Sonification of network traffic flow for monitoring and situational awareness
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543
Sonification of network traffic flow for monitoring and situational awareness.
Debashi, Mohamed; Vickers, Paul
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.
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.
Traffic Driven Analysis of Cellular and WiFi Networks
ERIC Educational Resources Information Center
Paul, Utpal Kumar
2012-01-01
Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…
NASA Technical Reports Server (NTRS)
Robinson, Julie A.; Tate-Brown, Judy M.
2009-01-01
Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.
Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong
2015-01-01
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404
Peeking Network States with Clustered Patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Jinoh; Sim, Alex
2015-10-20
Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learningmore » tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.« less
Traffic Profiling in Wireless Sensor Networks
2006-12-01
components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.
Cellphone probes as an ATMS tool
DOT National Transportation Integrated Search
2003-06-01
The foundation of traffic operations and management is the ability to monitor traffic conditions. One approach to traffic monitoring is to sample conditions by tracking a limited number of probe vehicles as they traverse a network. An emerging techno...
Traffic flow collection wireless sensor network node for intersection light control
NASA Astrophysics Data System (ADS)
Li, Xu; Li, Xue
2011-10-01
Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.
Improving the effectiveness of traffic monitoring based on wireless location technology.
DOT National Transportation Integrated Search
2004-01-01
A fundamental requirement for effectively monitoring and operating transportation facilities is reliable, accurate data on traffic flow. The current state of the practice is to use networks of point detectors to gather information on traffic flow at ...
Toward a Scalable Visualization System for Network Traffic Monitoring
NASA Astrophysics Data System (ADS)
Malécot, Erwan Le; Kohara, Masayoshi; Hori, Yoshiaki; Sakurai, Kouichi
With the multiplication of attacks against computer networks, system administrators are required to monitor carefully the traffic exchanged by the networks they manage. However, that monitoring task is increasingly laborious because of the augmentation of the amount of data to analyze. And that trend is going to intensify with the explosion of the number of devices connected to computer networks along with the global rise of the available network bandwidth. So system administrators now heavily rely on automated tools to assist them and simplify the analysis of the data. Yet, these tools provide limited support and, most of the time, require highly skilled operators. Recently, some research teams have started to study the application of visualization techniques to the analysis of network traffic data. We believe that this original approach can also allow system administrators to deal with the large amount of data they have to process. In this paper, we introduce a tool for network traffic monitoring using visualization techniques that we developed in order to assist the system administrators of our corporate network. We explain how we designed the tool and some of the choices we made regarding the visualization techniques to use. The resulting tool proposes two linked representations of the network traffic and activity, one in 2D and the other in 3D. As 2D and 3D visualization techniques have different assets, we resulted in combining them in our tool to take advantage of their complementarity. We finally tested our tool in order to evaluate the accuracy of our approach.
A network monitor for HTTPS protocol based on proxy
NASA Astrophysics Data System (ADS)
Liu, Yangxin; Zhang, Lingcui; Zhou, Shuguang; Li, Fenghua
2016-10-01
With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can't filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.
47 CFR 32.6532 - Network administration expense.
Code of Federal Regulations, 2013 CFR
2013-10-01
... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...
47 CFR 32.6532 - Network administration expense.
Code of Federal Regulations, 2012 CFR
2012-10-01
... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...
47 CFR 32.6532 - Network administration expense.
Code of Federal Regulations, 2014 CFR
2014-10-01
... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...
The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.
Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai
2014-06-16
Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.
Effects of Sampling and Spatio/Temporal Granularity in Traffic Monitoring on Anomaly Detectability
NASA Astrophysics Data System (ADS)
Ishibashi, Keisuke; Kawahara, Ryoichi; Mori, Tatsuya; Kondoh, Tsuyoshi; Asano, Shoichiro
We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.
The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring
Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C.; Khang, Soon-Jai
2014-01-01
Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011–2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1–1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring. PMID:24937527
Cooperative Learning for Distributed In-Network Traffic Classification
NASA Astrophysics Data System (ADS)
Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.
2017-04-01
Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.
An approach to online network monitoring using clustered patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Jinoh; Sim, Alex; Suh, Sang C.
Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less
An approach to online network monitoring using clustered patterns
Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...
2017-03-13
Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less
Monitor Network Traffic with Packet Capture (pcap) on an Android Device
2015-09-01
administrative privileges . Under the current design Android development requirement, an Android Graphical User Interface (GUI) application cannot directly...build an Android application to monitor network traffic using open source packet capture (pcap) libraries. 15. SUBJECT TERMS ELIDe, Android , pcap 16...Building Application with Native Codes 5 8.1 Calling Native Codes Using JNI 5 8.2 Calling Native Codes from an Android Application 8 9. Retrieve Live
Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.
Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon
2018-04-03
Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.
Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
NASA Astrophysics Data System (ADS)
Hamdan, H. G. Muhammad; Khalifah, O. O.
2017-11-01
Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.
ERIC Educational Resources Information Center
Sng, Dennis Cheng-Hong
The University of Illinois at Urbana-Champaign (UIUC) has a large campus computer network serving a community of about 20,000 users. With such a large network, it is inevitable that there are a wide variety of technologies co-existing in a multi-vendor environment. Effective network monitoring tools can help monitor traffic and link usage, as well…
DOT National Transportation Integrated Search
2002-04-01
Louisianan has established a traffic monitoring program, compliant with FHWA incentives, that is designed to collect and manage the traffic data needed for the design and management of LADOTD's network of current and future highways. In the early 198...
Report on the Dagstuhl Seminar on Visualization and Monitoring of Network Traffic
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keim, Daniel; Pras, Aiko; Schonwalder, Jurgen
2011-01-26
The Dagstuhl Seminar on Visualization and Monitoring of Network Traffic [1] took place May 17-20, 2009 in Dagstuhl, Germany. Dagstuhl seminars promote personal interaction and open discussion of results as well as new ideas. Unlike at most conferences, the focus is not solely on the presentation of established results but to equal parts on results, ideas, sketches, and open problems. The aim of this particular seminar was to bring together experts from the information visualization community and the networking community in order to discuss the state of the art of monitoring and visualization of network traffic. People from the differentmore » research communities involved jointly organized the seminar. The co-chairs of the seminar from the networking community were Aiko Pras (University of Twente) and Jürgen Schönwälder (Jacobs University Bremen). The co-chairs from the visualization community were Daniel A. Keim (University of Konstanz) and Pak Chung Wong (Pacific Northwest National Lab). Florian Mansmann (University of Konstanz) helped with producing this report. The seminar was organized and supported by Schloss Dagstuhl and the EC IST-EMANICS Network of Excellence [1].« less
High-speed and high-fidelity system and method for collecting network traffic
Weigle, Eric H [Los Alamos, NM
2010-08-24
A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.
Clustering and Flow Conservation Monitoring Tool for Software Defined Networks
Puente Fernández, Jesús Antonio
2018-01-01
Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches. PMID:29614049
A wireless sensor network for urban traffic characterization and trend monitoring.
Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A
2015-10-15
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.
Report: Improvements Needed in EPA’s Network Traffic Management Practices
Report #11-P-0159, March 14, 2011. OEI does not have consistent, repeatable intrusion detection system monitoring practices in place, which inhibits EPA’s ability to monitor unusual network activity and thus protect Agency systems and associated data.
With Geospatial in Path of Smart City
NASA Astrophysics Data System (ADS)
Homainejad, A. S.
2015-04-01
With growth of urbanisation, there is a requirement for using the leverage of smart city in city management. The core of smart city is Information and Communication Technologies (ICT), and one of its elements is smart transport which includes sustainable transport and Intelligent Transport Systems (ITS). Cities and especially megacities are facing urgent transport challenge in traffic management. Geospatial can provide reliable tools for monitoring and coordinating traffic. In this paper a method for monitoring and managing the ongoing traffic in roads using aerial images and CCTV will be addressed. In this method, the road network was initially extracted and geo-referenced and captured in a 3D model. The aim is to detect and geo-referenced any vehicles on the road from images in order to assess the density and the volume of vehicles on the roads. If a traffic jam was recognised from the images, an alternative route would be suggested for easing the traffic jam. In a separate test, a road network was replicated in the computer and a simulated traffic was implemented in order to assess the traffic management during a pick time using this method.
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-01-01
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-11-27
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.
Faro, Alberto; Giordano, Daniela; Spampinato, Concetto
2008-06-01
This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.
VoIP attacks detection engine based on neural network
NASA Astrophysics Data System (ADS)
Safarik, Jakub; Slachta, Jiri
2015-05-01
The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.
Real-time stress monitoring of highway bridges with a secured wireless sensor network.
DOT National Transportation Integrated Search
2011-12-01
"This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...
A subjective scheduler for subjective dedicated networks
NASA Astrophysics Data System (ADS)
Suherman; Fakhrizal, Said Reza; Al-Akaidi, Marwan
2017-09-01
Multiple access technique is one of important techniques within medium access layer in TCP/IP protocol stack. Each network technology implements the selected access method. Priority can be implemented in those methods to differentiate services. Some internet networks are dedicated for specific purpose. Education browsing or tutorial video accesses are preferred in a library hotspot, while entertainment and sport contents could be subjects of limitation. Current solution may use IP address filter or access list. This paper proposes subjective properties of users or applications are used for priority determination in multiple access techniques. The NS-2 simulator is employed to evaluate the method. A video surveillance network using WiMAX is chosen as the object. Subjective priority is implemented on WiMAX scheduler based on traffic properties. Three different traffic sources from monitoring video: palace, park, and market are evaluated. The proposed subjective scheduler prioritizes palace monitoring video that results better quality, xx dB than the later monitoring spots.
Yoon, Hong-Jun; Tourassi, Georgia
2014-05-01
Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples' behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of "leaders" on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of "followers", people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.
A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring
Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.
2015-01-01
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278
Low Cost Wireless Network Camera Sensors for Traffic Monitoring
DOT National Transportation Integrated Search
2012-07-01
Many freeways and arterials in major cities in Texas are presently equipped with video detection cameras to : collect data and help in traffic/incident management. In this study, carefully controlled experiments determined : the throughput and output...
NASA Astrophysics Data System (ADS)
Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.
2017-09-01
Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.
Alternative approaches to condition monitoring in freeway management systems.
DOT National Transportation Integrated Search
2002-01-01
In response to growing concerns over traffic congestion, traffic management systems have been built in large urban areas in an effort to improve the efficiency and safety of the transportation network. This research effort developed an automated cond...
NCC Simulation Model: Simulating the operations of the network control center, phase 2
NASA Technical Reports Server (NTRS)
Benjamin, Norman M.; Paul, Arthur S.; Gill, Tepper L.
1992-01-01
The simulation of the network control center (NCC) is in the second phase of development. This phase seeks to further develop the work performed in phase one. Phase one concentrated on the computer systems and interconnecting network. The focus of phase two will be the implementation of the network message dialogues and the resources controlled by the NCC. These resources are requested, initiated, monitored and analyzed via network messages. In the NCC network messages are presented in the form of packets that are routed across the network. These packets are generated, encoded, decoded and processed by the network host processors that generate and service the message traffic on the network that connects these hosts. As a result, the message traffic is used to characterize the work done by the NCC and the connected network. Phase one of the model development represented the NCC as a network of bi-directional single server queues and message generating sources. The generators represented the external segment processors. The served based queues represented the host processors. The NCC model consists of the internal and external processors which generate message traffic on the network that links these hosts. To fully realize the objective of phase two it is necessary to identify and model the processes in each internal processor. These processes live in the operating system of the internal host computers and handle tasks such as high speed message exchanging, ISN and NFE interface, event monitoring, network monitoring, and message logging. Inter process communication is achieved through the operating system facilities. The overall performance of the host is determined by its ability to service messages generated by both internal and external processors.
Intelligent Traffic Quantification System
NASA Astrophysics Data System (ADS)
Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta
2017-08-01
Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.
Assessment of traffic noise levels in urban areas using different soft computing techniques.
Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D
2016-10-01
Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.
An Energy-Efficient MAC Protocol for Medical Emergency Monitoring Body Sensor Networks
Zhang, Chongqing; Wang, Yinglong; Liang, Yongquan; Shu, Minglei; Chen, Changfang
2016-01-01
Medical emergency monitoring body sensor networks (BSNs) monitor the occurrence of medical emergencies and are helpful for the daily care of the elderly and chronically ill people. Such BSNs are characterized by rare traffic when there is no emergency occurring, high real-time and reliable requirements of emergency data and demand for a fast wake-up mechanism for waking up all nodes when an emergency happens. A beacon-enabled MAC protocol is specially designed to meet the demands of medical emergency monitoring BSNs. The rarity of traffic is exploited to improve energy efficiency. By adopting a long superframe structure to avoid unnecessary beacons and allocating most of the superframe to be inactive periods, the duty cycle is reduced to an extremely low level to save energy. Short active time slots are interposed into the superframe and shared by all of the nodes to deliver the emergency data in a low-delay and reliable way to meet the real-time and reliable requirements. The interposition slots can also be used by the coordinator to broadcast network demands to wake-up all nodes in a low-delay and energy-efficient way. Experiments display that the proposed MAC protocol works well in BSNs with low emergency data traffic. PMID:26999145
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoon, Hong-Jun; Tourassi, Georgia
Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of leaders on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of followers , people who never discussed the topicsmore » before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.« less
MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems
2007-05-03
34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each
Mapping edge-based traffic measurements onto the internal links in MPLS network
NASA Astrophysics Data System (ADS)
Zhao, Guofeng; Tang, Hong; Zhang, Yi
2004-09-01
Applying multi-protocol label switching techniques to IP-based backbone for traffic engineering goals has shown advantageous. Obtaining a volume of load on each internal link of the network is crucial for traffic engineering applying. Though collecting can be available for each link, such as applying traditional SNMP scheme, the approach may cause heavy processing load and sharply degrade the throughput of the core routers. Then monitoring merely at the edge of the network and mapping the measurements onto the core provides a good alternative way. In this paper, we explore a scheme for traffic mapping with edge-based measurements in MPLS network. It is supposed that the volume of traffic on each internal link over the domain would be mapped onto by measurements available only at ingress nodes. We apply path-based measurements at ingress nodes without enabling measurements in the core of the network. We propose a method that can infer a path from the ingress to the egress node using label distribution protocol without collecting routing data from core routers. Based on flow theory and queuing theory, we prove that our approach is effective and present the algorithm for traffic mapping. We also show performance simulation results that indicate potential of our approach.
USDA-ARS?s Scientific Manuscript database
Despite increasing amounts of transportation related activities on rangelands globally, few tools exist for assessing and monitoring impacts of roads, road networks and off-road vehicle traffic. This is in part due to an historical emphasis on grazing issues in rangelands and the complexity of monit...
An efficient method to detect periodic behavior in botnet traffic by analyzing control plane traffic
AsSadhan, Basil; Moura, José M.F.
2013-01-01
Botnets are large networks of bots (compromised machines) that are under the control of a small number of bot masters. They pose a significant threat to Internet’s communications and applications. A botnet relies on command and control (C2) communications channels traffic between its members for its attack execution. C2 traffic occurs prior to any attack; hence, the detection of botnet’s C2 traffic enables the detection of members of the botnet before any real harm happens. We analyze C2 traffic and find that it exhibits a periodic behavior. This is due to the pre-programmed behavior of bots that check for updates to download them every T seconds. We exploit this periodic behavior to detect C2 traffic. The detection involves evaluating the periodogram of the monitored traffic. Then applying Walker’s large sample test to the periodogram’s maximum ordinate in order to determine if it is due to a periodic component or not. If the periodogram of the monitored traffic contains a periodic component, then it is highly likely that it is due to a bot’s C2 traffic. The test looks only at aggregate control plane traffic behavior, which makes it more scalable than techniques that involve deep packet inspection (DPI) or tracking the communication flows of different hosts. We apply the test to two types of botnet, tinyP2P and IRC that are generated by SLINGbot. We verify the periodic behavior of their C2 traffic and compare it to the results we get on real traffic that is obtained from a secured enterprise network. We further study the characteristics of the test in the presence of injected HTTP background traffic and the effect of the duty cycle on the periodic behavior. PMID:25685512
Traffic Congestion Detection System through Connected Vehicles and Big Data
Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo
2016-01-01
This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur. PMID:27136548
Traffic Congestion Detection System through Connected Vehicles and Big Data.
Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo
2016-04-28
This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
Fiber optic sensor for monitoring a density of road traffic
NASA Astrophysics Data System (ADS)
Nedoma, Jan; Fajkus, Marcel; Martinek, Radek; Mec, Pavel; Novak, Martin; Jargus, Jan; Vasinek, Vladimir
2017-10-01
Authors of this article have focused on the use of fiber-optic technology in the car traffic. The article describes the use of fiber-optic interferometer for the purpose of the dynamic calculation of traffic density and inclusion the vehicle into the traffic lane. The objective is to increase safety and traffic flow. Presented solution is characterized by the non-destructive character to the road - sensor no need built into the roadway. The sensor works with standard telecommunications fibers of the G.652 standard. Other hallmarks are immunity to electromagnetic interference (EMI) and passivity of concerning the power supply. The massive expansion of optical cables within telecommunication needs along roads offers the possibility of connecting to the existing telecommunications fiber-optic network without a converter. Information can be transmitted at distances of several km up to tens km by this fiber-optic network. Set of experimental measurements in real traffic flow verified the functionality of presented solution.
A lightweight network anomaly detection technique
Kim, Jinoh; Yoo, Wucherl; Sim, Alex; ...
2017-03-13
While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less
A lightweight network anomaly detection technique
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Jinoh; Yoo, Wucherl; Sim, Alex
While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less
Monitoring and assessing global impacts of roads and off-road vehicle traffic
USDA-ARS?s Scientific Manuscript database
Rapid increases in the number of vehicles, urban sprawl, exurban development and infrastructure development for energy and water have led to dramatic increases in both the size and extent of the global road network. Anecdotal evidence suggests that off-road vehicle traffic has also increased in many...
Remotely Accessed Vehicle Traffic Management System
NASA Astrophysics Data System (ADS)
Al-Alawi, Raida
2010-06-01
The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.
DAMT - DISTRIBUTED APPLICATION MONITOR TOOL (HP9000 VERSION)
NASA Technical Reports Server (NTRS)
Keith, B.
1994-01-01
Typical network monitors measure status of host computers and data traffic among hosts. A monitor to collect statistics about individual processes must be unobtrusive and possess the ability to locate and monitor processes, locate and monitor circuits between processes, and report traffic back to the user through a single application program interface (API). DAMT, Distributed Application Monitor Tool, is a distributed application program that will collect network statistics and make them available to the user. This distributed application has one component (i.e., process) on each host the user wishes to monitor as well as a set of components at a centralized location. DAMT provides the first known implementation of a network monitor at the application layer of abstraction. Potential users only need to know the process names of the distributed application they wish to monitor. The tool locates the processes and the circuit between them, and reports any traffic between them at a user-defined rate. The tool operates without the cooperation of the processes it monitors. Application processes require no changes to be monitored by this tool. Neither does DAMT require the UNIX kernel to be recompiled. The tool obtains process and circuit information by accessing the operating system's existing process database. This database contains all information available about currently executing processes. Expanding the information monitored by the tool can be done by utilizing more information from the process database. Traffic on a circuit between processes is monitored by a low-level LAN analyzer that has access to the raw network data. The tool also provides features such as dynamic event reporting and virtual path routing. A reusable object approach was used in the design of DAMT. The tool has four main components; the Virtual Path Switcher, the Central Monitor Complex, the Remote Monitor, and the LAN Analyzer. All of DAMT's components are independent, asynchronously executing processes. The independent processes communicate with each other via UNIX sockets through a Virtual Path router, or Switcher. The Switcher maintains a routing table showing the host of each component process of the tool, eliminating the need for each process to do so. The Central Monitor Complex provides the single application program interface (API) to the user and coordinates the activities of DAMT. The Central Monitor Complex is itself divided into independent objects that perform its functions. The component objects are the Central Monitor, the Process Locator, the Circuit Locator, and the Traffic Reporter. Each of these objects is an independent, asynchronously executing process. User requests to the tool are interpreted by the Central Monitor. The Process Locator identifies whether a named process is running on a monitored host and which host that is. The circuit between any two processes in the distributed application is identified using the Circuit Locator. The Traffic Reporter handles communication with the LAN Analyzer and accumulates traffic updates until it must send a traffic report to the user. The Remote Monitor process is replicated on each monitored host. It serves the Central Monitor Complex processes with application process information. The Remote Monitor process provides access to operating systems information about currently executing processes. It allows the Process Locator to find processes and the Circuit Locator to identify circuits between processes. It also provides lifetime information about currently monitored processes. The LAN Analyzer consists of two processes. Low-level monitoring is handled by the Sniffer. The Sniffer analyzes the raw data on a single, physical LAN. It responds to commands from the Analyzer process, which maintains the interface to the Traffic Reporter and keeps track of which circuits to monitor. DAMT is written in C-language for HP-9000 series computers running HP-UX and Sun 3 and 4 series computers running SunOS. DAMT requires 1Mb of disk space and 4Mb of RAM for execution. This package requires MIT's X Window System, Version 11 Revision 4, with OSF/Motif 1.1. The HP-9000 version (GSC-13589) includes sample HP-9000/375 and HP-9000/730 executables which were compiled under HP-UX, and the Sun version (GSC-13559) includes sample Sun3 and Sun4 executables compiled under SunOS. The standard distribution medium for the HP version of DAMT is a .25 inch HP pre-formatted streaming magnetic tape cartridge in UNIX tar format. It is also available on a 4mm magnetic tape in UNIX tar format. The standard distribution medium for the Sun version of DAMT is a .25 inch streaming magnetic tape cartridge in UNIX tar format. It is also available on a 3.5 inch diskette in UNIX tar format. DAMT was developed in 1992.
Monitoring Malware Activity on the LAN Network
NASA Astrophysics Data System (ADS)
Skrzewski, Mirosław
Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.
Remote Video Monitor of Vehicles in Cooperative Information Platform
NASA Astrophysics Data System (ADS)
Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan
Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.
Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.
Al-Medhwahi, Mohammed; Hashim, Fazirulhisyam; Ali, Borhanuddin Mohd; Sali, Aduwati
2016-01-01
The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.
Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks
Ali, Borhanuddin Mohd; Sali, Aduwati
2016-01-01
The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications. PMID:27257964
Experimental system for computer network via satellite /CS/. III - Network control processor
NASA Astrophysics Data System (ADS)
Kakinuma, Y.; Ito, A.; Takahashi, H.; Uchida, K.; Matsumoto, K.; Mitsudome, H.
1982-03-01
A network control processor (NCP) has the functions of generating traffics, the control of links and the control of transmitting bursts. The NCP executes protocols, monitors of experiments, gathering and compiling data of measurements, of which programs are loaded on a minicomputer (MELCOM 70/40) with 512KB of memories. The NCP acts as traffic generators, instead of a host computer, in the experiment. For this purpose, 15 fake stations are realized by the software in each user station. This paper describes the configuration of the NCP and the implementation of the protocols for the experimental system.
DOT National Transportation Integrated Search
1993-06-16
The City of South Lyon converted the traffic signals on the street network from fixed time control to the Sydney Coordinated Adaptive Traffic System (SCATS). The objectives of this research study were to analyze the differences in certain delay param...
Energy Efficient, Cross-Layer Enabled, Dynamic Aggregation Networks for Next Generation Internet
NASA Astrophysics Data System (ADS)
Wang, Michael S.
Today, the Internet traffic is growing at a near exponential rate, driven predominately by data center-based applications and Internet-of-Things services. This fast-paced growth in Internet traffic calls into question the ability of the existing optical network infrastructure to support this continued growth. The overall optical networking equipment efficiency has not been able to keep up with the traffic growth, creating a energy gap that makes energy and cost expenditures scale linearly with the traffic growth. The implication of this energy gap is that it is infeasible to continue using existing networking equipment to meet the growing bandwidth demand. A redesign of the optical networking platform is needed. The focus of this dissertation is on the design and implementation of energy efficient, cross-layer enabled, dynamic optical networking platforms, which is a promising approach to address the exponentially growing Internet bandwidth demand. Chapter 1 explains the motivation for this work by detailing the huge Internet traffic growth and the unsustainable energy growth of today's networking equipment. Chapter 2 describes the challenges and objectives of enabling agile, dynamic optical networking platforms and the vision of the Center for Integrated Access Networks (CIAN) to realize these objectives; the research objectives of this dissertation and the large body of related work in this field is also summarized. Chapter 3 details the design and implementation of dynamic networking platforms that support wavelength switching granularity. The main contribution of this work involves the experimental validation of deep cross-layer communication across the optical performance monitoring (OPM), data, and control planes. The first experiment shows QoS-aware video streaming over a metro-scale test-bed through optical power monitoring of the transmission wavelength and cross-layer feedback control of the power level. The second experiment extends the performance monitoring capabilities to include real-time monitoring of OSNR and polarization mode dispersion (PMD) to enable dynamic wavelength switching and selective restoration. Chapter 4 explains the author?s contributions in designing dynamic networking at the sub-wavelength switching granularity, which can provide greater network efficiency due to its finer granularity. To support dynamic switching, regeneration, adding/dropping, and control decisions on each individual packet, the cross-layer enabled node architecture is enhanced with a FPGA controller that brings much more precise timing and control to the switching, OPM, and control planes. Furthermore, QoS-aware packet protection and dynamic switching, dropping, and regeneration functionalities were experimentally demonstrated in a multi-node network. Chapter 5 describes a technique to perform optical grooming, a process of optically combining multiple incoming data streams into a single data stream, which can simultaneously achieve greater bandwidth utilization and increased spectral efficiency. In addition, an experimental demonstration highlighting a fully functioning multi-node, agile optical networking platform is detailed. Finally, a summary and discussion of future work is provided in Chapter 6. The future of the Internet is very exciting, filled with not-yet-invented applications and services driven by cloud computing and Internet-of-Things. The author is cautiously optimistic that agile, dynamically reconfigurable optical networking is the solution to realizing this future.
Virtual Induction Loops Based on Cooperative Vehicular Communications
Gramaglia, Marco; Bernardos, Carlos J.; Calderon, Maria
2013-01-01
Induction loop detectors have become the most utilized sensors in traffic management systems. The gathered traffic data is used to improve traffic efficiency (i.e., warning users about congested areas or planning new infrastructures). Despite their usefulness, their deployment and maintenance costs are expensive. Vehicular networks are an emerging technology that can support novel strategies for ubiquitous and more cost-effective traffic data gathering. In this article, we propose and evaluate VIL (Virtual Induction Loop), a simple and lightweight traffic monitoring system based on cooperative vehicular communications. The proposed solution has been experimentally evaluated through simulation using real vehicular traces. PMID:23348033
Network monitoring in the Tier2 site in Prague
NASA Astrophysics Data System (ADS)
Eliáš, Marek; Fiala, Lukáš; Horký, Jiří; Chudoba, Jiří; Kouba, Tomáš; Kundrát, Jan; Švec, Jan
2011-12-01
Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.
A Survey on Urban Traffic Management System Using Wireless Sensor Networks.
Nellore, Kapileswar; Hancke, Gerhard P
2016-01-27
Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.
A Survey on Urban Traffic Management System Using Wireless Sensor Networks
Nellore, Kapileswar; Hancke, Gerhard P.
2016-01-01
Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research. PMID:26828489
Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.
Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi
2016-01-01
Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.
Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks
Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi
2016-01-01
Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977
A neural-visualization IDS for honeynet data.
Herrero, Álvaro; Zurutuza, Urko; Corchado, Emilio
2012-04-01
Neural intelligent systems can provide a visualization of the network traffic for security staff, in order to reduce the widely known high false-positive rate associated with misuse-based Intrusion Detection Systems (IDSs). Unlike previous work, this study proposes an unsupervised neural models that generate an intuitive visualization of the captured traffic, rather than network statistics. These snapshots of network events are immensely useful for security personnel that monitor network behavior. The system is based on the use of different neural projection and unsupervised methods for the visual inspection of honeypot data, and may be seen as a complementary network security tool that sheds light on internal data structures through visual inspection of the traffic itself. Furthermore, it is intended to facilitate verification and assessment of Snort performance (a well-known and widely-used misuse-based IDS), through the visualization of attack patterns. Empirical verification and comparison of the proposed projection methods are performed in a real domain, where two different case studies are defined and analyzed.
An Implementation of Wireless Body Area Networks for Improving Priority Data Transmission Delay.
Gündoğdu, Köksal; Çalhan, Ali
2016-03-01
The rapid growth of wireless sensor networks has enabled the human health monitoring of patients using body sensor nodes that gather and evaluate human body parameters and movements. This study describes both simulation model and implementation of a new traffic sensitive wireless body area network by using non-preemptive priority queue discipline. A wireless body area network implementation employing TDMA is designed with three different priorities of data traffics. Besides, a coordinator node having the non-preemptive priority queue is performed in this study. We have also developed, modeled and simulated example network scenarios by using the Riverbed Modeler simulation software with the purpose of verifying the implementation results. The simulation results obtained under various network load conditions are consistent with the implementation results.
Network Monitoring Traffic Compression Using Singular Value Decomposition
2014-03-27
Shootouts." Workshop on Intrusion Detection and Network Monitoring. 1999. [12] Goodall , John R. "Visualization is better! a comparative evaluation...34 Visualization for Cyber Security, 2009. VizSec 2009. 6th International Workshop on IEEE, 2009. [13] Goodall , John R., and Mark Sowul. "VIAssist...Viruses and Log Visualization.” In Australian Digital Forensics Conference. Paper 54, 2008. [30] Tesone, Daniel R., and John R. Goodall . "Balancing
DOE Office of Scientific and Technical Information (OSTI.GOV)
- PNNL, Harold Trease
2012-10-10
ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.
Monitoring of heavy metal concentrations in home outdoor air using moss bags.
Rivera, Marcela; Zechmeister, Harald; Medina-Ramón, Mercedes; Basagaña, Xavier; Foraster, Maria; Bouso, Laura; Moreno, Teresa; Solanas, Pascual; Ramos, Rafael; Köllensperger, Gunda; Deltell, Alexandre; Vizcaya, David; Künzli, Nino
2011-04-01
One monitoring station is insufficient to characterize the high spatial variation of traffic-related heavy metals within cities. We tested moss bags (Hylocomium splendens), deployed in a dense network, for the monitoring of metals in outdoor air and characterized metals' long-term spatial distribution and its determinants in Girona, Spain. Mosses were exposed outside 23 homes for two months; NO₂ was monitored for comparison. Metals were not highly correlated with NO₂ and showed higher spatial variation than NO₂. Regression models explained 61-85% of Cu, Cr, Mo, Pb, Sb, Sn, and Zn and 72% of NO₂ variability. Metals were strongly associated with the number of bus lines in the nearest street. Heavy metals are an alternative traffic-marker to NO₂ given their toxicological relevance, stronger association with local traffic and higher spatial variability. Monitoring heavy metals with mosses is appealing, particularly for long-term exposure assessment, as mosses can remain on site many months without maintenance. Copyright © 2010 Elsevier Ltd. All rights reserved.
Research on moving target defense based on SDN
NASA Astrophysics Data System (ADS)
Chen, Mingyong; Wu, Weimin
2017-08-01
An address mutation strategy was proposed. This strategy provided an unpredictable change in address, replacing the real address of the packet forwarding process and path mutation, thus hiding the real address of the host and path. a mobile object defense technology based on Spatio-temporal Mutation on this basis is proposed, Using the software Defined Network centralized control architecture advantage combines sFlow traffic monitoring technology and Moving Target Defense. A mutated time period which can be changed in real time according to the network traffic is changed, and the destination address is changed while the controller abruptly changes the address while the data packet is transferred between the switches to construct a moving target, confusing the host within the network, thereby protecting the host and network.
The Alaska Volcano Observatory - Expanded Monitoring of Volcanoes Yields Results
Brantley, Steven R.; McGimsey, Robert G.; Neal, Christina A.
2004-01-01
Recent explosive eruptions at some of Alaska's 52 historically active volcanoes have significantly affected air traffic over the North Pacific, as well as Alaska's oil, power, and fishing industries and local communities. Since its founding in the late 1980s, the Alaska Volcano Observatory (AVO) has installed new monitoring networks and used satellite data to track activity at Alaska's volcanoes, providing timely warnings and monitoring of frequent eruptions to the aviation industry and the general public. To minimize impacts from future eruptions, scientists at AVO continue to assess volcano hazards and to expand monitoring networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Huan; Cheng, Liang; Chuah, Mooi Choo
In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impactsmore » of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.« less
Valdivieso Caraguay, Ángel Leonardo; García Villalba, Luis Javier
2017-01-01
This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors. PMID:28362346
Caraguay, Ángel Leonardo Valdivieso; Villalba, Luis Javier García
2017-03-31
This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.
