim is presented that achieves a high degree of flexibility by relying on a small set of building blocks. The state variables and algorithms put in this framework can easily be accessed through a command shell. This allows one to distribute a large-scale simulation over several workstations and to generate the interactive graphics automatically. OpenSim opens new possibilities for cooperation among Neural Network researchers. Copyright 1997 Elsevier Science Ltd. PMID:12662864

  2. A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

    PubMed

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2015-01-01

    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. PMID:26287189

  3. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    SciTech Connect

    Gu, Z.; Rizy, D.T.

    1996-10-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks and a nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  4. Analysis of internal network requirements for the distributed Nordic Tier-1

    NASA Astrophysics Data System (ADS)

    Behrmann, G.; Fischer, L.; Gamst, M.; Grønager, M.; Kleist, J.

    2010-04-01

    The Tier-1 facility operated by the Nordic DataGrid Facility (NDGF) differs significantly from other Tier-1s in several aspects: It is not located at one or a few locations but instead distributed throughout the Nordic, it is not under the governance of a single organisation but but is instead build from resources under the control of a number of different national organisations. Being physically distributed makes the design and implementation of the networking infrastructure a challenge. NDGF has its own internal OPN connecting the sites participating in the distributed Tier-1. To assess the suitability of the network design and the capacity of the links, we present a model of the internal bandwidth needs for the NDGF Tier-1 and its associated Tier-2 sites. The model takes the different type of workloads into account and can handle different kinds of data management strategies. It has already been used to dimension the internal network structure of NDGF. We also compare the model with real life data measurements.

  5. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    SciTech Connect

    Gu, Z.; Rizy, D.T.

    1996-02-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks an d one nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  6. Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

    NASA Astrophysics Data System (ADS)

    Zheng, Yan

    2015-03-01

    Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

  7. Low-cost scalable TV/video on-demand distribution over telco networks

    NASA Astrophysics Data System (ADS)

    Cheung, Kwok-wai

    2005-02-01

    With the proliferation of IP networking and wireless access, local exchange carriers (LEC) are under tremendous pressure to evolve into broadband service providers. On-demand video distribution to the mass appears to be one of the best evolution paths for the LEC. Various approaches for providing on-demand content/video distribution to massive viewers are compared. In particular, a novel low-cost network architecture called DINA for distributing video content to massive viewers is described. DINA employs hybrid multicast-unicast streaming to achieve scalability. Furthermore, it offers full interactive functions to the viewers and readily deployable over existing broadband network infrastructures. An innovative technique to offer low-cost on-demand video services to massive subscribers called multi-stream multicasting is described. It employs fixed but irregular stream intervals that can significantly reduce the startup latency. Many fault protection mechanisms are built into the DINA architecture to improve the robustness. DINA also offers additional protection against copyright infringement and has been demonstrated commercially.

  8. A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks

    PubMed Central

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2015-01-01

    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. PMID:26287189

  9. Using hybrid angle/distance information for distributed topology control in vehicular sensor networks.

    PubMed

    Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

    2014-01-01

    In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

  10. Two-layer wireless distributed sensor/control network based on RF

    NASA Astrophysics Data System (ADS)

    Feng, Li; Lin, Yuchi; Zhou, Jingjing; Dong, Guimei; Xia, Guisuo

    2006-11-01

    A project of embedded Wireless Distributed Sensor/Control Network (WDSCN) based on RF is presented after analyzing the disadvantages of traditional measure and control system. Because of high-cost and complexity, such wireless techniques as Bluetooth and WiFi can't meet the needs of WDSCN. The two-layer WDSCN is designed based on RF technique, which operates in the ISM free frequency channel with low power and high transmission speed. Also the network is low cost, portable and moveable, integrated with the technologies of computer network, sensor, microprocessor and wireless communications. The two-layer network topology is selected in the system; a simple but efficient self-organization net protocol is designed to fit the periodic data collection, event-driven and store-and-forward. Furthermore, adaptive frequency hopping technique is adopted for anti-jamming apparently. The problems about power reduction and synchronization of data in wireless system are solved efficiently. Based on the discussion above, a measure and control network is set up to control such typical instruments and sensors as temperature sensor and signal converter, collect data, and monitor environmental parameters around. This system works well in different rooms. Experiment results show that the system provides an efficient solution to WDSCN through wireless links, with high efficiency, low power, high stability, flexibility and wide working range.

  11. Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud

    PubMed Central

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H.; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-01-01

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221

  12. Calibration of an outdoor distributed camera network with a 3D point cloud.

    PubMed

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-01-01

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221

  13. Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

    PubMed Central

    Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

    2014-01-01

    In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

  14. A hybrid deep neural network and physically based distributed model for river stage prediction

    NASA Astrophysics Data System (ADS)

    hitokoto, Masayuki; sakuraba, Masaaki

    2016-04-01

    We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network

  15. Dynamics of bacterial communities before and after distribution in a full-scale drinking water network.

    PubMed

    El-Chakhtoura, Joline; Prest, Emmanuelle; Saikaly, Pascal; van Loosdrecht, Mark; Hammes, Frederik; Vrouwenvelder, Hans

    2015-05-01

    Understanding the biological stability of drinking water distribution systems is imperative in the framework of process control and risk management. The objective of this research was to examine the dynamics of the bacterial community during drinking water distribution at high temporal resolution. Water samples (156 in total) were collected over short time-scales (minutes/hours/days) from the outlet of a treatment plant and a location in its corresponding distribution network. The drinking water is treated by biofiltration and disinfectant residuals are absent during distribution. The community was analyzed by 16S rRNA gene pyrosequencing and flow cytometry as well as conventional, culture-based methods. Despite a random dramatic event (detected with pyrosequencing and flow cytometry but not with plate counts), the bacterial community profile at the two locations did not vary significantly over time. A diverse core microbiome was shared between the two locations (58-65% of the taxa and 86-91% of the sequences) and found to be dependent on the treatment strategy. The bacterial community structure changed during distribution, with greater richness detected in the network and phyla such as Acidobacteria and Gemmatimonadetes becoming abundant. The rare taxa displayed the highest dynamicity, causing the major change during water distribution. This change did not have hygienic implications and is contingent on the sensitivity of the applied methods. The concept of biological stability therefore needs to be revised. Biostability is generally desired in drinking water guidelines but may be difficult to achieve in large-scale complex distribution systems that are inherently dynamic. PMID:25732558

  16. Stability Analysis of SIR Model with Distributed Delay on Complex Networks.

    PubMed

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number [Formula: see text] of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff's matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if [Formula: see text], then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if [Formula: see text], then the system with distributed time delay stabilizes fastest; while [Formula: see text], the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  17. Stability Analysis of SIR Model with Distributed Delay on Complex Networks

    PubMed Central

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number R0 of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if R0≤1, then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if R0>1, then the system with distributed time delay stabilizes fastest; while R0≤1, the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  18. Re-examining the global distribution of seamounts using neural network techniques

    NASA Astrophysics Data System (ADS)

    Valentine, A. P.; Kalnins, L. M.; Trampert, J.