Modeling DNP3 Traffic Characteristics of Field Devices in SCADA Systems of the Smart Grid
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Huan; Cheng, Liang; Chuah, Mooi Choo
In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impactsmore » of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.« less
NASA Astrophysics Data System (ADS)
Balouchestani, Mohammadreza
2017-05-01
Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.
Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks
Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing
2016-01-01
Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871
Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio
2016-12-29
One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps' generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.
Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio
2016-01-01
One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work. PMID:28036065
Fault-Tolerant Local-Area Network
NASA Technical Reports Server (NTRS)
Morales, Sergio; Friedman, Gary L.
1988-01-01
Local-area network (LAN) for computers prevents single-point failure from interrupting communication between nodes of network. Includes two complete cables, LAN 1 and LAN 2. Microprocessor-based slave switches link cables to network-node devices as work stations, print servers, and file servers. Slave switches respond to commands from master switch, connecting nodes to two cable networks or disconnecting them so they are completely isolated. System monitor and control computer (SMC) acts as gateway, allowing nodes on either cable to communicate with each other and ensuring that LAN 1 and LAN 2 are fully used when functioning properly. Network monitors and controls itself, automatically routes traffic for efficient use of resources, and isolates and corrects its own faults, with potential dramatic reduction in time out of service.
NASA Astrophysics Data System (ADS)
Naim, Nani Fadzlina; Ab-Rahman, Mohammad Syuhaimi; Kamaruddin, Nur Hasiba; Bakar, Ahmad Ashrif A.
2013-09-01
Nowadays, optical networks are becoming dense while detecting faulty branches in the tree-structured networks has become problematic. Conventional methods are inconvenient as they require an engineer to visit the failure site to check the optical fiber using an optical time-domain reflectometer. An innovative monitoring technique for tree-structured network topology in Ethernet passive optical networks (EPONs) by using the erbium-doped fiber amplifier to amplify the traffic signal is demonstrated, and in the meantime, a residual amplified spontaneous emission spectrum is used as the input signal to monitor the optical cable from the central office. Fiber Bragg gratings with distinct center wavelengths are employed to reflect the monitoring signals. Faulty branches of the tree-structured EPONs can be identified using a simple and low-cost receiver. We will show that this technique is capable of providing monitoring range up to 32 optical network units using a power meter with a sensitivity of -65 dBm while maintaining the bit error rate of 10-13.
NASA Astrophysics Data System (ADS)
Felix, J.
The management center and new circuit switching services offered by the French Telecom I network are described. Attention is focused on business services. The satellite has a 125 Mbit/sec capability distributed over 5 frequency bands, yielding the equivalent of 1800 channels. Data are transmitted in digitized bursts with TDMA techniques. Besides the management center, Telecom I interfaces with 310 local network antennas with access managed by the center through a reservation service and protocol assignment. The center logs and supervises alarms and network events, monitors traffic, logs taxation charges and manages the man-machine dialog for TDMA and terrestrial operations. Time slots are arranged in terms of minimal 10 min segments. The reservations can be directly accessed by up to 1000 terminals. All traffic is handled on a call-by-call basis.
Framework and implementation of a continuous network-wide health monitoring system for roadways
NASA Astrophysics Data System (ADS)
Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar
2014-03-01
According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.
Near real-time traffic routing
NASA Technical Reports Server (NTRS)
Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)
2012-01-01
A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.
Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness
Vollmer, Todd; Manic, Milos; Linda, Ondrej
2013-06-01
The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfiguremore » in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.« less
A GPS-based Real-time Road Traffic Monitoring System
NASA Astrophysics Data System (ADS)
Tanti, Kamal Kumar
In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.
Secured network sensor-based defense system
NASA Astrophysics Data System (ADS)
Wei, Sixiao; Shen, Dan; Ge, Linqiang; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe
2015-05-01
Network sensor-based defense (NSD) systems have been widely used to defend against cyber threats. Nonetheless, if the adversary finds ways to identify the location of monitor sensors, the effectiveness of NSD systems can be reduced. In this paper, we propose both temporal and spatial perturbation based defense mechanisms to secure NSD systems and make the monitor sensor invisible to the adversary. The temporal-perturbation based defense manipulates the timing information of published data so that the probability of successfully recognizing monitor sensors can be reduced. The spatial-perturbation based defense dynamically redeploys monitor sensors in the network so that the adversary cannot obtain the complete information to recognize all of the monitor sensors. We carried out experiments using real-world traffic traces to evaluate the effectiveness of our proposed defense mechanisms. Our data shows that our proposed defense mechanisms can reduce the attack accuracy of recognizing detection sensors.
Air Pollution Monitoring and Mining Based on Sensor Grid in London
Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John
2008-01-01
In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895
Air Pollution Monitoring and Mining Based on Sensor Grid in London.
Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John
2008-06-01
In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.
Optimal Control of Connected and Automated Vehicles at Roundabouts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Liuhui; Malikopoulos, Andreas; Rios-Torres, Jackeline
Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This study investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other and to an infrastructure in roundabouts to achieve a smooth traffic flow without stop-and-go driving. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the efficiency of the proposed approach is validated through simulationmore » and it is shown that coordination of vehicles can reduce total travel time by 3~49% and fuel consumption by 2~27% with respect to different traffic levels. In addition, network throughput is improved by up to 25% due to elimination of stop-and-go driving behavior.« less
Surveying traffic congestion based on the concept of community structure of complex networks
NASA Astrophysics Data System (ADS)
Ma, Lili; Zhang, Zhanli; Li, Meng
2016-07-01
In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.
An optimization model for the US Air-Traffic System
NASA Technical Reports Server (NTRS)
Mulvey, J. M.
1986-01-01
A systematic approach for monitoring U.S. air traffic was developed in the context of system-wide planning and control. Towards this end, a network optimization model with nonlinear objectives was chosen as the central element in the planning/control system. The network representation was selected because: (1) it provides a comprehensive structure for depicting essential aspects of the air traffic system, (2) it can be solved efficiently for large scale problems, and (3) the design can be easily communicated to non-technical users through computer graphics. Briefly, the network planning models consider the flow of traffic through a graph as the basic structure. Nodes depict locations and time periods for either individual planes or for aggregated groups of airplanes. Arcs define variables as actual airplanes flying through space or as delays across time periods. As such, a special case of the network can be used to model the so called flow control problem. Due to the large number of interacting variables and the difficulty in subdividing the problem into relatively independent subproblems, an integrated model was designed which will depict the entire high level (above 29000 feet) jet route system for the 48 contiguous states in the U.S. As a first step in demonstrating the concept's feasibility a nonlinear risk/cost model was developed for the Indianapolis Airspace. The nonlinear network program --NLPNETG-- was employed in solving the resulting test cases. This optimization program uses the Truncated-Newton method (quadratic approximation) for determining the search direction at each iteration in the nonlinear algorithm. It was shown that aircraft could be re-routed in an optimal fashion whenever traffic congestion increased beyond an acceptable level, as measured by the nonlinear risk function.
Congestion control strategy on complex network with privilege traffic
NASA Astrophysics Data System (ADS)
Li, Shi-Bao; He, Ya; Liu, Jian-Hang; Zhang, Zhi-Gang; Huang, Jun-Wei
The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor Ui is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, Ui is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of Ui can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.
Incidents Prediction in Road Junctions Using Artificial Neural Networks
NASA Astrophysics Data System (ADS)
Hajji, Tarik; Alami Hassani, Aicha; Ouazzani Jamil, Mohammed
2018-05-01
The implementation of an incident detection system (IDS) is an indispensable operation in the analysis of the road traffics. However the IDS may, in no case, represent an alternative to the classical monitoring system controlled by the human eye. The aim of this work is to increase detection and prediction probability of incidents in camera-monitored areas. Knowing that, these areas are monitored by multiple cameras and few supervisors. Our solution is to use Artificial Neural Networks (ANN) to analyze moving objects trajectories on captured images. We first propose a modelling of the trajectories and their characteristics, after we develop a learning database for valid and invalid trajectories, and then we carry out a comparative study to find the artificial neural network architecture that maximizes the rate of valid and invalid trajectories recognition.
Wireless sensor networks for heritage object deformation detection and tracking algorithm.
Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu
2014-10-31
Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.
Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm
Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu
2014-01-01
Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458
A novel Smart Routing Protocol for remote health monitoring in Medical Wireless Networks.
Sundararajan, T V P; Sumithra, M G; Maheswar, R
2014-01-01
In a Medical Wireless Network (MWN), sensors constantly monitor patient's physiological condition and movement. Inter-MWN communications are set up between the Patient Server and one or more Centralized Coordinators. However, MWNs require protocols with little energy consumption and the self-organizing attribute perceived in ad-hoc networks. The proposed Smart Routing Protocol (SRP) selects only the nodes with a higher residual energy and lower traffic density for routing. This approach enhances cooperation among the nodes of a Mobile Ad Hoc Network. Consequently, SRP produces better results than the existing protocols, namely Conditional Min-Max Battery Cost Routing, Min-Max Battery Cost Routing and AdHoc On-demand Distance Vector in terms of network parameters. The performance of the erstwhile schemes for routing protocols is evaluated using the network simulator Qualnet v 4.5.
Error monitoring issues for common channel signaling
NASA Astrophysics Data System (ADS)
Hou, Victor T.; Kant, Krishna; Ramaswami, V.; Wang, Jonathan L.
1994-04-01
Motivated by field data which showed a large number of link changeovers and incidences of link oscillations between in-service and out-of-service states in common channel signaling (CCS) networks, a number of analyses of the link error monitoring procedures in the SS7 protocol were performed by the authors. This paper summarizes the results obtained thus far and include the following: (1) results of an exact analysis of the performance of the error monitoring procedures under both random and bursty errors; (2) a demonstration that there exists a range of error rates within which the error monitoring procedures of SS7 may induce frequent changeovers and changebacks; (3) an analysis of the performance ofthe SS7 level-2 transmission protocol to determine the tolerable error rates within which the delay requirements can be met; (4) a demonstration that the tolerable error rate depends strongly on various link and traffic characteristics, thereby implying that a single set of error monitor parameters will not work well in all situations; (5) some recommendations on a customizable/adaptable scheme of error monitoring with a discussion on their implementability. These issues may be particularly relevant in the presence of anticipated increases in SS7 traffic due to widespread deployment of Advanced Intelligent Network (AIN) and Personal Communications Service (PCS) as well as for developing procedures for high-speed SS7 links currently under consideration by standards bodies.
Novel method for fog monitoring using cellular networks infrastructures
NASA Astrophysics Data System (ADS)
David, N.; Alpert, P.; Messer, H.
2012-08-01
A major detrimental effect of fog is visibility limitation which can result in serious transportation accidents, traffic delays and therefore economic damage. Existing monitoring techniques including satellites, transmissometers and human observers - suffer from low spatial resolution, high cost or lack of precision when measuring near ground level. Here we show a novel technique for fog monitoring using wireless communication systems. Communication networks widely deploy commercial microwave links across the terrain at ground level. Operating at frequencies of tens of GHz they are affected by fog and are, effectively, an existing, spatially world-wide distributed sensor network that can provide crucial information about fog concentration and visibility. Fog monitoring potential is demonstrated for a heavy fog event that took place in Israel. The correlation between transmissomters and human eye observations to the visibility estimates from the nearby microwave links was found to be 0.53 and 0.61, respectively. These values indicate the high potential of the proposed method.
Reasoning and Knowledge Acquisition Framework for 5G Network Analytics
2017-01-01
Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473
Fiber optic voice/data network
NASA Technical Reports Server (NTRS)
Bergman, Larry A. (Inventor)
1989-01-01
An asynchronous, high-speed, fiber optic local area network originally developed for tactical environments with additional benefits for other environments such as spacecraft, and the like. The network supports ordinary data packet traffic simultaneously with synchronous T1 voice traffic over a common token ring channel; however, the techniques and apparatus of this invention can be applied to any deterministic class of packet data networks, including multitier backbones, that must transport stream data (e.g., video, SAR, sensors) as well as data. A voice interface module parses, buffers, and resynchronizes the voice data to the packet network employing elastic buffers on both the sending and receiving ends. Voice call setup and switching functions are performed external to the network with ordinary PABX equipment. Clock information is passed across network boundaries in a token passing ring by preceeding the token with an idle period of non-transmission which allows the token to be used to re-establish a clock synchronized to the data. Provision is made to monitor and compensate the elastic receiving buffers so as to prevent them from overflowing or going empty.
Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.
Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier
2017-10-21
Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.
Developing a Framework for Effective Network Capacity Planning
NASA Technical Reports Server (NTRS)
Yaprak, Ece
2005-01-01
As Internet traffic continues to grow exponentially, developing a clearer understanding of, and appropriately measuring, network's performance is becoming ever more critical. An important challenge faced by the Information Resources Directorate (IRD) at the Johnson Space Center in this context remains not only monitoring and maintaining a secure network, but also better understanding the capacity and future growth potential boundaries of its network. This requires capacity planning which involves modeling and simulating different network alternatives, and incorporating changes in design as technologies, components, configurations, and applications change, to determine optimal solutions in light of IRD's goals, objectives and strategies. My primary task this summer was to address this need. I evaluated network-modeling tools from OPNET Technologies Inc. and Compuware Corporation. I generated a baseline model for Building 45 using both tools by importing "real" topology/traffic information using IRD's various network management tools. I compared each tool against the other in terms of the advantages and disadvantages of both tools to accomplish IRD's goals. I also prepared step-by-step "how to design a baseline model" tutorial for both OPNET and Compuware products.
Fine-granularity inference and estimations to network traffic for SDN.
Jiang, Dingde; Huo, Liuwei; Li, Ya
2018-01-01
An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.
Fine-granularity inference and estimations to network traffic for SDN
Huo, Liuwei; Li, Ya
2018-01-01
An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective. PMID:29718913
Dėdelė, Audrius; Miškinytė, Auksė
2015-09-01
In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.
Hybrid monitoring scheme for end-to-end performance enhancement of multicast-based real-time media
NASA Astrophysics Data System (ADS)
Park, Ju-Won; Kim, JongWon
2004-10-01
As real-time media applications based on IP multicast networks spread widely, end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) a next-generation group collaboration tool based on multi-party media services, the applicability of hybrid monitoring scheme that combines active and passive monitoring is investigated. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks both application-layer metrics (i.e., user traffic condition by analyzing RTCP packets) and system metrics. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.
Traffic placement policies for a multi-band network
NASA Technical Reports Server (NTRS)
Maly, Kurt J.; Foudriat, E. C.; Game, David; Mukkamala, R.; Overstreet, C. Michael
1990-01-01
Recently protocols were introduced that enable the integration of synchronous traffic (voice or video) and asynchronous traffic (data) and extend the size of local area networks without loss in speed or capacity. One of these is DRAMA, a multiband protocol based on broadband technology. It provides dynamic allocation of bandwidth among clusters of nodes in the total network. A number of traffic placement policies for such networks are proposed and evaluated. Metrics used for performance evaluation include average network access delay, degree of fairness of access among the nodes, and network throughput. The feasibility of the DRAMA protocol is established through simulation studies. DRAMA provides effective integration of synchronous and asychronous traffic due to its ability to separate traffic types. Under the suggested traffic placement policies, the DRAMA protocol is shown to handle diverse loads, mixes of traffic types, and numbers of nodes, as well as modifications to the network structure and momentary traffic overloads.
Estimating TCP Packet Loss Ratio from Sampled ACK Packets
NASA Astrophysics Data System (ADS)
Yamasaki, Yasuhiro; Shimonishi, Hideyuki; Murase, Tutomu
The advent of various quality-sensitive applications has greatly changed the requirements for IP network management and made the monitoring of individual traffic flows more important. Since the processing costs of per-flow quality monitoring are high, especially in high-speed backbone links, packet sampling techniques have been attracting considerable attention. Existing sampling techniques, such as those used in Sampled NetFlow and sFlow, however, focus on the monitoring of traffic volume, and there has been little discussion of the monitoring of such quality indexes as packet loss ratio. In this paper we propose a method for estimating, from sampled packets, packet loss ratios in individual TCP sessions. It detects packet loss events by monitoring duplicate ACK events raised by each TCP receiver. Because sampling reveals only a portion of the actual packet loss, the actual packet loss ratio is estimated statistically. Simulation results show that the proposed method can estimate the TCP packet loss ratio accurately from a 10% sampling of packets.
NASA Astrophysics Data System (ADS)
Yenier, E.; Baturan, D.; Karimi, S.; Moores, A. O.; Spriggs, N.
2016-12-01
Earthquakes may be induced by man-made activity in the vicinity of critically-stressed fault segments. A number of earthquakes characterized as induced with magnitudes M>3 were recorded in British Columbia, Alberta, Oklahoma and Ohio, since 2013. In response to growing induced seismicity in North America, many jurisdictions have mandated near real-time seismic monitoring around operation sites. The data products from monitoring networks are used as drivers of operational traffic light systems designed to mitigate risks associated with induced seismicity. Most traffic light protocols developed to date use staged thresholds of earthquake magnitudes. Additionally, ground motions, which are used to estimate the impact of earthquakes and specify seismic hazard, have been proposed as an enhancement to the existing protocols. There are several challenges and options to consider at the time of planning and designing a monitoring network, the most important of which is the choice of ground motion sensing technology. In order to accurately estimate event source parameters and ground motions, monitoring instruments have to record and image the low-frequency plateau and the corner frequency of the anticipated event spectrum. A flat response over a wide frequency range with a wide dynamic range is desired for a maximum benefit from ground motion products. This study evaluates the performance of three types of instruments in terms of their suitability for induced seismic monitoring (ISM): broadband seismometers, accelerometers and geophones. Each instrument type is assessed in terms of self-noise, frequency response and clip level using instrument specifications and real-world ISM application data. The impact of each sensing technology on key ISM network performance criteria, event magnitude estimations and ground motion measurements are examined.
Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network
NASA Astrophysics Data System (ADS)
Yang, Bin
2017-07-01
Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately
Effects of traffic generation patterns on the robustness of complex networks
NASA Astrophysics Data System (ADS)
Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui
2018-02-01
Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.
A collaborative network middleware project by Lambda Station, TeraPaths, and Phoebus
NASA Astrophysics Data System (ADS)
Bobyshev, A.; Bradley, S.; Crawford, M.; DeMar, P.; Katramatos, D.; Shroff, K.; Swany, M.; Yu, D.
2010-04-01
The TeraPaths, Lambda Station, and Phoebus projects, funded by the US Department of Energy, have successfully developed network middleware services that establish on-demand and manage true end-to-end, Quality-of-Service (QoS) aware, virtual network paths across multiple administrative network domains, select network paths and gracefully reroute traffic over these dynamic paths, and streamline traffic between packet and circuit networks using transparent gateways. These services improve network QoS and performance for applications, playing a critical role in the effective use of emerging dynamic circuit network services. They provide interfaces to applications, such as dCache SRM, translate network service requests into network device configurations, and coordinate with each other to setup up end-to-end network paths. The End Site Control Plane Subsystem (ESCPS) builds upon the success of the three projects by combining their individual capabilities into the next generation of network middleware. ESCPS addresses challenges such as cross-domain control plane signalling and interoperability, authentication and authorization in a Grid environment, topology discovery, and dynamic status tracking. The new network middleware will take full advantage of the perfSONAR monitoring infrastructure and the Inter-Domain Control plane efforts and will be deployed and fully vetted in the Large Hadron Collider data movement environment.
The Role of Incomplete Information and Others' Choice in Reducing Traffic: A Pilot Study
Romano, Angelo; Mosso, Cristina O.; Merlone, Ugo
2016-01-01
In this study, we investigate the role of payoff information and conformity in improving network performance in a traffic dilemma known as the Braess paradox. Our goal is to understand when decisions are guided by selfish motivations or otherwise by social ones. For this purpose, we consider the manipulation of others' choice, public and private monitoring and information on distribution of choices. Data show that when social comparison was not salient, participants were more cooperative. By contrast, cooperativeness of others' choice made participants more competitive leading to traffic and collective performance decrease. The implications of these findings to the literature on social dilemmas are discussed. PMID:26903931
Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K K; Luk, Connie W Y; Ning, Zhi
2016-02-05
This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.
Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K.K.; Luk, Connie W.Y.; Ning, Zhi
2016-01-01
This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring. PMID:26861336
Predicting Information Flows in Network Traffic.
ERIC Educational Resources Information Center
Hinich, Melvin J.; Molyneux, Robert E.
2003-01-01
Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)
Relationship between microscopic dynamics in traffic flow and complexity in networks.
Li, Xin-Gang; Gao, Zi-You; Li, Ke-Ping; Zhao, Xiao-Mei
2007-07-01
Complex networks are constructed in the evolution process of traffic flow, and the states of traffic flow are represented by nodes in the network. The traffic dynamics can then be studied by investigating the statistical properties of those networks. According to Kerner's three-phase theory, there are two different phases in congested traffic, synchronized flow and wide moving jam. In the framework of this theory, we study different properties of synchronized flow and moving jam in relation to complex network. Scale-free network is constructed in stop-and-go traffic, i.e., a sequence of moving jams [Chin. Phys. Lett. 10, 2711 (2005)]. In this work, the networks generated in synchronized flow are investigated in detail. Simulation results show that the degree distribution of the networks constructed in synchronized flow has two power law regions, so the distinction in topological structure can really reflect the different dynamics in traffic flow. Furthermore, the real traffic data are investigated by this method, and the results are consistent with the simulations.
SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks
NASA Astrophysics Data System (ADS)
Lin, Likun
Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network monitoring sensors. In order to maintain signal quality while optimizing network resources, we find that it is essential to model and update estimates of the physical link impairments in real-time. In this thesis, we consider the key elements required to enable an agile optical network, with contributions as follows: • Control Framework: extended the SDN concept to include the optical transport network through extensions to the OpenFlow (OF) protocol. A unified SDN control plane is built to facilitate control and management capability across the electrical/packet-switched and optical/circuit-switched portions of the network seamlessly. The SDN control plane serves as a platform to abstract the resources of multilayer/multivendor networks. Through this platform, applications can dynamically request the network resources to meet their service requirements. • Use of In-situ Monitors: enabled real-time physical impairment sensing in the control plane using in-situ Optical Performance Monitoring (OPM) and bit error rate (BER) analyzers. OPM and BER values are used as quantitative indicators of the link status and are fed to the control plane through a high-speed data collection interface to form a closed-loop feedback system to enable adaptive resource allocation. • Predictive Network Model: used a network model embedded in the control layer to study the link status. The estimated results of network status is fed into the control decisions to precompute the network resources. The performance of the network model can be enhanced by the sensing results. • Real-Time Control Algorithms: investigated various dynamic resource allocation mechanisms supporting an agile optical network. Intelligent routing and wavelength switching for recovering from traffic impairments is achieved experimentally in the agile optical network within one second. A distance-adaptive spectrum allocation scheme to address transmission impairments caused by cascaded Wavelength Selective Switches (WSS) is proposed and evaluated for improving network spectral efficiency.
Wireless Infrastructure M2M Network For Distributed Power Grid Monitoring
Gharavi, Hamid; Hu, Bin
2018-01-01
With the massive integration of distributed renewable energy sources (RESs) into the power system, the demand for timely and reliable network quality monitoring, control, and fault analysis is rapidly growing. Following the successful deployment of Phasor Measurement Units (PMUs) in transmission systems for power monitoring, a new opportunity to utilize PMU measurement data for power quality assessment in distribution grid systems is emerging. The main problem however, is that a distribution grid system does not normally have the support of an infrastructure network. Therefore, the main objective in this paper is to develop a Machine-to-Machine (M2M) communication network that can support wide ranging sensory data, including high rate synchrophasor data for real-time communication. In particular, we evaluate the suitability of the emerging IEEE 802.11ah standard by exploiting its important features, such as classifying the power grid sensory data into different categories according to their traffic characteristics. For performance evaluation we use our hardware in the loop grid communication network testbed to access the performance of the network. PMID:29503505
Wireless Infrastructure M2M Network For Distributed Power Grid Monitoring.
Gharavi, Hamid; Hu, Bin
2017-01-01
With the massive integration of distributed renewable energy sources (RESs) into the power system, the demand for timely and reliable network quality monitoring, control, and fault analysis is rapidly growing. Following the successful deployment of Phasor Measurement Units (PMUs) in transmission systems for power monitoring, a new opportunity to utilize PMU measurement data for power quality assessment in distribution grid systems is emerging. The main problem however, is that a distribution grid system does not normally have the support of an infrastructure network. Therefore, the main objective in this paper is to develop a Machine-to-Machine (M2M) communication network that can support wide ranging sensory data, including high rate synchrophasor data for real-time communication. In particular, we evaluate the suitability of the emerging IEEE 802.11ah standard by exploiting its important features, such as classifying the power grid sensory data into different categories according to their traffic characteristics. For performance evaluation we use our hardware in the loop grid communication network testbed to access the performance of the network.
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei
2017-01-01
Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction. PMID:28672867
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.
Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei
2017-06-26
Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.
Integrated risk/cost planning models for the US Air Traffic system
NASA Technical Reports Server (NTRS)
Mulvey, J. M.; Zenios, S. A.
1985-01-01
A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.
Classifier fusion for VoIP attacks classification
NASA Astrophysics Data System (ADS)
Safarik, Jakub; Rezac, Filip
2017-05-01
SIP is one of the most successful protocols in the field of IP telephony communication. It establishes and manages VoIP calls. As the number of SIP implementation rises, we can expect a higher number of attacks on the communication system in the near future. This work aims at malicious SIP traffic classification. A number of various machine learning algorithms have been developed for attack classification. The paper presents a comparison of current research and the use of classifier fusion method leading to a potential decrease in classification error rate. Use of classifier combination makes a more robust solution without difficulties that may affect single algorithms. Different voting schemes, combination rules, and classifiers are discussed to improve the overall performance. All classifiers have been trained on real malicious traffic. The concept of traffic monitoring depends on the network of honeypot nodes. These honeypots run in several networks spread in different locations. Separation of honeypots allows us to gain an independent and trustworthy attack information.
A framework for visualization of battlefield network behavior
NASA Astrophysics Data System (ADS)
Perzov, Yury; Yurcik, William
2006-05-01
An extensible network simulation application was developed to study wireless battlefield communications. The application monitors node mobility and depicts broadcast and unicast traffic as expanding rings and directed links. The network simulation was specially designed to support fault injection to show the impact of air strikes on disabling nodes. The application takes standard ns-2 trace files as an input and provides for performance data output in different graphical forms (histograms and x/y plots). Network visualization via animation of simulation output can be saved in AVI format that may serve as a basis for a real-time battlefield awareness system.
Spatial correlation analysis of urban traffic state under a perspective of community detection
NASA Astrophysics Data System (ADS)
Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan
2018-05-01
Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-04-10
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-01-01
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270
Evaluation of Deployment Challenges of Wireless Sensor Networks at Signalized Intersections
Azpilicueta, Leyre; López-Iturri, Peio; Aguirre, Erik; Martínez, Carlos; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco
2016-01-01
With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However, it is highly important to analyze radio propagation prior to the deployment of a wireless sensor network in such complex scenarios. In this work, the radio wave characterization for ISM 2.4 GHz and 5 GHz Wireless Sensor Networks (WSNs) deployed taking advantage of the existence of traffic light infrastructure has been assessed. By means of an in-house developed 3D ray launching algorithm, the impact of topology as well as urban morphology of the environment has been analyzed, emulating the realistic operation in the framework of the scenario. The complexity of the scenario, which is an intersection city area with traffic lights, vehicles, people, buildings, vegetation and urban environment, makes necessary the channel characterization with accurate models before the deployment of wireless networks. A measurement campaign has been conducted emulating the interaction of the system, in the vicinity of pedestrians as well as nearby vehicles. A real time interactive application has been developed and tested in order to visualize and monitor traffic as well as pedestrian user location and behavior. Results show that the use of deterministic tools in WSN deployment can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network. PMID:27455270
Evaluation of Deployment Challenges of Wireless Sensor Networks at Signalized Intersections.
Azpilicueta, Leyre; López-Iturri, Peio; Aguirre, Erik; Martínez, Carlos; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco
2016-07-22
With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However, it is highly important to analyze radio propagation prior to the deployment of a wireless sensor network in such complex scenarios. In this work, the radio wave characterization for ISM 2.4 GHz and 5 GHz Wireless Sensor Networks (WSNs) deployed taking advantage of the existence of traffic light infrastructure has been assessed. By means of an in-house developed 3D ray launching algorithm, the impact of topology as well as urban morphology of the environment has been analyzed, emulating the realistic operation in the framework of the scenario. The complexity of the scenario, which is an intersection city area with traffic lights, vehicles, people, buildings, vegetation and urban environment, makes necessary the channel characterization with accurate models before the deployment of wireless networks. A measurement campaign has been conducted emulating the interaction of the system, in the vicinity of pedestrians as well as nearby vehicles. A real time interactive application has been developed and tested in order to visualize and monitor traffic as well as pedestrian user location and behavior. Results show that the use of deterministic tools in WSN deployment can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network.
Doulamis, A D; Doulamis, N D; Kollias, S D
2003-01-01
Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.
Minimal-delay traffic grooming for WDM star networks
NASA Astrophysics Data System (ADS)
Choi, Hongsik; Garg, Nikhil; Choi, Hyeong-Ah
2003-10-01
All-optical networks face the challenge of reducing slower opto-electronic conversions by managing assignment of traffic streams to wavelengths in an intelligent manner, while at the same time utilizing bandwidth resources to the maximum. This challenge becomes harder in networks closer to the end users that have insufficient data to saturate single wavelengths as well as traffic streams outnumbering the usable wavelengths, resulting in traffic grooming which requires costly traffic analysis at access nodes. We study the problem of traffic grooming that reduces the need to analyze traffic, for a class of network architecture most used by Metropolitan Area Networks; the star network. The problem being NP-complete, we provide an efficient twice-optimal-bound greedy heuristic for the same, that can be used to intelligently groom traffic at the LANs to reduce latency at the access nodes. Simulation results show that our greedy heuristic achieves a near-optimal solution.
A scalable architecture for online anomaly detection of WLCG batch jobs
NASA Astrophysics Data System (ADS)
Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.
2016-10-01
For data centres it is increasingly important to monitor the network usage, and learn from network usage patterns. Especially configuration issues or misbehaving batch jobs preventing a smooth operation need to be detected as early as possible. At the GridKa data and computing centre we therefore operate a tool BPNetMon for monitoring traffic data and characteristics of WLCG batch jobs and pilots locally on different worker nodes. On the one hand local information itself are not sufficient to detect anomalies for several reasons, e.g. the underlying job distribution on a single worker node might change or there might be a local misconfiguration. On the other hand a centralised anomaly detection approach does not scale regarding network communication as well as computational costs. We therefore propose a scalable architecture based on concepts of a super-peer network.
NASA Astrophysics Data System (ADS)
Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei
2017-07-01
Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.
Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants
NASA Astrophysics Data System (ADS)
Milando, Chad W.; Batterman, Stuart A.
2018-06-01
Exposure to traffic-related air pollutants (TRAP) remains a key public health issue, and improved exposure measures are needed to support health impact and epidemiologic studies and inform regulatory responses. The recently developed Research LINE source model (RLINE), a Gaussian line source dispersion model, has been used in several epidemiologic studies of TRAP exposure, but evaluations of RLINE's performance in such applications have been limited. This study provides an operational evaluation of RLINE in which predictions of NOx, CO and PM2.5 are compared to observations at air quality monitoring stations located near high traffic roads in Detroit, MI. For CO and NOx, model performance was best at sites close to major roads, during downwind conditions, during weekdays, and during certain seasons. For PM2.5, the ability to discern local and particularly the traffic-related portion was limited, a result of high background levels, the sparseness of the monitoring network, and large uncertainties for certain processes (e.g., formation of secondary aerosols) and non-mobile sources (e.g., area, fugitive). Overall, RLINE's performance in near-road environments suggests its usefulness for estimating spatially- and temporally-resolved exposures. The study highlights considerations relevant to health impact and epidemiologic applications, including the importance of selecting appropriate pollutants, using appropriate monitoring approaches, considering prevailing wind directions during study design, and accounting for uncertainty.
NASA Astrophysics Data System (ADS)
Mavroidis, I.; Ilia, M.