    2012-12-01

    The distribution of seamounts and ocean islands, ranging from small hills just a few hundred meters in height to mountains such as Mauna Kea, offers key insights into the patterns of intraplate volcanism and their spatial and temporal variations. This may in turn provide information about the underlying lithosphere and asthenosphere. Mapping the global distribution of seamounts is complicated by the limitations of marine topography data and by the scale of the problem: 335 billion km2 of ocean must be searched. Whilst seamounts are comparatively easy to identify by visual inspection, automating this identification is often difficult, since a mathematical description of the feature is required. Previous techniques include modelling seamounts using simple Gaussian or elliptical polynomial models (e.g. Kim & Wessel, 2011) or searching for sinks in inverted bathymetry data (e.g. Kitchingman & Lai, 2004). However, seamounts exhibit significant natural variation, and any particular model may not suit all examples. It is therefore difficult to develop an algorithm that detects the full range of seamount morphologies, yet excludes other features of different origin but similar general form, such as tectonic fabric or abyssal hills. One potential avenue lies in the use of neural networks, or other learning algorithms, inspired by the pattern-recognition ability of the brain. Rather than formulating an textit{a priori} description of the feature, a neural network assimilates characteristics from a set of hand-picked examples. Here, we use an autoencoder network to assess whether small patches of ocean floor display the representative characteristics learnt by our network. From this, we can build up a database of seamount locations, with early indications suggesting a reduction in false positives such as abyssal hills when compared with traditional methods, whilst results over large features are generally similar. Once the dataset is constructed, the distribution of the

  19. Input Response of Neural Network Model with Lognormally Distributed Synaptic Weights

    NASA Astrophysics Data System (ADS)

    Nagano, Yoshihiro; Karakida, Ryo; Watanabe, Norifumi; Aoyama, Atsushi; Okada, Masato

    2016-07-01

    Neural assemblies in the cortical microcircuit can sustain irregular spiking activity without external inputs. On the other hand, neurons exhibit rich evoked activities driven by sensory stimulus, and both activities are reported to contribute to cognitive functions. We studied the external input response of the neural network model with lognormally distributed synaptic weights. We show that the model can achieve irregular spontaneous activity and population oscillation depending on the presence of external input. The firing rate distribution was maintained for the external input, and the order of firing rates in evoked activity reflected that in spontaneous activity. Moreover, there were bistable regions in the inhibitory input parameter space. The bimodal membrane potential distribution, which is a characteristic feature of the up-down state, was obtained under such conditions. From these results, we can conclude that the model displays various evoked activities due to the external input and is biologically plausible.

  20. Neural network-based distributed attitude coordination control for spacecraft formation flying with input saturation.

    PubMed

    Zou, An-Min; Kumar, Krishna Dev

    2012-07-01

    This brief considers the attitude coordination control problem for spacecraft formation flying when only a subset of the group members has access to the common reference attitude. A quaternion-based distributed attitude coordination control scheme is proposed with consideration of the input saturation and with the aid of the sliding-mode observer, separation principle theorem, Chebyshev neural networks, smooth projection algorithm, and robust control technique. Using graph theory and a Lyapunov-based approach, it is shown that the distributed controller can guarantee the attitude of all spacecraft to converge to a common time-varying reference attitude when the reference attitude is available only to a portion of the group of spacecraft. Numerical simulations are presented to demonstrate the performance of the proposed distributed controller. PMID:24807141

  1. Distributed consensus estimation for diffusion systems with missing measurements over sensor networks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhengxian; Cui, Baotong; Lou, Xuyang

    2016-09-01

    In this paper, the problem of distributed consensus estimation with randomly missing measurements is investigated for a diffusion system over the sensor network. A random variable, the probability of which is known a priori, is used to model the randomly missing phenomena for each sensor. The aim of the addressed estimation problem is to design distributed consensus estimators depending on the neighbouring information such that, for all random measurement missing, the estimation error systems are guaranteed to be globally asymptotically stable in the mean square. By using Lyapunov functional method and the stochastic analysis approach, the sufficient conditions are derived for the convergence of the estimation error systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed distributed consensus estimator design scheme.

  2. An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

    NASA Astrophysics Data System (ADS)

    Leon, Barbara D.; Heller, Paul R.

    1987-05-01

    A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system

  3. Local multipoint distribution system (LDMS) versus free-space optical (FSO) networks

    NASA Astrophysics Data System (ADS)

    Willebrand, Heinz A.; Clark, Gerald R.; Willson, Bryan; Andreu von Euw, Christian G.; Roy, Joe; Mayhew, Laurel M.

    2001-11-01

    This paper compares two emerging broadband access methodologies, Free Space Optics (FSO) and Local Multipoint Distribution System (LMDS) and the atmospheric propagation characteristics of each when exposed to a dynamically changing channel. The comparison focuses on bandwidth, availability, and distance requirements for the new broadband market and how LMDS and FSO can be used to meet these requirements. Possible network topologies and their associated costs are examined. This comparison takes into account the total cost of deployment, including equipment costs, installation fees, access fees, and spectrum licensing fees. LMDS and FSO are compared on speed of deployment, scalability, aggregate bandwidth, and bandwidth per customer. Present and projected capabilities of each technology are considered for their suitability in different locations in the network, from the Wide Area Network (WAN), to the Metropolitan Area Network (MAN), all the way to Last Mile Access. There is a discussion on the relative performance of LMDS and FSO, focusing on the different factors that can affect link availability. Since network design is a large factor in assuring overall reliability, the flexibility of each technology with regard to network design is compared. LMDS and FSO are both line of sight, space-propagated technologies, and as such, they are both susceptible to path impediments and atmospheric attenuation, dispersion, scattering, and absorption. LMDS and FSO are affected very differently by different meteorological phenomena. Problematic atmospheric conditions are, specifically scintillation, rainfall, and fog, are examined. In addition to a discussion of these conditions, various techniques for minimizing atmospheric and environmental effects are investigated. The paper concludes with a summary of findings and recommendations for a number of broadband wireless applications.

  4. Distributed Storage Healthcare — The Basis of a Planet-Wide Public Health Care Network

    PubMed Central

    Kakouros, Nikolaos

    2013-01-01

    Background: As health providers move towards higher levels of information technology (IT) integration, they become increasingly dependent on the availability of the electronic health record (EHR). Current solutions of individually managed storage by each healthcare provider focus on efforts to ensure data security, availability and redundancy. Such models, however, scale poorly to a future of a planet-wide public health-care network (PWPHN). Our aim was to review the research literature on distributed storage systems and propose methods that may aid the implementation of a PWPHN. Methods: A systematic review was carried out of the research dealing with distributed storage systems and EHR. A literature search was conducted on five electronic databases: Pubmed/Medline, Cinalh, EMBASE, Web of Science (ISI) and Google Scholar and then expanded to include non-authoritative sources. Results: The English National Health Service Spine represents the most established country-wide PHN but is limited in deployment and remains underused. Other, literature identified and established distributed EHR attempts are more limited in scope. We discuss the currently available distributed file storage solutions and propose a schema of how one of these technologies can be used to deploy a distributed storage of EHR with benefits in terms of enhanced fault tolerance and global availability within the PWPHN. We conclude that a PWPHN distributed health care record storage system is technically feasible over current Internet infrastructure. Nonetheless, the socioeconomic viability of PWPHN implementations remains to be determined. PMID:23459171

  5. Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

    NASA Astrophysics Data System (ADS)