2012-12-01
This work presents a systematic analysis and evaluation of the historic and current levels of atmospheric pollution in the Athens metropolitan region, regarding nitrogen oxides (NOx = NO + NO2), ozone (O3) and the NO2/NOx and NO/NO2 concentration ratios. Hourly, daily, monthly, seasonal and annual pollutant variations are examined and compared, using the results of concentration time series from three different stations of the national network for air pollution monitoring, one urban-traffic, one urban-background and one suburban-background. Concentration data are also related to meteorological parameters. The results show that the traffic affected station of Patission Street presents the higher NOx values and the lower concentrations of O3, while it is the station with the highest number of NO2 limit exceedances. The monitoring data suggest, inter alia, that there is a change in the behaviour of the suburban-background station of Liossia at about year 2000, indicating that the exact location of this station may need to be reconsidered. Comparison of NOx concentrations in Athens with concentrations in urban areas of other countries reveal that the Patission urban-traffic station records very high NOx concentrations, while remarkably high is the ratio of NO2 concentrations recorded at the urban-traffic vs. the urban-background station in Athens, indicating the overarching role of vehicles and traffic congestion on NO2 formation. The NO2/NOx ratio in the urban-traffic station appears to be almost constant with time, while it has been increasing in other urban areas, such as London and Seoul, suggesting an increased effect of primary NO2 in these areas. Diesel passenger cars were only recently allowed in Athens and, therefore, NO2 trends should be carefully monitored since a possible increase in primary NO2 may affect compliance with NO2 air quality standards.
An algorithm for monitoring the traffic on a less-travelled road using multi-modal sensor suite
NASA Astrophysics Data System (ADS)
Damarla, Thyagaraju; Chatters, Gary; Liss, Brian; Vu, Hao; Sabatier, James M.
2014-06-01
We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well- traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.
Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network
Chen, Hong; Li, Yang
2014-01-01
The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969
Fast packet switching algorithms for dynamic resource control over ATM networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tsang, R.P.; Keattihananant, P.; Chang, T.
1996-12-01
Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less
Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.
2017-01-01
Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398
Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E
2017-04-26
Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.
Detecting and Blocking Network Attacks at Ultra High Speeds
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paxson, Vern
2010-11-29
Stateful, in-depth, in-line traffic analysis for intrusion detection and prevention has grown increasingly more difficult as the data rates of modern networks rise. One point in the design space for high-performance network analysis - pursued by a number of commercial products - is the use of sophisticated custom hardware. For very high-speed processing, such systems often cast the entire analysis process in ASICs. This project pursued a different architectural approach, which we term Shunting. Shunting marries a conceptually quite simple hardware device with an Intrusion Prevention System (IPS) running on commodity PC hardware. The overall design goal is was tomore » keep the hardware both cheap and readily scalable to future higher speeds, yet also retain the unparalleled flexibility that running the main IPS analysis in a full general-computing environment provides. The Shunting architecture we developed uses a simple in-line hardware element that maintains several large state tables indexed by packet header fields, including IP/TCP flags, source and destination IP addresses, and connection tuples. The tables yield decision values the element makes on a packet-by-packet basis: forward the packet, drop it, or divert ('shunt') it through the IPS (the default). By manipulating table entries, the IPS can, on a fine-grained basis: (i) specify the traffic it wishes to examine, (ii) directly block malicious traffic, and (iii) 'cut through' traffic streams once it has had an opportunity to 'vet' them, or (iv) skip over large items within a stream before proceeding to further analyze it. For the Shunting architecture to yield benefits, it needs to operate in an environment for which the monitored network traffic has the property that - after proper vetting - much of it can be safely skipped. This property does not universally hold. For example, if a bank needs to examine all Web traffic involving its servers for regulatory compliance, then a monitor in front of one of the bank's server farms cannot safely omit a subset of the traffic from analysis. In this environment, Shunting cannot realize its main performance benefits, and the monitoring task likely calls for using custom hardware instead. However, in many other environments we find Shunting holds promise for delivering major performance gains. This arises due to the the widely documented 'heavy tail' nature of most forms of network traffic, which we might express as 'a few of the connections carry just about all the bytes.' The key additional insight is '... and very often for these few large connections, the very beginning of the connection contains nearly all the information of interest from a security analysis perspective.' We argue that this second claim holds because it is at the beginning of connections that authentication exchanges occur, data or file names and types are specified, request and reply status codes conveyed, and encryption is negotiated. Once these occur, we have seen most of the interesting facets of the dialog. Certainly the remainder of the connection might also yield some grist for analysis, but this is generally less likely, and thus if we want to lower analysis load at as small a loss as possible of information relevant to security analysis, we might best do so by skipping the bulk of large connections. In a different context, the 'Time Machine' work by Kornexl and colleagues likewise shows that in some environments we can realize major reductions in the volume of network traffic processed, by limiting the processing to the first 10-20 KB of each connection. As a concrete example, consider an IPS that monitors SSH traffic. When a new SSH connection arrives and the Shunt fails to find an entry for it in any of its tables (per-address, per-port, per-connection), it executes the default action of diverting the connection through the IPS. The IPS analyzes the beginning of the connection in this fashion. As long as it is satisified with the dialog, it reinjects the packets forwarded to it so that the connection can continue. If the connection successfully negotiates encryption, the IPS can no longer profitably analyze it, so it downloads a per-connection table entry to the Shunt specifying that the action for the connection in the future is 'forward.' For heavy-tailed connections, this means a very large majority of the connection's packets will now pass through the Shunt device without burdening the IPS with any further analysis load. On the other hand, if the IPS is dissatisfied with some element of the initial dialog, it downloads a 'drop' entry to terminate the connection. Note that by providing for reinjection, we can promote an intrusion detection system into an intrusion prevention system, one that does not merely detect attacks but can block them before they complete. Reinjection also allows the IPS to normalize traffic to remove ambiguities that attackers can leverage to evade the IPS.« less
Traffic Management for Satellite-ATM Networks
NASA Technical Reports Server (NTRS)
Goyal, Rohit; Jain, Raj; Fahmy, Sonia; Vandalore, Bobby; Goyal, Mukul
1998-01-01
Various issues associated with "Traffic Management for Satellite-ATM Networks" are presented in viewgraph form. Specific topics include: 1) Traffic management issues for TCP/IP based data services over satellite-ATM networks; 2) Design issues for TCP/IP over ATM; 3) Optimization of the performance of TCP/IP over ATM for long delay networks; and 4) Evaluation of ATM service categories for TCP/IP traffic.
Efficient large-scale graph data optimization for intelligent video surveillance
NASA Astrophysics Data System (ADS)
Shang, Quanhong; Zhang, Shujun; Wang, Yanbo; Sun, Chen; Wang, Zepeng; Zhang, Luming
2017-08-01
Society is rapidly accepting the use of a wide variety of cameras Location and applications: site traffic monitoring, parking Lot surveillance, car and smart space. These ones here the camera provides data every day in an analysis Effective way. Recent advances in sensor technology Manufacturing, communications and computing are stimulating.The development of new applications that can change the traditional Vision system incorporating universal smart camera network. This Analysis of visual cues in multi camera networks makes wide Applications ranging from smart home and office automation to large area surveillance and traffic surveillance. In addition, dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One Sparse camera network using large area surveillance. As few cameras as possible, most cameras do not overlap Each other’s field of vision. This task is challenging Lack of knowledge of topology Network, the specific changes in appearance and movement Track different opinions of the target, as well as difficulties Understanding complex events in a network. In this review in this paper, we present a comprehensive survey of recent studies Results to solve the problem of topology learning, Object appearance modeling and global activity understanding sparse camera network. In addition, some of the current open Research issues are discussed.
Nonuniform traffic spots (NUTS) in multistage interconnection networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lang, T.; Kurisaki, L.
1990-09-01
The performance of multistage interconnection networks for multiprocessors is degraded when the traffic pattern produces nonuniform congestion in the blocking switches, that is, when there exist nonuniform traffic spots. For some specific patterns the authors evaluate this degradation in performance and propose modifications to the network organization and operation to reduce the degradation. Successful modifications are the use of diverting switches and the extension of the network with additional links. The use of these modifications makes the network more effective for a larger variety of traffic patterns. The authors also consider the case in which the network carries the superpositionmore » of two types of traffic. One type is the high throughput data and instruction traffic, while the other consists of control and I/O packets which are of low throughput but have severe real-time constraints. The authors conclude that diverting switches and networks with additional links are also suitable for assuring low latency for the real-time traffic, especially when using the displacing mode.« less
NASA Astrophysics Data System (ADS)
Ballora, Mark; Hall, David L.
2010-04-01
Detection of intrusions is a continuing problem in network security. Due to the large volumes of data recorded in Web server logs, analysis is typically forensic, taking place only after a problem has occurred. This paper describes a novel method of representing Web log information through multi-channel sound, while simultaneously visualizing network activity using a 3-D immersive environment. We are exploring the detection of intrusion signatures and patterns, utilizing human aural and visual pattern recognition ability to detect intrusions as they occur. IP addresses and return codes are mapped to an informative and unobtrusive listening environment to act as a situational sound track of Web traffic. Web log data is parsed and formatted using Python, then read as a data array by the synthesis language SuperCollider [1], which renders it as a sonification. This can be done either for the study of pre-existing data sets or in monitoring Web traffic in real time. Components rendered aurally include IP address, geographical information, and server Return Codes. Users can interact with the data, speeding or slowing the speed of representation (for pre-existing data sets) or "mixing" sound components to optimize intelligibility for tracking suspicious activity.
On-track testing of a power harvesting device for railroad track health monitoring
NASA Astrophysics Data System (ADS)
Hansen, Sean E.; Pourghodrat, Abolfazl; Nelson, Carl A.; Fateh, Mahmood
2010-03-01
A considerable proportion of railroad infrastructure exists in regions which are comparatively remote. With regard to the cost of extending electrical infrastructure into these areas, road crossings in these areas do not have warning light systems or crossing gates and are commonly marked with reflective signage. For railroad track health monitoring purposes, distributed sensor networks can be applicable in remote areas, but the same limitation regarding electrical infrastructure is the hindrance. This motivated the development of an energy harvesting solution for remote railroad deployment. This paper describes on-track experimental testing of a mechanical device for harvesting mechanical power from passing railcar traffic, in view of supplying electrical power to warning light systems at crossings and to remote networks of sensors. The device is mounted to and spans two rail ties and transforms the vertical rail displacement into electrical energy through mechanical amplification and rectification into a PMDC generator. A prototype was tested under loaded and unloaded railcar traffic at low speeds. Stress analysis and speed scaling analysis are presented, results of the on-track tests are compared and contrasted to previous laboratory testing, discrepancies between the two are explained, and conclusions are drawn regarding suitability of the device for illuminating high-efficiency LED lights at railroad crossings and powering track-health sensor networks.
A Protocol Specification-Based Intrusion Detection System for VoIP and Its Evaluation
NASA Astrophysics Data System (ADS)
Phit, Thyda; Abe, Kôki
We propose an architecture of Intrusion Detection System (IDS) for VoIP using a protocol specification-based detection method to monitor the network traffics and alert administrator for further analysis of and response to suspicious activities. The protocol behaviors and their interactions are described by state machines. Traffic that behaves differently from the standard specifications are considered to be suspicious. The IDS has been implemented and simulated using OPNET Modeler, and verified to detect attacks. It was found that our system can detect typical attacks within a reasonable amount of delay time.
NASA Astrophysics Data System (ADS)
Raysoni, Amit U.; Stock, Thomas H.; Sarnat, Jeremy A.; Montoya Sosa, Teresa; Ebelt Sarnat, Stefanie; Holguin, Fernando; Greenwald, Roby; Johnson, Brent; Li, Wen-Whai
2013-12-01
Children spend substantial amount of time within school microenvironments; therefore, assessing school-based exposures is essential for characterizing and preventing children's health risks to air pollutants. Indeed, the importance of characterizing children's exposures in schools is recognized by the US Environmental Protection Agency's recent initiative to promote outdoor air monitoring networks near schools. As part of a health effects study investigating the impact of traffic-related air pollution on asthmatic children along the US-Mexico border, this research examines children's exposures to, and spatio-temporal heterogeneity in concentrations of, traffic-related air pollutants at four elementary schools in El Paso, Texas. Three schools were located in an area of high traffic density and one school in an area of low traffic density. Paired indoor and outdoor concentrations of 48-h fine and coarse particulate matter (PM2.5 and PM10-2.5), 48-h black carbon (BC), 96-h nitrogen dioxide (NO2), and 96-h volatile organic compounds (VOCs) were measured for 13 weeks at each school. Outdoor concentrations of PM, NO2, BC, and BTEX (benzene, toluene, ethylbenzene, m,p-xylene, o-xylene) compounds were similar among the three schools in the high-traffic zone in contrast to the school in the low-traffic zone. Results from this study and previous studies in this region corroborate the fact that PM pollution in El Paso is dominated by coarse PM (PM10-2.5) and fine fraction (PM2.5) accounts for only 25-30% of the total PM mass in PM10. BTEX species and BC are better surrogates for traffic air pollution in this region. Correlation analyses indicate a range of association between indoor and outdoor pollutant concentrations due to uncontrollable factors like student foot traffic and varying building and ventilation configurations across the four schools. Results suggest the need of micro-scale monitoring for children's exposure assessment, which may not be adequately characterized by the measurements from a centralized monitoring site.
DOT National Transportation Integrated Search
1995-02-01
This guide is designed to provide direction on the monitoring of traffic characteristics. It begins with a discussion of the structure of traffic characteristics monitoring and traffic counting. The next two sections cover vehicle classification and ...
Remote detection of riverine traffic using an ad hoc wireless sensor network
NASA Astrophysics Data System (ADS)
Athan, Stephan P.
2005-05-01
Trafficking of illegal drugs on riverine and inland waterways continues to proliferate in South America. While there has been a successful joint effort to cut off overland and air trafficking routes, there exists a vast river network and Amazon region consisting of over 13,000 water miles that remains difficult to adequately monitor, increasing the likelihood of narcotics moving along this extensive river system. Hence, an effort is underway to provide remote unattended riverine detection in lieu of manned or attended detection measures.
Proton beam therapy control system
Baumann, Michael A [Riverside, CA; Beloussov, Alexandre V [Bernardino, CA; Bakir, Julide [Alta Loma, CA; Armon, Deganit [Redlands, CA; Olsen, Howard B [Colton, CA; Salem, Dana [Riverside, CA
2008-07-08
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
Proton beam therapy control system
Baumann, Michael A.; Beloussov, Alexandre V.; Bakir, Julide; Armon, Deganit; Olsen, Howard B.; Salem, Dana
2010-09-21
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
Proton beam therapy control system
Baumann, Michael A; Beloussov, Alexandre V; Bakir, Julide; Armon, Deganit; Olsen, Howard B; Salem, Dana
2013-06-25
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
Proton beam therapy control system
Baumann, Michael A; Beloussov, Alexandre V; Bakir, Julide; Armon, Deganit; Olsen, Howard B; Salem, Dana
2013-12-03
A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.
A low power medium access control protocol for wireless medical sensor networks.
Lamprinos, I; Prentza, A; Sakka, E; Koutsouris, D
2004-01-01
The concept of a wireless integrated network of sensors, already applied in several sectors of our everyday life, such as security, transportation and environment monitoring, can as well provide an advanced monitor and control resource for healthcare services. By networking medical sensors wirelessly, attaching them in patient's body, we create the appropriate infrastructure for continuous and real-time monitoring of patient without discomforting him. This infrastructure can improve healthcare by providing the means for flexible acquisition of vital signs, while at the same time it provides more convenience to the patient. Given the type of wireless network, traditional medium access control (MAC) protocols cannot take advantage of the application specific requirements and information characteristics occurring in medical sensor networks, such as the demand for low power consumption and the rather limited and asymmetric data traffic. In this paper, we present the architecture of a low power MAC protocol, designated to support wireless networks of medical sensors. This protocol aims to improve energy efficiency by exploiting the inherent application features and requirements. It is oriented towards the avoidance of main energy wastage sources, such as idle listening, collision and power outspending.
Low Duty-Cycling MAC Protocol for Low Data-Rate Medical Wireless Body Area Networks
Zhang, Chongqing; Wang, Yinglong; Liang, Yongquan; Shu, Minglei; Zhang, Jinquan; Ni, Lina
2017-01-01
Wireless body area networks (WBANs) are severely energy constrained, and how to improve the energy efficiency so as to prolong the network lifetime as long as possible is one of the most important goals of WBAN research. Low data-rate WBANs are promising to cut down the energy consumption and extend the network lifetime. Considering the characteristics and demands of low data-rate WBANs, a low duty-cycling medium access control (MAC) protocol is specially designed for this kind of WBAN in this paper. Longer superframes are exploited to cut down the energy consumed on the transmissions and receptions of redundant beacon frames. Insertion time slots are embedded into the inactive part of a superframe to deliver the frames and satisfy the quality of service (QoS) requirements. The number of the data subsections in an insertion time slot can be adaptively adjusted so as to accommodate low data-rate WBANs with different traffic. Simulation results show that the proposed MAC protocol performs well under the condition of low data-rate monitoring traffic. PMID:28509849
An efficient routing strategy for traffic dynamics on two-layer complex networks
NASA Astrophysics Data System (ADS)
Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu
2018-05-01
In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.
Human recognition in a video network
NASA Astrophysics Data System (ADS)
Bhanu, Bir
2009-10-01
Video networks is an emerging interdisciplinary field with significant and exciting scientific and technological challenges. It has great promise in solving many real-world problems and enabling a broad range of applications, including smart homes, video surveillance, environment and traffic monitoring, elderly care, intelligent environments, and entertainment in public and private spaces. This paper provides an overview of the design of a wireless video network as an experimental environment, camera selection, hand-off and control, anomaly detection. It addresses challenging questions for individual identification using gait and face at a distance and present new techniques and their comparison for robust identification.
Fixed Point Learning Based Intelligent Traffic Control System
NASA Astrophysics Data System (ADS)
Zongyao, Wang; Cong, Sui; Cheng, Shao
2017-10-01
Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.
Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms
2014-03-27
BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS THESIS Jessica R. Werling, Captain, USAF AFIT-ENG-14-M-81 DEPARTMENT...subject to copyright protection in the United States. AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ...AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS Jessica R. Werling, B.S.C.S. Captain, USAF Approved
Dynamic baseline detection method for power data network service
NASA Astrophysics Data System (ADS)
Chen, Wei
2017-08-01
This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.
Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao
2018-01-01
The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551
Cyclist route choice, traffic-related air pollution, and lung function: a scripted exposure study
2013-01-01
Background A travel mode shift to active transportation such as bicycling would help reduce traffic volume and related air pollution emissions as well as promote increased physical activity level. Cyclists, however, are at risk for exposure to vehicle-related air pollutants due to their proximity to vehicle traffic and elevated respiratory rates. To promote safe bicycle commuting, the City of Berkeley, California, has designated a network of residential streets as “Bicycle Boulevards.” We hypothesized that cyclist exposure to air pollution would be lower on these Bicycle Boulevards when compared to busier roads and this elevated exposure may result in reduced lung function. Methods We recruited 15 healthy adults to cycle on two routes – a low-traffic Bicycle Boulevard route and a high-traffic route. Each participant cycled on the low-traffic route once and the high-traffic route once. We mounted pollutant monitors and a global positioning system (GPS) on the bicycles. The monitors were all synced to GPS time so pollutant measurements could be spatially plotted. We measured lung function using spirometry before and after each bike ride. Results We found that fine and ultrafine particulate matter, carbon monoxide, and black carbon were all elevated on the high-traffic route compared to the low-traffic route. There were no corresponding changes in the lung function of healthy non-asthmatic study subjects. We also found that wind-speed affected pollution concentrations. Conclusions These results suggest that by selecting low-traffic Bicycle Boulevards instead of heavily trafficked roads, cyclists can reduce their exposure to vehicle-related air pollution. The lung function results indicate that elevated pollutant exposure may not have acute negative effects on healthy cyclists, but further research is necessary to determine long-term effects on a more diverse population. This study and broader field of research have the potential to encourage policy-makers and city planners to expand infrastructure to promote safe and healthy bicycle commuting. PMID:23391029
Cyclist route choice, traffic-related air pollution, and lung function: a scripted exposure study.
Jarjour, Sarah; Jerrett, Michael; Westerdahl, Dane; de Nazelle, Audrey; Hanning, Cooper; Daly, Laura; Lipsitt, Jonah; Balmes, John
2013-02-07
A travel mode shift to active transportation such as bicycling would help reduce traffic volume and related air pollution emissions as well as promote increased physical activity level. Cyclists, however, are at risk for exposure to vehicle-related air pollutants due to their proximity to vehicle traffic and elevated respiratory rates. To promote safe bicycle commuting, the City of Berkeley, California, has designated a network of residential streets as "Bicycle Boulevards." We hypothesized that cyclist exposure to air pollution would be lower on these Bicycle Boulevards when compared to busier roads and this elevated exposure may result in reduced lung function. We recruited 15 healthy adults to cycle on two routes - a low-traffic Bicycle Boulevard route and a high-traffic route. Each participant cycled on the low-traffic route once and the high-traffic route once. We mounted pollutant monitors and a global positioning system (GPS) on the bicycles. The monitors were all synced to GPS time so pollutant measurements could be spatially plotted. We measured lung function using spirometry before and after each bike ride. We found that fine and ultrafine particulate matter, carbon monoxide, and black carbon were all elevated on the high-traffic route compared to the low-traffic route. There were no corresponding changes in the lung function of healthy non-asthmatic study subjects. We also found that wind-speed affected pollution concentrations. These results suggest that by selecting low-traffic Bicycle Boulevards instead of heavily trafficked roads, cyclists can reduce their exposure to vehicle-related air pollution. The lung function results indicate that elevated pollutant exposure may not have acute negative effects on healthy cyclists, but further research is necessary to determine long-term effects on a more diverse population. This study and broader field of research have the potential to encourage policy-makers and city planners to expand infrastructure to promote safe and healthy bicycle commuting.
NASA Astrophysics Data System (ADS)
Gendreau, Audrey
Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing application had established the network traffic flow to the sink. The same scenario was repeated using a power-based IDS to compare it against the proposed model. To identify a clusterhead's ability to host monitoring agents after the temperature sensing application terminated, the deployed IDS utilized the communication history and other network factors in order to rank the nodes. Similarly, using the node's communication history, the deployed power-based IDS ranked nodes based on their remaining power. For each individual scenario, and after the IDS application was deployed, the temperature sensing application was run for a second time. This time, to monitor the temperature sensing agents as the data flowed towards the sink, the network traffic was rerouted through the new intrusion detection clusterheads. Consequently, if the clusterheads were shared, the re-routing step was not preformed. Experimental results in this research demonstrated the effectiveness of applying a robust deployment metric to improve upon the energy efficiency of a deployed application in a multi-application WSN. It was found that in the scenarios with the intrusion detection application that utilized the proposed model resulted in more remaining energy than in the scenarios that implemented the power-based IDS. The algorithm especially had a positive impact on the small, dense, and more homogeneous networks. This finding was reinforced by the smaller percentage of new clusterheads that was selected. Essentially, the energy cost of the route to the sink was reduced because the network traffic was rerouted through fewer new clusterheads. Additionally, it was found that the intrusion detection topology that used the proposed approach formed smaller and more connected sets of clusterheads than the power-based IDS. As a consequence, this proposed approach essentially achieved the research objective for enhancing energy use in a multi-application WSN.
NASA Astrophysics Data System (ADS)
Takuma, Takehisa; Masugi, Masao
2009-03-01
This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.
Network Traffic Generator for Low-rate Small Network Equipment Software
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lanzisera, Steven
2013-05-28
Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.
Monitoring and Indentification Packet in Wireless With Deep Packet Inspection Method
NASA Astrophysics Data System (ADS)
Fali Oklilas, Ahmad; Tasmi
2017-04-01
Layer 2 and Layer 3 are used to make a process of network monitoring, but with the development of applications on the network such as the p2p file sharing, VoIP, encrypted, and many applications that already use the same port, it would require a system that can classify network traffics, not only based on port number classification. This paper reports the implementation of the deep packet inspection method to analyse data packets based on the packet header and payload to be used in packet data classification. If each application can be grouped based on the application layer, then we can determine the pattern of internet users and also to perform network management of computer science department. In this study, a prototype wireless network and applications SSO were developed to detect the active user. The focus is on the ability of open DPI and nDPI in detecting the payload of an application and the results are elaborated in this paper.
Active Traffic Capture for Network Forensics
NASA Astrophysics Data System (ADS)
Slaviero, Marco; Granova, Anna; Olivier, Martin
Network traffic capture is an integral part of network forensics, but current traffic capture techniques are typically passive in nature. Under heavy loads, it is possible for a sniffer to miss packets, which affects the quality of forensic evidence.
Nap, Marius
2016-01-01
Digital pathology is indisputably connected with high demands on data traffic and storage. As a consequence, control of the logistic process and insight into the management of both traffic and storage is essential. We monitored data traffic from scanners to server and server to workstation and registered storage needs for diagnostic images and additional projects. The results showed that data traffic inside the hospital network (1 Gbps) never exceeded 80 Mbps for scanner-to-server activity, and activity from the server to the workstation took at most 5 Mbps. Data storage per image increased from 300 MB to an average of 600 MB as a result of camera and software updates, and, due to the increased scanning speed, the scanning time was reduced with almost 8 h/day. Introduction of a storage policy of only 12 months for diagnostic images and rescanning if needed resulted in a manageable storage window of 45 TB for the period of 1 year. Using simple registration tools allowed the transition of digital pathology into a concise package that allows planning and control. Incorporating retrieval of such information from scanning and storage devices will reduce the fear of losing control by the management when introducing digital pathology in daily routine. © 2016 S. Karger AG, Basel.
Real time network traffic monitoring for wireless local area networks based on compressed sensing
NASA Astrophysics Data System (ADS)
Balouchestani, Mohammadreza
2017-05-01
A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.
Using OpenSSH to secure mobile LAN network traffic
NASA Astrophysics Data System (ADS)
Luu, Brian B.; Gopaul, Richard D.
2002-08-01
Mobile Internet Protocol (IP) Local Area Network (LAN) is a technique, developed by the U.S. Army Research Laboratory, which allows a LAN to be IP mobile when attaching to a foreign IP-based network and using this network as a means to retain connectivity to its home network. In this paper, we describe a technique that uses Open Secure Shell (OpenSSH) software to ensure secure, encrypted transmission of a mobile LAN's network traffic. Whenever a mobile LAN, implemented with Mobile IP LAN, moves to a foreign network, its gateway (router) obtains an IP address from the new network. IP tunnels, using IP encapsulation, are then established from the gateway through the foreign network to a home agent on its home network. These tunnels provide a virtual two-way connection to the home network for the mobile LAN as if the LAN were connected directly to its home network. Hence, when IP mobile, a mobile LAN's tunneled network traffic must traverse one or more foreign networks that may not be trusted. This traffic could be subject to eavesdropping, interception, modification, or redirection by malicious nodes in these foreign networks. To protect network traffic passing through the tunnels, OpenSSH is used as a means of encryption because it prevents surveillance, modification, and redirection of mobile LAN traffic passing across foreign networks. Since the software is found in the public domain, is available for most current operating systems, and is commonly used to provide secure network communications, OpenSSH is the software of choice.
Neural networks for continuous online learning and control.
Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long
2006-11-01
This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.
NASA Astrophysics Data System (ADS)
Huang, Darong; Bai, Xing-Rong
Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.
Real-Time SCADA Cyber Protection Using Compression Techniques
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lyle G. Roybal; Gordon H Rueff
2013-11-01
The Department of Energy’s Office of Electricity Delivery and Energy Reliability (DOE-OE) has a critical mission to secure the energy infrastructure from cyber attack. Through DOE-OE’s Cybersecurity for Energy Delivery Systems (CEDS) program, the Idaho National Laboratory (INL) has developed a method to detect malicious traffic on Supervisory, Control, and Data Acquisition (SCADA) network using a data compression technique. SCADA network traffic is often repetitive with only minor differences between packets. Research performed at the INL showed that SCADA network traffic has traits desirable for using compression analysis to identify abnormal network traffic. An open source implementation of a Lempel-Ziv-Welchmore » (LZW) lossless data compression algorithm was used to compress and analyze surrogate SCADA traffic. Infected SCADA traffic was found to have statistically significant differences in compression when compared against normal SCADA traffic at the packet level. The initial analyses and results are clearly able to identify malicious network traffic from normal traffic at the packet level with a very high confidence level across multiple ports and traffic streams. Statistical differentiation between infected and normal traffic level was possible using a modified data compression technique at the 99% probability level for all data analyzed. However, the conditions tested were rather limited in scope and need to be expanded into more realistic simulations of hacking events using techniques and approaches that are better representative of a real-world attack on a SCADA system. Nonetheless, the use of compression techniques to identify malicious traffic on SCADA networks in real time appears to have significant merit for infrastructure protection.« less
A Measurement Plane for Optical Networks to Manage Emergency Events
NASA Astrophysics Data System (ADS)
Tego, E.; Carciofi, C.; Grazioso, P.; Petrini, V.; Pompei, S.; Matera, F.; Attanasio, V.; Nastri, E.; Restuccia, E.
2017-11-01
In this work, we show a wide geographical area optical network test bed, adopting the mPlane measurement plane for monitoring its performance and to manage software defined network approaches, with some specific tests and procedures dedicated to respond to disaster events and to support emergency networks. Such a test bed includes FTTX accesses, and it is currently implemented to support future 5G wireless services with slicing procedures based on Carrier Ethernet. The characteristics of this platform have been experimentally tested in the case of a damage-causing link failure and traffic congestion, showing a fast reactions to these disastrous events, allowing the user to recharge the initial QoS parameters.
Long-range wireless mesh network for weather monitoring in unfriendly geographic conditions.
Toledano-Ayala, Manuel; Herrera-Ruiz, Gilberto; Soto-Zarazúa, Genaro M; Rivas-Araiza, Edgar A; Bazán Trujillo, Rey D; Porrás-Trejo, Rafael E
2011-01-01
In this paper a long-range wireless mesh network system is presented. It consists of three main parts: Remote Terminal Units (RTUs), Base Terminal Units (BTUs) and a Central Server (CS). The RTUs share a wireless network transmitting in the industrial, scientific and medical applications ISM band, which reaches up to 64 Km in a single point-to-point communication. A BTU controls the traffic within the network and has as its main task interconnecting it to a Ku-band satellite link using an embedded microcontroller-based gateway. Collected data is stored in a CS and presented to the final user in a numerical and a graphical form in a web portal.
Network traffic anomaly prediction using Artificial Neural Network
NASA Astrophysics Data System (ADS)
Ciptaningtyas, Hening Titi; Fatichah, Chastine; Sabila, Altea
2017-03-01
As the excessive increase of internet usage, the malicious software (malware) has also increase significantly. Malware is software developed by hacker for illegal purpose(s), such as stealing data and identity, causing computer damage, or denying service to other user[1]. Malware which attack computer or server often triggers network traffic anomaly phenomena. Based on Sophos's report[2], Indonesia is the riskiest country of malware attack and it also has high network traffic anomaly. This research uses Artificial Neural Network (ANN) to predict network traffic anomaly based on malware attack in Indonesia which is recorded by Id-SIRTII/CC (Indonesia Security Incident Response Team on Internet Infrastructure/Coordination Center). The case study is the highest malware attack (SQL injection) which has happened in three consecutive years: 2012, 2013, and 2014[4]. The data series is preprocessed first, then the network traffic anomaly is predicted using Artificial Neural Network and using two weight update algorithms: Gradient Descent and Momentum. Error of prediction is calculated using Mean Squared Error (MSE) [7]. The experimental result shows that MSE for SQL Injection is 0.03856. So, this approach can be used to predict network traffic anomaly.
A new traffic control design method for large networks with signalized intersections
NASA Technical Reports Server (NTRS)
Leininger, G. G.; Colony, D. C.; Seldner, K.
1979-01-01
The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.
Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.
Al-Jarrah, Omar Y; Alhussein, Omar; Yoo, Paul D; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo
2016-08-01
Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet's payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network's traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.
Predicting commuter flows in spatial networks using a radiation model based on temporal ranges
NASA Astrophysics Data System (ADS)
Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán
2014-11-01
Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.
DOT National Transportation Integrated Search
1992-01-01
The Traffic Monitoring Guide (TMG) provides a method for the development of a statistically based procedure to monitor traffic characteristics such as traffic loadings. Truck weight data in particular are a major element of the pavement management pr...