    Islam, Mujahidul

    A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable

  6. Shaping protein distributions in stochastic self-regulated gene expression networks

    NASA Astrophysics Data System (ADS)

    Pájaro, Manuel; Alonso, Antonio A.; Vázquez, Carlos

    2015-09-01

    In this work, we study connections between dynamic behavior and network parameters, for self-regulatory networks. To that aim, a method to compute the regions in the space of parameters that sustain bimodal or binary protein distributions has been developed. Such regions are indicative of stochastic dynamics manifested either as transitions between absence and presence of protein or between two positive protein levels. The method is based on the continuous approximation of the chemical master equation, unlike other approaches that make use of a deterministic description, which as will be shown can be misleading. We find that bimodal behavior is a ubiquitous phenomenon in cooperative gene expression networks under positive feedback. It appears for any range of transcription and translation rate constants whenever leakage remains below a critical threshold. Above such a threshold, the region in the parameters space which sustains bimodality persists, although restricted to low transcription and high translation rate constants. Remarkably, such a threshold is independent of the transcription or translation rates or the proportion of an active or inactive promoter and depends only on the level of cooperativity. The proposed method can be employed to identify bimodal or binary distributions leading to stochastic dynamics with specific switching properties, by searching inside the parameter regions that sustain such behavior.

  7. A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks.

    PubMed

    Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

    2016-01-01

    In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ 1 norm regularization ( ℓ 1 -regularized) is investigated, and a novel distributed learning algorithm for the ℓ 1 -regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. PMID:27376298

  8. A Distributed Learning Method for ℓ1-Regularized Kernel Machine over Wireless Sensor Networks

    PubMed Central

    Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

    2016-01-01

    In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ1 norm regularization (ℓ1-regularized) is investigated, and a novel distributed learning algorithm for the ℓ1-regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. PMID:27376298

  9. Distributed Power Control Network and Green Building Test-Bed for Demand Response in Smart Grid

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Kei; Nguyen, Van Ky; Tao, Yu; Tran, Gia Khanh; Araki, Kiyomichi

    It is known that demand and supply power balancing is an essential method to operate power delivery system and prevent blackouts caused by power shortage. In this paper, we focus on the implementation of demand response strategy to save power during peak hours by using Smart Grid. It is obviously impractical with centralized power control network to realize the real-time control performance, where a single central controller measures the huge metering data and sends control command back to all customers. For that purpose, we propose a new architecture of hierarchical distributed power control network which is scalable regardless of the network size. The sub-controllers are introduced to partition the large system into smaller distributed clusters where low-latency local feedback power control loops are conducted to guarantee control stability. Furthermore, sub-controllers are stacked up in an hierarchical manner such that data are fed back layer-by-layer in the inbound while in the outbound control responses are decentralized in each local sub-controller for realizing the global objectives. Numerical simulations in a realistic scenario of up to 5000 consumers show the effectiveness of the proposed scheme to achieve a desired 10% peak power saving by using off-the-shelf wireless devices with IEEE802.15.4g standard. In addition, a small scale power control system for green building test-bed is implemented to demonstrate the potential use of the proposed scheme for power saving in real life.

  10. Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

    PubMed

    Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

    2013-01-28

    We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile. PMID:23389228

  11. Resistance to HF jamming interference in mobile radio networks by an adaptive, distributed reconfiguration technique

    NASA Astrophysics Data System (ADS)

    Baker, D. J.; Wieselthier, J. E.; Ephremides, A.; McGregor, D. N.

    1984-08-01

    In radio communication, interference (and in particular jamming) represents an important limitation to the rate and range of information transfer. In a radio network environment, a combination of relaying and other classes of interference-combatting methods, such as spread spectrum signaling, may achieve highly robust resistance to jamming. Since the presence of relays is an inherent characteristic of a network, it is possible to use some nodes as relays when previously existing direct links are disabled as a result of jamming. The purpose of this report is to show how a distributed algorithm can enable an HF radio network to reconfigure itself to combat various jamming threats. We present models for the communication range that is achievable through the use of HF groundwave signals under both benign and stressed conditions and for cases of narrowband and wideband signaling. The models are used in our simulations. These simulations show that the choice of best frequency for communication in an HF network should not depend solely on communication range in a benign environment.

  12. Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

    PubMed

    Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

    2015-11-01

    Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. PMID:26343165

  13. An efficient distributed algorithm for constructing spanning trees in wireless sensor networks.

    PubMed

    Lachowski, Rosana; Pellenz, Marcelo E; Penna, Manoel C; Jamhour, Edgard; Souza, Richard D

    2015-01-01

    Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing. PMID:25594593

  14. Distributed multisensory integration in a recurrent network model through supervised learning

    NASA Astrophysics Data System (ADS)

    Wang, He; Wong, K. Y. Michael

    Sensory integration between different modalities has been extensively studied. It is suggested that the brain integrates signals from different modalities in a Bayesian optimal way. However, how the Bayesian rule is implemented in a neural network remains under debate. In this work we propose a biologically plausible recurrent network model, which can perform Bayesian multisensory integration after trained by supervised learning. Our model is composed of two modules, each for one modality. We assume that each module is a recurrent network, whose activity represents the posterior distribution of each stimulus. The feedforward input on each module is the likelihood of each modality. Two modules are integrated through cross-links, which are feedforward connections from the other modality, and reciprocal connections, which are recurrent connections between different modules. By stochastic gradient descent, we successfully trained the feedforward and recurrent coupling matrices simultaneously, both of which resembles the Mexican-hat. We also find that there are more than one set of coupling matrices that can approximate the Bayesian theorem well. Specifically, reciprocal connections and cross-links will compensate each other if one of them is removed. Even though trained with two inputs, the network's performance with only one input is in good accordance with what is predicted by the Bayesian theorem.

  15. A majorization-minimization approach to design of power distribution networks

    SciTech Connect

    Johnson, Jason K; Chertkov, Michael

    2010-01-01

    We consider optimization approaches to design cost-effective electrical networks for power distribution. This involves a trade-off between minimizing the power loss due to resistive heating of the lines and minimizing the construction cost (modeled by a linear cost in the number of lines plus a linear cost on the conductance of each line). We begin with a convex optimization method based on the paper 'Minimizing Effective Resistance of a Graph' [Ghosh, Boyd & Saberi]. However, this does not address the Alternating Current (AC) realm and the combinatorial aspect of adding/removing lines of the network. Hence, we consider a non-convex continuation method that imposes a concave cost of the conductance of each line thereby favoring sparser solutions. By varying a parameter of this penalty we extrapolate from the convex problem (with non-sparse solutions) to the combinatorial problem (with sparse solutions). This is used as a heuristic to find good solutions (local minima) of the non-convex problem. To perform the necessary non-convex optimization steps, we use the majorization-minimization algorithm that performs a sequence of convex optimizations obtained by iteratively linearizing the concave part of the objective. A number of examples are presented which suggest that the overall method is a good heuristic for network design. We also consider how to obtain sparse networks that are still robust against failures of lines and/or generators.

  16. A multi-period distribution network design model under demand uncertainty

    NASA Astrophysics Data System (ADS)

    Tabrizi, Babak H.; Razmi, Jafar

    2013-05-01

    Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

  17. An Efficient Distributed Algorithm for Constructing Spanning Trees in Wireless Sensor Networks

    PubMed Central

    Lachowski, Rosana; Pellenz, Marcelo E.; Penna, Manoel C.; Jamhour, Edgard; Souza, Richard D.

    2015-01-01

    Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing. PMID:25594593

  18. A university-based distributed satellite mission control network for operating professional space missions

    NASA Astrophysics Data System (ADS)

    Kitts, Christopher; Rasay, Mike

    2016-03-01

    For more than a decade, Santa Clara University's Robotic Systems Laboratory has operated a unique, distributed, internet-based command and control network for providing professional satellite mission control services for a variety of government and industry space missions. The system has been developed and is operated by students who become critical members of the mission teams throughout the development, test, and on-orbit phases of these missions. The mission control system also supports research in satellite control technology and hands-on student aerospace education. This system serves as a benchmark for its comprehensive nature, its student-centric nature, its ability to support NASA and industry space missions, and its longevity in providing a consistent level of professional services. This paper highlights the unique features of this program, reviews the network's design and the supported spacecraft missions, and describes the critical programmatic features of the program that support the control of professional space missions.

  19. A high-performance network for a distributed-control system

    NASA Astrophysics Data System (ADS)

    Cuttone, G.; Aghion, F.; Giove, D.

    1989-04-01

    Local area networks play a central rule in modern distributed-control systems for accelerators. For a superconducting cyclotron under construction at the University of Milan, an optical Ethernet network has been implemented for the interconnection of multicomputer-based stations. Controller boards, with VLSI protocol chips, have been used. The higher levels of the ISO OSI model have been implemented to suit real-time control requirements. The experimental setup for measuring the data throughput between stations will be described. The effect of memory-to-memory data transfer with respect to the packet size has been studied for packets ranging from 200 bytes to 10 Kbytes. Results, showing the data throughput to range from 0.2 to 1.1 Mbit/s, will be discussed.

  20. Low-Power Direct-Sequence Spread-Spectrum Modem Architecture for Distributed Wireless Sensor Networks

    SciTech Connect

    Chien, C; Elgorriaga, I; McConaghy, C

    2001-07-03

    Emerging CMOS and MEMS technologies enable the implementation of a large number of wireless distributed microsensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors should operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. This paper presents a direct-sequence spread-spectrum modem architecture that provides robust communications for wireless sensor networks while dissipating very low power. The modem architecture has been verified in an FPGA implementation that dissipates only 33 mW for both transmission and reception. The implementation can be easily mapped to an ASIC technology, with an estimated power performance of less than 1 mW.

  1. L-hop percolation on networks with arbitrary degree distributions and its applications.

    PubMed

    Shang, Yilun; Luo, Weiliang; Xu, Shouhuai

    2011-09-01

    Site percolation has been used to help understand analytically the robustness of complex networks in the presence of random node deletion (or failure). In this paper we move a further step beyond random node deletion by considering that a node can be deleted because it is chosen or because it is within some L-hop distance of a chosen node. Using the generating functions approach, we present analytic results on the percolation threshold as well as the mean size, and size distribution, of nongiant components of complex networks under such operations. The introduction of parameter L is both conceptually interesting because it accommodates a sort of nonindependent node deletion, which is often difficult to tackle analytically, and practically interesting because it offers useful insights for cybersecurity (such as botnet defense). PMID:22060334

  2. L-hop percolation on networks with arbitrary degree distributions and its applications

    NASA Astrophysics Data System (ADS)

    Shang, Yilun; Luo, Weiliang; Xu, Shouhuai

    2011-09-01

    Site percolation has been used to help understand analytically the robustness of complex networks in the presence of random node deletion (or failure). In this paper we move a further step beyond random node deletion by considering that a node can be deleted because it is chosen or because it is within some L-hop distance of a chosen node. Using the generating functions approach, we present analytic results on the percolation threshold as well as the mean size, and size distribution, of nongiant components of complex networks under such operations. The introduction of parameter L is both conceptually interesting because it accommodates a sort of nonindependent node deletion, which is often difficult to tackle analytically, and practically interesting because it offers useful insights for cybersecurity (such as botnet defense).

  3. A jazz-based approach for optimal setting of pressure reducing valves in water distribution networks

    NASA Astrophysics Data System (ADS)

    De Paola, Francesco; Galdiero, Enzo; Giugni, Maurizio

    2016-05-01

    This study presents a model for valve setting in water distribution networks (WDNs), with the aim of reducing the level of leakage. The approach is based on the harmony search (HS) optimization algorithm. The HS mimics a jazz improvisation process able to find the best solutions, in this case corresponding to valve settings in a WDN. The model also interfaces with the improved version of a popular hydraulic simulator, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the solutions. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to two case studies, and the obtained results in terms of pressure reductions are comparable with those of competitive metaheuristic algorithms (e.g. genetic algorithms). The results demonstrate the suitability of the HS algorithm for water network management and optimization.

  4. Competitive hopfield network combined with estimation of distribution for maximum diversity problems.

    PubMed

    Wang, Jiahai; Zhou, Yalan; Yin, Jian; Zhang, Yunong

    2009-08-01

    This paper presents a discrete competitive Hopfield neural network (HNN) (DCHNN) based on the estimation of distribution algorithm (EDA) for the maximum diversity problem. In order to overcome the local minimum problem of DCHNN, the idea of EDA is combined with DCHNN. Once the network is trapped in local minima, the perturbation based on EDA can generate a new starting point for DCHNN for further search. It is expected that the further search is guided to a promising area by the probability model. Thus, the proposed algorithm can escape from local minima and further search better results. The proposed algorithm is tested on 120 benchmark problems with the size ranging from 100 to 5000. Simulation results show that the proposed algorithm is better than the other improved DCHNN such as multistart DCHNN and DCHNN with random flips and is better than or competitive with metaheuristic algorithms such as tabu-search-based algorithms and greedy randomized adaptive search procedure algorithms. PMID:19336334

  5. Power-law distributed temporal heterogeneity of human activities promotes cooperation on complex networks

    NASA Astrophysics Data System (ADS)

    Liu, Chao; Li, Rong

    2016-09-01

    An evolutionary prisoner's dilemma game (PDG) with players located on Barabási-Albert scale-free networks is studied. The impact of players' heterogeneous temporal activity pattern on the evolution of cooperation is investigated. To this end, the normal procedure that players update their strategies immediately after a round of game is discarded. Instead, players update strategies according to their assigned reproduction time, which follows a power-law distribution. We find that the temporal heterogeneity of players' activities facilitates the prosperity of cooperation, indicating the important role of hubs in the maintenance of cooperation on scale-free networks. When the reproduction time is assigned to individuals negatively related to their degrees, a fluctuation of the cooperation level with the increase of the exponent β is observed.

  6. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders

    PubMed Central

    Kim, Katherine K; Browe, Dennis K; Logan, Holly C; Holm, Roberta; Hack, Lori; Ohno-Machado, Lucila

    2014-01-01

    There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research. PMID:24302285

  7. Analysis of a distributed algorithm to determine multiple routes with path diversity in ad hoc networks.

    SciTech Connect

    Ghosal, Dipak; Mueller, Stephen Ng

    2005-04-01

    With multipath routing in mobile ad hoc networks (MANETs), a source can establish multiple routes to a destination for routing data. In MANETs, mulitpath routing can be used to provide route resilience, smaller end-to-end delay, and better load balancing. However, when the multiple paths are close together, transmissions of different paths may interfere with each other, causing degradation in performance. Besides interference, the physical diversity of paths also improves fault tolerance. We present a purely distributed multipath protocol based on the AODV-Multipath (AODVM) protocol called AODVM with Path Diversity (AODVM/PD) that finds multiple paths with a desired degree of correlation between paths specified as an input parameter to the algorithm. We demonstrate through detailed simulation analysis that multiple paths with low degree of correlation determined by AODVM/PD provides both smaller end-to-end delay than AODVM in networks with low mobility and better route resilience in the presence of correlated node failures.