Understanding the T2 traffic in CMS during Run-1
NASA Astrophysics Data System (ADS)
T, Wildish
2015-12-01
In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes. Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community. Tier-2 to Tier-2 traffic may also traverse parts of the WAN that are at the 'edge' of our network, with limited network capacity or reliability compared to, say, the Tier-0 to Tier-1 traffic which goes the over LHCOPN network. CMS is looking to exploit technologies that allow us to interact with the network fabric so that it can manage our traffic better for us, this we hope to achieve before the end of Run-2. Tier-2 to Tier-2 traffic would be the most interesting use-case for such traffic management, precisely because it is close to the users' analysis and far from the 'core' network infrastructure. As such, a better understanding of our Tier-2 to Tier-2 traffic is important. Knowing the characteristics of our data-flows can help us place our data more intelligently. Knowing how widely the data moves can help us anticipate the requirements for network capacity, and inform the dynamic data placement algorithms we expect to have in place for Run-2. This paper presents an analysis of the CMS Tier-2 traffic during Run 1.
Discovering urban mobility patterns with PageRank based traffic modeling and prediction
NASA Astrophysics Data System (ADS)
Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun
2017-11-01
Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.
NASA Astrophysics Data System (ADS)
Tadić, Bosiljka; Thurner, Stefan; Rodgers, G. J.
2004-03-01
We study the microscopic time fluctuations of traffic load and the global statistical properties of a dense traffic of particles on scale-free cyclic graphs. For a wide range of driving rates R the traffic is stationary and the load time series exhibits antipersistence due to the regulatory role of the superstructure associated with two hub nodes in the network. We discuss how the superstructure affects the functioning of the network at high traffic density and at the jamming threshold. The degree of correlations systematically decreases with increasing traffic density and eventually disappears when approaching a jamming density Rc. Already before jamming we observe qualitative changes in the global network-load distributions and the particle queuing times. These changes are related to the occurrence of temporary crises in which the network-load increases dramatically, and then slowly falls back to a value characterizing free flow.
Vibration harvesting in traffic tunnels to power wireless sensor nodes
NASA Astrophysics Data System (ADS)
Wischke, M.; Masur, M.; Kröner, M.; Woias, P.
2011-08-01
Monitoring the traffic and the structural health of traffic tunnels requires numerous sensors. Powering these remote and partially embedded sensors from ambient energies will reduce maintenance costs, and improve the sensor network performance. This work reports on vibration levels detected in railway and road tunnels as a potential energy source for embedded sensors. The measurement results showed that the vibrations at any location in the road tunnel and at the wall in the railway tunnel are too small for useful vibration harvesting. In contrast, the railway sleeper features usable vibrations and sufficient mounting space. For this application site, a robust piezoelectric vibration harvester was designed and equipped with a power interface circuit. Within the field test, it is demonstrated that sufficient energy is harvested to supply a microcontroller with a radio frequency (RF) interface.
A novel interacting multiple model based network intrusion detection scheme
NASA Astrophysics Data System (ADS)
Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry
2006-04-01
In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.
Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan
2018-02-02
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management
2018-01-01
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884
NASA Astrophysics Data System (ADS)
Yun, Changho; Kim, Kiseon
2006-04-01
For the passive star-coupled wavelength-division multiple-access (WDMA) network, a modified accelerative preallocation WDMA (MAP-WDMA) media access control (MAC) protocol is proposed, which is based on AP-WDMA. To show the advantages of MAP-WDMA as an adequate MAC protocol for the network over AP-WDMA, the channel utilization, the channel-access delay, and the latency of MAP-WDMA are investigated and compared with those of AP-WDMA under various data traffic patterns, including uniform, quasi-uniform type, disconnected type, mesh type, and ring type data traffics, as well as the assumption that a given number of network stations is equal to that of channels, in other words, without channel sharing. As a result, the channel utilization of MAP-WDMA can be competitive with respect to that of AP-WDMA at the expense of insignificantly higher latency. Namely, if the number of network stations is small, MAP-WDMA provides better channel utilization for uniform, quasi-uniform-type, and disconnected-type data traffics at all data traffic loads, as well as for mesh and ring-type data traffics at low data traffic loads. Otherwise, MAP-WDMA only outperforms AP-WDMA for the first three data traffics at higher data traffic loads. In the aspect of channel-access delay, MAP-WDMA gives better performance than AP-WDMA, regardless of data traffic patterns and the number of network stations.
LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.
Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less
Analysis of adaptive algorithms for an integrated communication network
NASA Technical Reports Server (NTRS)
Reed, Daniel A.; Barr, Matthew; Chong-Kwon, Kim
1985-01-01
Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.
Modeling the coevolution of topology and traffic on weighted technological networks
NASA Astrophysics Data System (ADS)
Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong
2007-02-01
For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.
Weighted complex network analysis of the Beijing subway system: Train and passenger flows
NASA Astrophysics Data System (ADS)
Feng, Jia; Li, Xiamiao; Mao, Baohua; Xu, Qi; Bai, Yun
2017-05-01
In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.
NASA Astrophysics Data System (ADS)
Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei
2018-07-01
A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.
NASA Astrophysics Data System (ADS)
Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin
As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.
Active Job Monitoring in Pilots
NASA Astrophysics Data System (ADS)
Kuehn, Eileen; Fischer, Max; Giffels, Manuel; Jung, Christopher; Petzold, Andreas
2015-12-01
Recent developments in high energy physics (HEP) including multi-core jobs and multi-core pilots require data centres to gain a deep understanding of the system to monitor, design, and upgrade computing clusters. Networking is a critical component. Especially the increased usage of data federations, for example in diskless computing centres or as a fallback solution, relies on WAN connectivity and availability. The specific demands of different experiments and communities, but also the need for identification of misbehaving batch jobs, requires an active monitoring. Existing monitoring tools are not capable of measuring fine-grained information at batch job level. This complicates network-aware scheduling and optimisations. In addition, pilots add another layer of abstraction. They behave like batch systems themselves by managing and executing payloads of jobs internally. The number of real jobs being executed is unknown, as the original batch system has no access to internal information about the scheduling process inside the pilots. Therefore, the comparability of jobs and pilots for predicting run-time behaviour or network performance cannot be ensured. Hence, identifying the actual payload is important. At the GridKa Tier 1 centre a specific tool is in use that allows the monitoring of network traffic information at batch job level. This contribution presents the current monitoring approach and discusses recent efforts and importance to identify pilots and their substructures inside the batch system. It will also show how to determine monitoring data of specific jobs from identified pilots. Finally, the approach is evaluated.
Behavioral analysis of malicious code through network traffic and system call monitoring
NASA Astrophysics Data System (ADS)
Grégio, André R. A.; Fernandes Filho, Dario S.; Afonso, Vitor M.; Santos, Rafael D. C.; Jino, Mario; de Geus, Paulo L.
2011-06-01
Malicious code (malware) that spreads through the Internet-such as viruses, worms and trojans-is a major threat to information security nowadays and a profitable business for criminals. There are several approaches to analyze malware by monitoring its actions while it is running in a controlled environment, which helps to identify malicious behaviors. In this article we propose a tool to analyze malware behavior in a non-intrusive and effective way, extending the analysis possibilities to cover malware samples that bypass current approaches and also fixes some issues with these approaches.
A state of the art regarding urban air quality prediction models
NASA Astrophysics Data System (ADS)
Croitoru, Cristiana; Nastase, Ilinca
2018-02-01
Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.
Development of Universal Controller Architecture for SiC Based Power Electronic Building Blocks
2017-10-30
time control and control network routing and the other for non -real time instrumentation and monitoring. The two subsystems are isolated and share...directly to the processor without any software intervention. We use a non -real time I Gb/s Ethernet interface for monitoring and control of the module...NOTC1 802.lW Spanning tree Prot. 76.96 184.0 107.04 Multiple point Private Line l NOTC1 203.2 382.3 179.1 N/ A Non applicable 1 No traffic control at
DOT National Transportation Integrated Search
2006-04-01
In this research report, an investigation was conducted to identify a suitable traffic monitoring device for collecting traffic data during actual emergency evacuation conditions that may result from hurricanes in Louisiana. The study reviewed thorou...
Joint parameter and state estimation algorithms for real-time traffic monitoring.
DOT National Transportation Integrated Search
2013-12-01
A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...
Network traffic behaviour near phase transition point
NASA Astrophysics Data System (ADS)
Lawniczak, A. T.; Tang, X.
2006-03-01
We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.
A Very Low Power MAC (VLPM) Protocol for Wireless Body Area Networks
Ullah, Niamat; Khan, Pervez; Kwak, Kyung Sup
2011-01-01
Wireless Body Area Networks (WBANs) consist of a limited number of battery operated nodes that are used to monitor the vital signs of a patient over long periods of time without restricting the patient’s movements. They are an easy and fast way to diagnose the patient’s status and to consult the doctor. Device as well as network lifetime are among the most important factors in a WBAN. Prolonging the lifetime of the WBAN strongly depends on controlling the energy consumption of sensor nodes. To achieve energy efficiency, low duty cycle MAC protocols are used, but for medical applications, especially in the case of pacemakers where data have time-limited relevance, these protocols increase latency which is highly undesirable and leads to system instability. In this paper, we propose a low power MAC protocol (VLPM) based on existing wakeup radio approaches which reduce energy consumption as well as improving the response time of a node. We categorize the traffic into uplink and downlink traffic. The nodes are equipped with both a low power wake-up transmitter and receiver. The low power wake-up receiver monitors the activity on channel all the time with a very low power and keeps the MCU (Micro Controller Unit) along with main radio in sleep mode. When a node [BN or BNC (BAN Coordinator)] wants to communicate with another node, it uses the low-power radio to send a wakeup packet, which will prompt the receiver to power up its primary radio to listen for the message that follows shortly. The wake-up packet contains the desired node’s ID along with some other information to let the targeted node to wake-up and take part in communication and let all other nodes to go to sleep mode quickly. The VLPM protocol is proposed for applications having low traffic conditions. For high traffic rates, optimization is needed. Analytical results show that the proposed protocol outperforms both synchronized and unsynchronized MAC protocols like T-MAC, SCP-MAC, B-MAC and X-MAC in terms of energy consumption and response time. PMID:22163818
Improved Efficient Routing Strategy on Scale-Free Networks
NASA Astrophysics Data System (ADS)
Jiang, Zhong-Yuan; Liang, Man-Gui
Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.
NASA Astrophysics Data System (ADS)
Yu, Chang Ho; Fan, Zhihua; Lioy, Paul J.; Baptista, Ana; Greenberg, Molly; Laumbach, Robert J.
2016-09-01
Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30-10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09-16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512-159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27-46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22-6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.
Intersection Monitor for Traffic-Light-Preemption System
NASA Technical Reports Server (NTRS)
Bachelder, Aaron; Foster, Conrad
2006-01-01
The figure shows an intersection monitor that is a key subsystem of an emergency traffic-light-preemption system that could be any of the systems described in the three immediately preceding articles and in Systems Would Preempt Traffic Lights for Emergency Vehicles (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. This unit is so named because it is installed at an intersection, where it monitors the phases (in the sense of timing) of the traffic lights. The mode of operation of this monitor is independent of the type of traffic-light-controller hardware or software in use at the intersection. Moreover, the design of the monitor is such that (1) the monitor does not, by itself, affect the operation of the traffic- light controller and (2) in the event of a failure of the monitor, the trafficlight controller continues to function normally (albeit without preemption). The monitor is installed in series with the traffic-light controller at an intersection. The control signals of interest are monitored by use of high-impedance taps on affected control lines. These taps are fully isolated and further protected by high-voltage diodes that prevent any voltages or short circuits that arise within the monitor from affecting the controller. The signals from the taps are processed digitally and cleaned up by use of high-speed logic gates, and the resulting data are passed on to other parts of the traffic-light-preemption intersection subsystem. The data are compared continuously with data from vehicles and used to calculate timing for reliable preemption of the traffic lights. The pedestrian crossing at the intersection is also monitored, and pedestrians are warned not to cross during preemption.
Large-scale measurement and modeling of backbone Internet traffic
NASA Astrophysics Data System (ADS)
Roughan, Matthew; Gottlieb, Joel
2002-07-01
There is a brewing controversy in the traffic modeling community concerning how to model backbone traffic. The fundamental work on self-similarity in data traffic appears to be contradicted by recent findings that suggest that backbone traffic is smooth. The traffic analysis work to date has focused on high-quality but limited-scope packet trace measurements; this limits its applicability to high-speed backbone traffic. This paper uses more than one year's worth of SNMP traffic data covering an entire Tier 1 ISP backbone to address the question of how backbone network traffic should be modeled. Although the limitations of SNMP measurements do not permit us to comment on the fine timescale behavior of the traffic, careful analysis of the data suggests that irrespective of the variation at fine timescales, we can construct a simple traffic model that captures key features of the observed traffic. Furthermore, the model's parameters are measurable using existing network infrastructure, making this model practical in a present-day operational network. In addition to its practicality, the model verifies basic statistical multiplexing results, and thus sheds deep insight into how smooth backbone traffic really is.
NASA Astrophysics Data System (ADS)
Sciare, Jean; Petit, Jean-Eudes; Sarda-Esteve, Roland; Bonnaire, Nicolas; Gros, Valérie; Pernot, Pierre; Ghersi, Véronique; Ampe, Christophe; Songeur, Charlotte; Brugge, Benjamin; Debert, Christophe; Favez, Olivier; Le Priol, Tiphaine; Mocnik, Grisa
2013-04-01
Motivations. Road traffic and domestic wood burning emissions are two major contributors of particulate pollution in our cities. These two sources emit ultra-fine, soot containing, particles in the atmosphere, affecting health adversely, increasing morbidity and mortality from cardiovascular and respiratory conditions and casing lung cancer. A better characterization of soot containing aerosol sources in our major cities provides useful information for policy makers for assessment, implementation and monitoring of strategies to tackle air pollution issues affecting human health with additional benefits for climate change. Objectives. This study on local sources of primary Particulate Matter (PM) in the megacity of Paris is a follow-up of several programs (incl. EU-FP7-MEGAPOLI) that have shown that fine PM - in the Paris background atmosphere - is mostly secondary and imported. A network of 14 stations of Black Carbon has been implemented in the larger region of Paris to provide highly spatially resolved long term survey of local combustion aerosols. To our best knowledge, this is the first time that such densely BC network is operating over a large urban area, providing novel information on the spatial/temporal distribution of combustion aerosols within a post-industrialized megacity. Experimental. As part of the PRIMEQUAL "PREQUALIF" project, a dense Black Carbon network (of 14 stations) has been installed over the city of Paris beginning of 2012 in order to produce spatially resolved Equivalent Black Carbon (EBC) concentration maps with high time resolution through modeling and data assimilation. This network is composed of various real-time instruments (Multi-Angle Absorption Photometer, MAAP by THERMO; Multi-wavelength Aethalometers by MAGEE Scientific) implemented in contrasted sites (rural background, urban background, traffic) complementing the regulated measurements (PM, NOx) in the local air quality network AIRPARIF (http://www.airparif.asso.fr/). Contribution of imported versus local EBC is calculated using the "Lenschow" methodology (Lenschow et al., 2001), whereas the influence of domestic wood burning EBC (vs traffic) over the region of Paris is evaluated using the Aethalometer model developed by Sandradewi et al. (2008). Results and discussion. First results of this BC network are presented here including the temporal variations of EBC from wood burning (domestic heating) and fossil fuel (traffic) for the various sites (1-year observation for rural background and traffic sites; 4-year observations for urban background). The local versus imported contributions of EBC are also presented and discussed for these 2 sources. References. Lenschow, P., et al., Some ideas about the sources of PM10, Atmospheric Environment 35 Supplement No. 1 (2001) S23-S33 Sandradewi, J., et al., Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 3316-3323, 2008
Statistical Traffic Anomaly Detection in Time-Varying Communication Networks
2015-02-01
methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types
Statistical Traffic Anomaly Detection in Time Varying Communication Networks
2015-02-01
methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types
Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic
NASA Astrophysics Data System (ADS)
Li, Yan; Dai, Shifang; Wu, Weiwei
2016-12-01
Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.
Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kerner, Boris S.
It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less
An On-Demand Emergency Packet Transmission Scheme for Wireless Body Area Networks.