  8. Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

    PubMed Central

    Chen, Qihong; Long, Rong; Quan, Shuhai

    2014-01-01

    This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

  9. 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

    2016-01-01

    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. PMID:26907275

  10. A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks

    PubMed Central

    Mi, Shichao; Han, Hui; Chen, Cailian; Yan, Jian; Guan, Xinping

    2016-01-01

    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. PMID:26907275

  11. Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

    NASA Technical Reports Server (NTRS)

    Sanders, Adam M. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor); Strawser, Philip A. (Inventor)

    2015-01-01

    A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

  12. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

    PubMed

    Kim, Katherine K; Browe, Dennis K; Logan, Holly C; Holm, Roberta; Hack, Lori; Ohno-Machado, Lucila

    2014-01-01

    There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research. PMID:24302285

  13. Community-Based Social Networks: Generation of Power Law Degree Distribution and IP Solutions to the KPP

    ERIC Educational Resources Information Center

    Wu, Wentao

    2012-01-01

    The objective of this thesis is two-fold: (1) to investigate the degree distribution property of community-based social networks (CSNs) and (2) to provide solutions to a pertinent problem, the Key Player Problem. In the first part of this thesis, we consider a growing community-based network in which the ability of nodes competing for links to new…

  14. Field-Scale Distributed Wireless Network for Monitoring Dynamic Hydrologic Processes

    NASA Astrophysics Data System (ADS)

    Campbell, C. S.; Crupper, J.; Brown, D. J.; Cobos, D. R.; Campbell, G. S.; Uberuaga, D.; Huggins, D. R.; Smith, J. L.; Gill, R. A.

    2007-12-01

    Measuring and monitoring field-scale hydrology is important to understanding the fate of water in the vadoze zone, especially in concert with pedological information. Historically, single point measurements of hydrologic and pedological information have been straightforward to obtain, while monitoring widely distributed locations over time has been more challenging, both in expense and labor. As radios have become more available, distributed wireless networks have been developed and constructed to meet this need. However, there remain relatively few commercially available, inexpensive, and simple options. The objective of this study was to test the viability of a distributed wireless network to monitor soil parameters (moisture, temperature, and electrical conductivity) across a growing season on the 36.5 hectare Cook Agronomy Farm in Eastern Washington. Using landscape analysis, 12 representative sites were selected using a stratified random procedure and sensors were installed at 30, 60, 90, 120, and 150 cm depths. Radio frequency wireless transmitters linked sensors to a central data station where data were made available anywhere in the world via a cell modem link. Data were analyzed to show relationships between soil features, crop type, and water use. Results show that a system can be assembled from commercially available components with excellent reliability across all communication links. Data from the system showed correlations between water use, directly sampled static soil features and crop type.

  15. El Sistema's Open Secrets

    ERIC Educational Resources Information Center

    Booth, Eric

    2011-01-01

    In this article, the author talks about Venezuela's national youth orchestra program called El Sistema whose attributes offer a direct challenge to traditional Western music practices. As U.S. classical music--and all "high arts"--struggle to find relevance to more than the small "arts club" percentage of the U.S. populace, El Sistema proposes…

  16. The impact of capillary dilation on the distribution of red blood cells in artificial networks.

    PubMed

    Schmid, Franca; Reichold, Johannes; Weber, Bruno; Jenny, Patrick

    2015-04-01

    Recent studies suggest that pericytes around capillaries are contractile and able to alter the diameter of capillaries. To investigate the effects of capillary dilation on network dynamics, we performed simulations in artificial capillary networks of different sizes and complexities. The unequal partition of hematocrit at diverging bifurcations was modeled by assuming that each red blood cell (RBC) enters the branch with the faster instantaneous flow. Network simulations with and without RBCs were performed to investigate the effect of local dilations. The results showed that the increase in flow rate due to capillary dilation was less when the effects of RBCs are included. For bifurcations with sufficient RBCs in the parent vessel and nearly equal flows in the branches, the flow rate in the dilated branch did not increase. Instead, a self-regulation of flow was observed due to accumulation of RBCs in the dilated capillary. A parametric study was performed to examine the dependence on initial capillary diameter, dilation factor, and tube hematocrit. Furthermore, the conditions needed for an efficient self-regulation mechanism are discussed. The results support the hypothesis that RBCs play a significant role for the fluid dynamics in capillary networks and that it is crucial to consider the blood flow rate and the distribution of RBCs to understand the supply of oxygen in the vasculature. Furthermore, our results suggest that capillary dilation/constriction offers the potential of being an efficient mechanism to alter the distribution of RBCs locally and hence could be important for the local regulation of oxygen delivery. PMID:25617356

  17. Blood flow distribution in an anatomically detailed arterial network model: criteria and algorithms.

    PubMed

    Blanco, Pablo J; Watanabe, Sansuke M; Dari, Enzo A; Passos, Marco Aurélio R F; Feijóo, Raúl A

    2014-11-01

    Development of blood flow distribution criteria is a mandatory step toward developing computational models and numerical simulations of the systemic circulation. In the present work, we (i) present a systematic approach based on anatomical and physiological considerations to distribute the blood flow in a 1D anatomically detailed model of the arterial network and (ii) develop a numerical procedure to calibrate resistive parameters in terminal models in order to effectively satisfy such flow distribution. For the first goal, we merge data collected from the specialized medical literature with anatomical concepts such as vascular territories to determine blood flow supply to specific (encephalon, kidneys, etc.) and distributed (muscles, skin, etc.) organs. Overall, 28 entities representing the main specific organs are accounted for in the detailed description of the arterial topology that we use as model substrate. In turn, 116 vascular territories are considered as the basic blocks that compose the distributed organs throughout the whole body. For the second goal, Windkessel models are used to represent the peripheral beds, and the values of the resistive parameters are computed applying a Newton method to a parameter identification problem to guarantee the supply of the correct flow fraction to each terminal location according to the given criteria. Finally, it is shown that, by means of the criteria developed, and for a rather standard set of model parameters, the model predicts physiologically realistic pressure and flow waveforms. PMID:24682727

  18. Distributed Multi-Target Tracking and Data Association in Vision Networks.

    PubMed

    Kamal, Ahmed T; Bappy, Jawadul H; Farrell, Jay A; Roy-Chowdhury, Amit K

    2016-07-01

    Distributed algorithms have recently gained immense popularity. With regards to computer vision applications, distributed multi-target tracking in a camera network is a fundamental problem. The goal is for all cameras to have accurate state estimates for all targets. Distributed estimation algorithms work by exchanging information between sensors that are communication neighbors. Vision-based distributed multi-target state estimation has at least two characteristics that distinguishes it from other applications. First, cameras are directional sensors and often neighboring sensors may not be sensing the same targets, i.e., they are naive with respect to that target. Second, in the presence of clutter and multiple targets, each camera must solve a data association problem. This paper presents an information-weighted, consensus-based, distributed multi-target tracking algorithm referred to as the Multi-target Information Consensus (MTIC) algorithm that is designed to address both the naivety and the data association problems. It converges to the centralized minimum mean square error estimate. The proposed MTIC algorithm and its extensions to non-linear camera models, termed as the Extended MTIC (EMTIC), are robust to false measurements and limited resources like power, bandwidth and the real-time operational requirements. Simulation and experimental analysis are provided to support the theoretical results. PMID:26441444

  19. Flow distribution analysis on the cooling tube network of ITER thermal shield

    NASA Astrophysics Data System (ADS)

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O.; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-01

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  20. Effects on electrical distribution networks of dispersed power generation at high levels of connection penetration

    SciTech Connect

    Longrigg, P

    1983-07-01

    The advent and deployment of significant levels of photovoltaic and wind energy generation in the spatially dispersed mode (i.e., residential and intermediate load centers) may have deleterious effects upon existing protective relay equipment and its time-current coordination on radial distribution circuits to which power conditioning equipment may be connected for power sell-back purposes. The problems that may arise involve harmonic injection from power conditioning inverters that can affect protective relays and cause excessive voltage and current from induced series and parallel resonances on feeders and connected passive equipment. Voltage regulation, var requirements, and consumer metering can also be affected by this type of dispersed generation. The creation of islands of supply is also possible, particularly on rural supply systems. This paper deals mainly with the effects of harmonics and short-circuit currents from wind energy conversion systems (WECS) and photovoltaic (PV) systems upon the operating characteristics of distribution networks and relays and other protective equipment designed to ensure the safety and supply integrity of electrical utility networks. Traditionally, electrical supply networks have been designed for one-way power flow-from generation to load, with a balance maintained between the two by means of automatic generation and load-frequency controls. Dispersed generation, from renewables like WECS or PV or from nonrenewable resources, can change traditional power flow. These changes must be dealt with effectively if renewable energy resources are to be integrated into the utility distribution system. This paper gives insight into these problems and proposes some solutions.

  1. The formation and distribution of hippocampal synapses on patterned neuronal networks

    NASA Astrophysics Data System (ADS)

    Dowell-Mesfin, Natalie M.

    Communication within the central nervous system is highly orchestrated with neurons forming trillions of specialized junctions called synapses. In vivo, biochemical and topographical cues can regulate neuronal growth. Biochemical cues also influence synaptogenesis and synaptic plasticity. The effects of topography on the development of synapses have been less studied. In vitro, neuronal growth is unorganized and complex making it difficult to study the development of networks. Patterned topographical cues guide and control the growth of neuronal processes (axons and dendrites) into organized networks. The aim of this dissertation was to determine if patterned topographical cues can influence synapse formation and distribution. Standard fabrication and compression molding procedures were used to produce silicon masters and polystyrene replicas with topographical cues presented as 1 mum high pillars with diameters of 0.5 and 2.0 mum and gaps of 1.0 to 5.0 mum. Embryonic rat hippocampal neurons grown unto patterned surfaces. A developmental analysis with immunocytochemistry was used to assess the distribution of pre- and post-synaptic proteins. Activity-dependent pre-synaptic vesicle uptake using functional imaging dyes was also performed. Adaptive filtering computer algorithms identified synapses by segmenting juxtaposed pairs of pre- and post-synaptic labels. Synapse number and area were automatically extracted from each deconvolved data set. In addition, neuronal processes were traced automatically to assess changes in synapse distribution. The results of these experiments demonstrated that patterned topographic cues can induce organized and functional neuronal networks that can serve as models for the study of synapse formation and plasticity as well as for the development of neuroprosthetic devices.

  2. Water quality modeling in the dead end sections of drinking water distribution networks.

    PubMed

    Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

    2016-02-01

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

  3. Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

    NASA Astrophysics Data System (ADS)

    Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

    1998-05-01

    Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.

  4. Flow distribution analysis on the cooling tube network of ITER thermal shield

    SciTech Connect

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-29

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  5. On-Board Fiber-Optic Network Architectures for Radar and Avionics Signal Distribution

    NASA Technical Reports Server (NTRS)

    Alam, Mohammad F.; Atiquzzaman, Mohammed; Duncan, Bradley B.; Nguyen, Hung; Kunath, Richard

    2000-01-01

    Continued progress in both civil and military avionics applications is overstressing the capabilities of existing radio-frequency (RF) communication networks based on coaxial cables on board modem aircrafts. Future avionics systems will require high-bandwidth on- board communication links that are lightweight, immune to electromagnetic interference, and highly reliable. Fiber optic communication technology can meet all these challenges in a cost-effective manner. Recently, digital fiber-optic communication systems, where a fiber-optic network acts like a local area network (LAN) for digital data communications, have become a topic of extensive research and development. Although a fiber-optic system can be designed to transport radio-frequency (RF) signals, the digital fiber-optic systems under development today are not capable of transporting microwave and millimeter-wave RF signals used in radar and avionics systems on board an aircraft. Recent advances in fiber optic technology, especially wavelength division multiplexing (WDM), has opened a number of possibilities for designing on-board fiber optic networks, including all-optical networks for radar and avionics RF signal distribution. In this paper, we investigate a number of different novel approaches for fiber-optic transmission of on-board VHF and UHF RF signals using commercial off-the-shelf (COTS) components. The relative merits and demerits of each architecture are discussed, and the suitability of each architecture for particular applications is pointed out. All-optical approaches show better performance than other traditional approaches in terms of signal-to-noise ratio, power consumption, and weight requirements.

  6. Distributed control of cluster synchronisation in networks with randomly occurring non-linearities

    NASA Astrophysics Data System (ADS)

    Hu, Aihua; Cao, Jinde; Hu, Manfeng; Guo, Liuxiao

    2016-08-01

    This paper is concerned with the issue of mean square cluster synchronisation in complex networks, which consist of non-identical nodes with randomly occurring non-linearities. In order to guarantee synchronisation, distributed controllers depending on the information from the neighbours in the same cluster are applied to each node, meanwhile, the control gains are supposed to be updated according to the given laws. Based on the Lyapunov stability theory, the sufficient synchronisation conditions are derived and proved theoretically. Finally, a numerical example is presented to demonstrate the effectiveness of the results.

  7. On KLJN-based Secure Key Distribution in Vehicular Communication Networks

    NASA Astrophysics Data System (ADS)

    Cao, X.; Saez, Y.; Pesti, G.; Kish, L. B.

    2015-12-01

    In a former paper [Fluct. Noise Lett. 13 (2014) 1450020] we introduced a vehicular communication system with unconditionally secure key exchange based on the Kirchhoff-Law-Johnson-Noise (KLJN) key distribution scheme. In this paper, we address the secure KLJN key donation to vehicles. This KLJN key donation solution is performed lane-by-lane by using roadside key provider equipment embedded in the pavement. A method to compute the lifetime of the KLJN key is also given. This key lifetime depends on the car density and gives an upper limit of the lifetime of the KLJN key for vehicular communication networks.

  8. Economic consideration of optimal vaccination distribution for epidemic Spreads in complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Bing; Suzuki, Hideyuki; Aihara, Kazuyuki

    2013-02-01

    The main concern of epidemiological modeling is to implement an economical vaccine allocation to the population. Here, we investigate the optimal vaccination allocation in complex networks. We find that the optimal vaccine coverage depends not only on the relative cost of treatment to vaccination but also on the vaccine efficacy. Especially with a high cost of treatment, nodes with high degree are prioritized to vaccinate. These results may help us understand factors that may impact the optimal vaccination distribution in the control of epidemic dynamics.

  9. Distribution of the Latest Content in Dynamic Content Updates over Delay Tolerant Networks

    NASA Astrophysics Data System (ADS)

    Li, Yong; Jin, Depeng; Su, Li; Zeng, Lieguang

    The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

  10. Distributed Synchronization Technique for OFDMA-Based Wireless Mesh Networks Using a Bio-Inspired Algorithm

    PubMed Central

    Kim, Mi Jeong; Maeng, Sung Joon; Cho, Yong Soo

    2015-01-01

    In this paper, a distributed synchronization technique based on a bio-inspired algorithm is proposed for an orthogonal frequency division multiple access (OFDMA)-based wireless mesh network (WMN) with a time difference of arrival. The proposed time- and frequency-synchronization technique uses only the signals received from the neighbor nodes, by considering the effect of the propagation delay between the nodes. It achieves a fast synchronization with a relatively low computational complexity because it is operated in a distributed manner, not requiring any feedback channel for the compensation of the propagation delays. In addition, a self-organization scheme that can be effectively used to construct 1-hop neighbor nodes is proposed for an OFDMA-based WMN with a large number of nodes. The performance of the proposed technique is evaluated with regard to the convergence property and synchronization success probability using a computer simulation. PMID:26225974

  11. Distributed network of integrated 3D sensors for transportation security applications

    NASA Astrophysics Data System (ADS)

    Hejmadi, Vic; Garcia, Fred

    2009-05-01

    The US Port Security Agency has strongly emphasized the needs for tighter control at transportation hubs. Distributed arrays of miniature CMOS cameras are providing some solutions today. However, due to the high bandwidth required and the low valued content of such cameras (simple video feed), large computing power and analysis algorithms as well as control software are needed, which makes such an architecture cumbersome, heavy, slow and expensive. We present a novel technique by integrating cheap and mass replicable stealth 3D sensing micro-devices in a distributed network. These micro-sensors are based on conventional structures illumination via successive fringe patterns on the object to be sensed. The communication bandwidth between each sensor remains very small, but is of very high valued content. Key technologies to integrate such a sensor are digital optics and structured laser illumination.

  12. Distributed OTDR-interferometric sensing network with identical ultra-weak fiber Bragg gratings.

    PubMed

    Wang, Chen; Shang, Ying; Liu, Xiao-Hui; Wang, Chang; Yu, Hai-Hu; Jiang, De-Sheng; Peng, Gang-Ding

    2015-11-01

    We demonstrate a distributed sensing network with 500 identical ultra-weak fiber Bragg gratings (uwFBGs) in an equal separation of 2m using balanced Michelson interferometer of the phase sensitive optical time domain reflectometry (φ-OTDR) for acoustic measurement. Phase, amplitude, frequency response and location information can be directly obtained at the same time by using the passive 3 × 3 coupler demodulation. Lab experiments on detecting sound waves in water tank are carried out. The results show that this system can well demodulate distributed acoustic signal with the pressure detection limit of 0.122Pa and achieve an acoustic phase sensitivity of around -158dB (re rad/μPa) with a relatively flat frequency response between 450Hz to 600Hz. PMID:26561173

  13. Privacy and Security Research Group workshop on network and distributed system security: Proceedings

    SciTech Connect

    Not Available

    1993-05-01

    This report contains papers on the following topics: NREN Security Issues: Policies and Technologies; Layer Wars: Protect the Internet with Network Layer Security; Electronic Commission Management; Workflow 2000 - Electronic Document Authorization in Practice; Security Issues of a UNIX PEM Implementation; Implementing Privacy Enhanced Mail on VMS; Distributed Public Key Certificate Management; Protecting the Integrity of Privacy-enhanced Electronic Mail; Practical Authorization in Large Heterogeneous Distributed Systems; Security Issues in the Truffles File System; Issues surrounding the use of Cryptographic Algorithms and Smart Card Applications; Smart Card Augmentation of Kerberos; and An Overview of the Advanced Smart Card Access Control System. Selected papers were processed separately for inclusion in the Energy Science and Technology Database.

  14. Orientational tomography of optical axes directions distributions of multilayer biological tissues birefringent polycrystalline networks

    NASA Astrophysics Data System (ADS)

    Zabolotna, Natalia I.; Dovhaliuk, Rostyslav Y.

    2013-09-01

    We present a novel measurement method of optic axes orientation distribution which uses a relatively simple measurement setup. The principal difference of our method from other well-known methods lies in direct approach for measuring the orientation of optical axis of polycrystalline networks biological crystals. Our test polarimetry setup consists of HeNe laser, quarter wave plate, two linear polarizers and a CCD camera. We also propose a methodology for processing of measured optic axes orientation distribution which consists of evaluation of statistical, correlational and spectral moments. Such processing of obtained data can be used to classify particular tissue sample as "healthy" or "pathological". For our experiment we use thin layers of histological section of normal and muscular dystrophy tissue sections. It is shown that the difference between mentioned moments` values of normal and pathological samples can be quite noticeable with relative difference up to 6.26.

  15. A decentralized training algorithm for Echo State Networks in distributed big data applications.

    PubMed

    Scardapane, Simone; Wang, Dianhui; Panella, Massimo

    2016-06-01

    The current big data deluge requires innovative solutions for performing efficient inference on large, heterogeneous amounts of information. Apart from the known challenges deriving from high volume and velocity, real-world big data applications may impose additional technological constraints, including the need for a fully decentralized training architecture. While several alternatives exist for training feed-forward neural networks in such a distributed setting, less attention has been devoted to the case of decentralized training of recurrent neural networks (RNNs). In this paper, we propose such an algorithm for a class of RNNs known as Echo State Networks. The algorithm is based on the well-known Alternating Direction Method of Multipliers optimization procedure. It is formulated only in terms of local exchanges between neighboring agents, without reliance on a coordinating node. Additionally, it does not require the communication of training patterns, which is a crucial component in realistic big data implementations. Experimental results on large scale artificial datasets show that it compares favorably with a fully centralized implementation, in terms of speed, efficiency and generalization accuracy. PMID:26341005

  16. Estimation of distribution algorithm for resource allocation in green cooperative cognitive radio sensor networks.

    PubMed

    Naeem, Muhammad; Pareek, Udit; Lee, Daniel C; Anpalagan, Alagan

    2013-01-01

    Due to the rapid increase in the usage and demand of wireless sensor networks (WSN), the limited frequency spectrum available for WSN applications will be extremely crowded in the near future. More sensor devices also mean more recharging/replacement of batteries, which will cause significant impact on the global carbon footprint. In this paper, we propose a relay-assisted cognitive radio sensor network (CRSN) that allocates communication resources in an environmentally friendly manner. We use shared band amplify and forward relaying for cooperative communication in the proposed CRSN. We present a multi-objective optimization architecture for resource allocation in a green cooperative cognitive radio sensor network (GC-CRSN). The proposed multi-objective framework jointly performs relay assignment and power allocation in GC-CRSN, while optimizing two conflicting objectives. The first objective is to maximize the total throughput, and the second objective is to minimize the total transmission power of CRSN. The proposed relay assignment and power allocation problem is a non-convex mixed-integer non-linear optimization problem (NC-MINLP), which is generally non-deterministic polynomial-time (NP)-hard. We introduce a hybrid heuristic algorithm for this problem. The hybrid heuristic includes an estimation-of-distribution algorithm (EDA) for performing power allocation and iterative greedy schemes for constraint satisfaction and relay assignment. We analyze the throughput and power consumption tradeoff in GC-CRSN. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results. PMID:23584119

  17. Estimation of Distribution Algorithm for Resource Allocation in Green Cooperative Cognitive Radio Sensor Networks

    PubMed Central

    Naeem, Muhammad; Pareek, Udit; Lee, Daniel C.; Anpalagan, Alagan

    2013-01-01

    Due to the rapid increase in the usage and demand of wireless sensor networks (WSN), the limited frequency spectrum available for WSN applications will be extremely crowded in the near future. More sensor devices also mean more recharging/replacement of batteries, which will cause significant impact on the global carbon footprint. In this paper, we propose a relay-assisted cognitive radio sensor network (CRSN) that allocates communication resources in an environmentally friendly manner. We use shared band amplify and forward relaying for cooperative communication in the proposed CRSN. We present a multi-objective optimization architecture for resource allocation in a green cooperative cognitive radio sensor network (GC-CRSN). The proposed multi-objective framework jointly performs relay assignment and power allocation in GC-CRSN, while optimizing two conflicting objectives. The first objective is to maximize the total throughput, and the second objective is to minimize the total transmission power of CRSN. The proposed relay assignment and power allocation problem is a non-convex mixed-integer non-linear optimization problem (NC-MINLP), which is generally non-deterministic polynomial-time (NP)-hard. We introduce a hybrid heuristic algorithm for this problem. The hybrid heuristic includes an estimation-of-distribution algorithm (EDA) for performing power allocation and iterative greedy schemes for constraint satisfaction and relay assignment. We analyze the throughput and power consumption tradeoff in GC-CRSN. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results. PMID:23584119

  18. An autonomous recovery mechanism against optical distribution network failures in EPON

    NASA Astrophysics Data System (ADS)

    Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar

    2014-10-01

    Ethernet Passive Optical Network (EPON) is chosen for servicing diverse applications with higher bandwidth and Quality-of-Service (QoS), starting from Fiber-To-The-Home (FTTH), FTTB (business/building) and FTTO (office). Typically, a single OLT can provide services to both residential and business customers on the same Optical Line Terminal (OLT) port; thus, any failures in the system will cause a great loss for both network operators and customers. Network operators are looking for low-cost and high service availability mechanisms that focus on the failures that occur within the drop fiber section because the majority of faults are in this particular section. Therefore, in this paper, we propose an autonomous recovery mechanism that provides protection and recovery against Drop Distribution Fiber (DDF) link faults or transceiver failure at the ONU(s) in EPON systems. In the proposed mechanism, the ONU can automatically detect any signal anomalies in the physical layer or transceiver failure, switching the working line to the protection line and sending the critical event alarm to OLT via its neighbor. Each ONU has a protection line, which is connected to the nearest neighbor ONU, and therefore, when failure occurs, the ONU can still transmit and receive data via the neighbor ONU. Lastly, the Fault Dynamic Bandwidth Allocation for recovery mechanism is presented. Simulation results show that our proposed autonomous recovery mechanism is able to maintain the overall QoS performance in terms of mean packet delay, system throughput, packet loss and EF jitter.

  19. Estimation of regional recharge in the HOBE catchment using data from a distributed soil moisture network

    NASA Astrophysics Data System (ADS)

    Andreasen, M.; Andreasen, L. A.; Bircher, S.; Sonnenborg, T.; Jensen, K. H.

    2012-12-01

    The regional variation of recharge of ground water is dependent on a larger number of variables and conditions and is therefore difficult to quantify. In this study we have estimated regional recharge using data from a distributed network of soil moisture stations within the HOBE catchment. The network has been designed in an arrangement of three clusters along a long-term precipitation gradient and the stations have been distributed according to respective fractions of classes combining the prevailing land use, top- and subsoil conditions. At each of the 30 stations water content has been measured at three depths (0-5cm, 20-25cm and 50-55cm) for the period 2009-2011 at a temporal resolution of 30 minutes. The 1D soil-plant-atmosphere system model DAISY has been applied to each of the field locations to simulate the water balance of the root zone and the associated components of evapotranspiration and recharge. The 30 models have been formulated and parameterized using specific information on local climate, soil texture, land use and management. Each model was calibrated to the measured soil water content from the distributed network using the PEST (Parameter ESTimation) software. The calibrated parameters were saturated hydraulic conductivity Ks and van Genuchten parameter n as they were found most sensitive. The 30 sets of results were averaged to represent the mean conditions of the catchment. An effective parameterization was also determined by calibration against mean soil moisture and compared to the results obtained by using effective parameters using various averaging methods. The regional variation in groundwater recharge, actual evapotranspiration and soil water content in the catchment was dependent on land use. The simulated results showed that the largest recharge was found at the agricultural sites (554 mm/yr) and the lowest at the forested sites (257 mm/yr). Correspondingly, the highest actual evapotranspiration was found at the forested sites (614

  20. Energy-efficient distributed constructions of miniumum spanning tree for wireless ad-hoc networks

    SciTech Connect

    Kumar, V. S. A.; Pandurangan, G.; Khan, M.

    2004-01-01

    The Minimum Spanning Tree (MST) problem is one of the most important and commonly occurring primitive in the design and operation of data and communication networks. While there a redistributed algorithms for the MST problem these require relatively large number of messages and time, and are fairly involved, require synchronization and a lot of book keeping; this makes these algorithms impractical for emerging technologies such as ad hoc and sensor networks. In such networks, a sensor has very limited power, and any algorithm needs to be simple, local and energy efficient for being practical. Motivated by these considerations, we study the performance of a class of simple and local algorithms called Nearest Neighbor Tree (NNT) algorithms for energy-efficient construction of MSTs in a wireless ad hoc setting. These employ a very simple idea to eliminate the work involved in cycle detection in other MST algorithms: each node chooses a distinct rank, and connects to the closest node of higher rank. We consider two variants of the NNT algorithms, obtained by two ways of choosing the ranks: (i) Random NNT, in which each node chooses a rank randomly, and (ii) Directional NNT, in which each node uses directional information for choosing the rank. We show provable bounds on the performance of these algorithms in instances obtained by uniformly distributed points in the unit square. Finally, we perform extensive simulations of our algorithms. We tested our algorithms on both uniformly random distributions of points, and on realistic distributions of points in an urban setting. The cost of the tree found by the NNT algorithms is within a factor of 2 of the MST, but there is more than a ten-fold saving on the energy and about a five fold saving on the number of messages sent. Also, our algorithms are significantly simpler to implement compared to, for instance, the GHS algorithm, which is essentially optimal with regards to the message complexity. Thus, our results