Al Ameen, Moshaddique; Hong, Choong Seon
2015-12-04
The rapid developments of sensor devices that can actively monitor human activities have given rise to a new field called wireless body area network (BAN). A BAN can manage devices in, on and around the human body. Major requirements of such a network are energy efficiency, long lifetime, low delay, security, etc. Traffic in a BAN can be scheduled (normal) or event-driven (emergency). Traditional media access control (MAC) protocols use duty cycling to improve performance. A sleep-wake up cycle is employed to save energy. However, this mechanism lacks features to handle emergency traffic in a prompt and immediate manner. To deliver an emergency packet, a node has to wait until the receiver is awake. It also suffers from overheads, such as idle listening, overhearing and control packet handshakes. An external radio-triggered wake up mechanism is proposed to handle prompt communication. It can reduce the overheads and improve the performance through an on-demand scheme. In this work, we present a simple-to-implement on-demand packet transmission scheme by taking into considerations the requirements of a BAN. The major concern is handling the event-based emergency traffic. The performance analysis of the proposed scheme is presented. The results showed significant improvements in the overall performance of a BAN compared to state-of-the-art protocols in terms of energy consumption, delay and lifetime.
An On-Demand Emergency Packet Transmission Scheme for Wireless Body Area Networks
Al Ameen, Moshaddique; Hong, Choong Seon
2015-01-01
The rapid developments of sensor devices that can actively monitor human activities have given rise to a new field called wireless body area network (BAN). A BAN can manage devices in, on and around the human body. Major requirements of such a network are energy efficiency, long lifetime, low delay, security, etc. Traffic in a BAN can be scheduled (normal) or event-driven (emergency). Traditional media access control (MAC) protocols use duty cycling to improve performance. A sleep-wake up cycle is employed to save energy. However, this mechanism lacks features to handle emergency traffic in a prompt and immediate manner. To deliver an emergency packet, a node has to wait until the receiver is awake. It also suffers from overheads, such as idle listening, overhearing and control packet handshakes. An external radio-triggered wake up mechanism is proposed to handle prompt communication. It can reduce the overheads and improve the performance through an on-demand scheme. In this work, we present a simple-to-implement on-demand packet transmission scheme by taking into considerations the requirements of a BAN. The major concern is handling the event-based emergency traffic. The performance analysis of the proposed scheme is presented. The results showed significant improvements in the overall performance of a BAN compared to state-of-the-art protocols in terms of energy consumption, delay and lifetime. PMID:26690161
Traffic sign recognition by color segmentation and neural network
NASA Astrophysics Data System (ADS)
Surinwarangkoon, Thongchai; Nitsuwat, Supot; Moore, Elvin J.
2011-12-01
An algorithm is proposed for traffic sign detection and identification based on color filtering, color segmentation and neural networks. Traffic signs in Thailand are classified by color into four types: namely, prohibitory signs (red or blue), general warning signs (yellow) and construction area warning signs (amber). A color filtering method is first used to detect traffic signs and classify them by type. Then color segmentation methods adapted for each color type are used to extract inner features, e.g., arrows, bars etc. Finally, neural networks trained to recognize signs in each color type are used to identify any given traffic sign. Experiments show that the algorithm can improve the accuracy of traffic sign detection and recognition for the traffic signs used in Thailand.
CubeSat constellation design for air traffic monitoring
NASA Astrophysics Data System (ADS)
Nag, Sreeja; Rios, Joseph L.; Gerhardt, David; Pham, Camvu
2016-11-01
Suitably equipped global and local air traffic can be tracked. The tracking information may then be used for control from ground-based stations by receiving the Automatic Dependent Surveillance-Broadcast (ADS-B) signal. In this paper, we describe a tool for designing a constellation of small satellites which demonstrates, through high-fidelity modeling based on simulated air traffic data, the value of space-based ADS-B monitoring. It thereby provides recommendations for cost-efficient deployment of a constellation of small satellites to increase safety and situational awareness in the currently poorly-served surveillance area of Alaska. Air traffic data were obtained from NASA's Future ATM Concepts Evaluation Tool, for the Alaskan airspace over one day. The results presented were driven by MATLAB and the satellites propagated and coverage calculated using AGI's Satellite Tool. While Ad-hoc and precession spread constellations have been quantitatively evaluated, Walker constellations show the best performance in simulation. Sixteen satellites in two perpendicular orbital planes are shown to provide more than 99% coverage over representative Alaskan airspace and the maximum time gap where any airplane in Alaska is not covered is six minutes, therefore meeting the standard set by the International Civil Aviation Organization to monitor every airplane at least once every fifteen minutes. In spite of the risk of signal collision when multiple packets arrive at the satellite receiver, the proposed constellation shows 99% cumulative probability of reception within four minutes when the airplanes are transmitting every minute, and at 100% reception probability if transmitting every second. Data downlink can be performed using any of the three ground stations of NASA Earth Network in Alaska.
Optimal topologies for maximizing network transmission capacity
NASA Astrophysics Data System (ADS)
Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.
2018-04-01
It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.
Traffic engineering and regenerator placement in GMPLS networks with restoration
NASA Astrophysics Data System (ADS)
Yetginer, Emre; Karasan, Ezhan
2002-07-01
In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.
Estimates of CO2 traffic emissions from mobile concentration measurements
NASA Astrophysics Data System (ADS)
Maness, H. L.; Thurlow, M. E.; McDonald, B. C.; Harley, R. A.
2015-03-01
We present data from a new mobile system intended to aid in the design of upcoming urban CO2-monitoring networks. Our collected data include GPS probe data, video-derived traffic density, and accurate CO2 concentration measurements. The method described here is economical, scalable, and self-contained, allowing for potential future deployment in locations without existing traffic infrastructure or vehicle fleet information. Using a test data set collected on California Highway 24 over a 2 week period, we observe that on-road CO2 concentrations are elevated by a factor of 2 in congestion compared to free-flow conditions. This result is found to be consistent with a model including vehicle-induced turbulence and standard engine physics. In contrast to surface concentrations, surface emissions are found to be relatively insensitive to congestion. We next use our model for CO2 concentration together with our data to independently derive vehicle emission rate parameters. Parameters scaling the leading four emission rate terms are found to be within 25% of those expected for a typical passenger car fleet, enabling us to derive instantaneous emission rates directly from our data that compare generally favorably to predictive models presented in the literature. The present results highlight the importance of high spatial and temporal resolution traffic data for interpreting on- and near-road concentration measurements. Future work will focus on transport and the integration of mobile platforms into existing stationary network designs.
DOT National Transportation Integrated Search
2009-09-01
The opening of a major traffic generator in the San Antonio area provided an opportunity to develop and : implement an extensive traffic monitoring system to analyze local, area, and regional traffic impacts from the : generator. Researchers reviewed...
Arcos-García, Álvaro; Álvarez-García, Juan A; Soria-Morillo, Luis M
2018-03-01
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements. Copyright © 2018 Elsevier Ltd. All rights reserved.
Traffic signal synchronization in the saturated high-density grid road network.
Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye
2015-01-01
Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.
Community structure in traffic zones based on travel demand
NASA Astrophysics Data System (ADS)
Sun, Li; Ling, Ximan; He, Kun; Tan, Qian
2016-09-01
Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin-destination pairs with large number of trips play a significant role in urban traffic network's community division. The layout of traffic community in a city also depends on the residents' trajectories.
Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Hong; Aziz, H M Abdul; Young, Stan
Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less
Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network
NASA Astrophysics Data System (ADS)
Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang
2015-12-01
Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.
Analysis of a Dynamic Multi-Track Airway Concept for Air Traffic Management
NASA Technical Reports Server (NTRS)
Wing, David J.; Smith, Jeremy C.; Ballin, Mark G.
2008-01-01
The Dynamic Multi-track Airways (DMA) Concept for Air Traffic Management (ATM) proposes a network of high-altitude airways constructed of multiple, closely spaced, parallel tracks designed to increase en-route capacity in high-demand airspace corridors. Segregated from non-airway operations, these multi-track airways establish high-priority traffic flow corridors along optimal routes between major terminal areas throughout the National Airspace System (NAS). Air traffic controllers transition aircraft equipped for DMA operations to DMA entry points, the aircraft use autonomous control of airspeed to fly the continuous-airspace airway and achieve an economic benefit, and controllers then transition the aircraft from the DMA exit to the terminal area. Aircraft authority within the DMA includes responsibility for spacing and/or separation from other DMA aircraft. The DMA controller is responsible for coordinating the entry and exit of traffic to and from the DMA and for traffic flow management (TFM), including adjusting DMA routing on a daily basis to account for predicted weather and wind patterns and re-routing DMAs in real time to accommodate unpredicted weather changes. However, the DMA controller is not responsible for monitoring the DMA for traffic separation. This report defines the mature state concept, explores its feasibility and performance, and identifies potential benefits. The report also discusses (a) an analysis of a single DMA, which was modeled within the NAS to assess capacity and determine the impact of a single DMA on regional sector loads and conflict potential; (b) a demand analysis, which was conducted to determine likely city-pair candidates for a nationwide DMA network and to determine the expected demand fraction; (c) two track configurations, which were modeled and analyzed for their operational characteristic; (d) software-prototype airborne capabilities developed for DMA operations research; (e) a feasibility analysis of key attributes in the concept design; (f) a near-term, transitional application of the DMA concept as a proving ground for new airborne technologies; and (g) conclusions. The analysis indicates that the operational feasibility of a national DMA network faces significant challenges, especially for interactions between DMAs and between DMA and non-DMA traffic. Provided these issues are resolved, sectors near DMAs could experience significant local capacity benefits.
Data modeling of network dynamics
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad
2004-01-01
This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.
Capacity-constrained traffic assignment in networks with residual queues
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lam, W.H.K.; Zhang, Y.
2000-04-01
This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less
NASA Astrophysics Data System (ADS)
Yan, Fei; Tian, Fuli; Shi, Zhongke
2016-10-01
Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.
General Dynamics of Topology and Traffic on Weighted Technological Networks
NASA Astrophysics Data System (ADS)
Wang, Wen-Xu; Wang, Bing-Hong; Hu, Bo; Yan, Gang; Ou, Qing
2005-05-01
For most technical networks, the interplay of dynamics, traffic, and topology is assumed crucial to their evolution. In this Letter, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general strength-coupling mechanism under which the traffic and topology mutually interact, the model gives power-law distributions of degree, weight, and strength, as confirmed in many real networks. Particularly, depending on a parameter W that controls the total weight growth of the system, the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation are all consistent with empirical evidence.
Considerations for Isochronous Data Services over the Proximity-1 Space Link
NASA Technical Reports Server (NTRS)
Gao, Jay L.
2006-01-01
Future mission concepts for robotic and human explorations will involve a high level of real time control/monitoring operations such as tele-operation for spacecraft rendezvous and surface mobile platforms carrying life-support equipments. The timely dissemination of voice, command, and real-time telemetry for monitoring and coordination purposes is critical for mission success. It is envisioned that future missions will require a network infrastructure capable of supporting isochronous data services. The CCSDS Proximity-1 Space Link Protocol1 could be used to provide isochronous service over the surface-to-Earth relay as well as "beyond-the-horizon" communications between distant Lunar or Mars surface elements. This paper will analyze the latency, jitter, and throughput performance of the Proximity-1 protocol for isochronous applications. In particular we will focus on constrained scenarios where the protocol operates in full-duplex mode, carrying isochronous traffic in one direction and error-controlled traffic in the other direction. We analyze the impact of the strict priority scheme in Proximity-1 on delay jitter and the impact of the isochronous traffic on the efficiency of the reliable data transfer in the other direction, and discuss methods for performance optimization. In general, jitter performance is driving by relative loading of isochronous traffic on the forward link compared to the acknowledgement traffic. Under light loading condition, the upper-bound of the delay jitter is the transmission duration of an acknowledgement frame on the forward link; for higher loading scenarios, the maximum jitter is scaled up by the inverse of the residual bandwidth, i.e., the spare capacity available in the forward link to carry isochronous traffic.
Landslides risk mitigation along lifelines
NASA Astrophysics Data System (ADS)
Capparelli, G.; Versace, P.; Artese, G.; Costanzo, S.; Corsonello, P.; Di Massa, G.; Mendicino, G.; Maletta, D.; Leone, S.; Muto, F.; Senatore, A.; Troncone, A.; Conte, E.; Galletta, D.
2012-04-01
The paper describes an integrated, innovative and efficient solution to manage risk issues associated to landslides interfering with infrastructures. The research project was submitted for financial support in the framework of the Multi -regional Operational Programme 2007-13: Research and Competitiveness funded by the Ministry of Research (MIUR) and co-funded by the European Regional Development Fund. The project is aimed to developing and demonstrating an integrated system of monitoring, early warning and mitigation of landslides risk. The final goal is to timely identify potentially dangerous landslides, and to activate all needed impact mitigation measures, including the information delivery. The essential components of the system include monitoring arrays, telecommunication networks and scenario simulation models, assisted by a data acquisition and processing centre, and a traffic control centres. Upon integration, the system will be experimentally validated and demonstrated over ca. 200 km of three highway sections, crossing the regions of Campania, Basilicata, Calabria and Sicily. Progress in the state of art is represented by the developments in the field of environmental monitoring and in the mathematical modeling of landslides and by the development of services for traffic management. The approach to the problem corresponds to a "systemic logics" where each developed component foresees different interchangeable technological solutions to maximize the operational flexibility. The final system may be configured as a simple to complex structure, including different configurations to deal with different scenarios. Specifically, six different monitoring systems will be realized: three "point" systems, made up of a network of locally measuring sensors, and three "area" systems to remotely measure the displacements of large areas. Each network will be fully integrated and connected to a unique data transmission system. Standardized and shared procedures for the identification of risk scenarios will be developed, concerning the surveys to be carried out, the procedures for each type of on-site testing and guidelines and dynamic templates for presentations of results, such as highway risk maps e.g. The setting up of data acquisition and processing centre and traffic control centre are the core of the integrated system. The DAC (data acquisition center, newly designed) will acquire and process data varying in intensity, dimensions, characteristics and information content. The Traffic Control Center (TCC) is meant to integrate the scientific and the management aspects of hydrological risk monitoring and early warning. The overall system is expected to benefit of the development of new, advanced mathematical models on landslide triggers and propagation. Triggering models will be empirical or hydrological, represented by simple empirical relationships, obtained by linking the antecedent rainfall and the landslide time occurrence, and complete models identified through more complex expressions that take into account different components as the specific site conditions, the mechanical, hydraulic and physical properties of soils and slopes, the local seepage conditions and their contribution to soil strength. The industrial partners of the University of Calabria are Autostrade Tech, Strago and TD Group, with the Universities of Firenze and Catania acting research Partners.
Integrating intersection traffic signal data into a traffic monitoring program.
DOT National Transportation Integrated Search
2014-09-01
The objective of this study was to provide the Georgia Department of Transportation with : an evaluation of the feasibility of integrating intersection traffic signal data into a traffic : monitoring program. Some of the pertinent conclusions from th...
New Mexico state traffic monitoring standards, calendar year 2009-2010
DOT National Transportation Integrated Search
2010-01-01
What follows are New Mexico's State Traffic Monitoring Standards : (NMSTMS) to be used for all New Mexico Traffic Monitoring activities. : The standards were first implemented on October 1, 1988. They : continue to be reviewed and refined on a three-...
Forecasting short-term data center network traffic load with convolutional neural networks.
Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra
2018-01-01
Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.
Switching performance of OBS network model under prefetched real traffic
NASA Astrophysics Data System (ADS)
Huang, Zhenhua; Xu, Du; Lei, Wen
2005-11-01
Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Forecasting short-term data center network traffic load with convolutional neural networks
Ordozgoiti, Bruno; Gómez-Canaval, Sandra
2018-01-01
Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936
Wang, Chenyu; Xu, Guoai; Sun, Jing
2017-12-19
As an essential part of Internet of Things (IoT), wireless sensor networks (WSNs) have touched every aspect of our lives, such as health monitoring, environmental monitoring and traffic monitoring. However, due to its openness, wireless sensor networks are vulnerable to various security threats. User authentication, as the first fundamental step to protect systems from various attacks, has attracted much attention. Numerous user authentication protocols armed with formal proof are springing up. Recently, two biometric-based schemes were proposed with confidence to be resistant to the known attacks including offline dictionary attack, impersonation attack and so on. However, after a scrutinization of these two schemes, we found them not secure enough as claimed, and then demonstrated that these schemes suffer from various attacks, such as offline dictionary attack, impersonation attack, no user anonymity, no forward secrecy, etc. Furthermore, we proposed an enhanced scheme to overcome the identified weaknesses, and proved its security via Burrows-Abadi-Needham (BAN) logic and the heuristic analysis. Finally, we compared our scheme with other related schemes, and the results showed the superiority of our scheme.
Xu, Guoai; Sun, Jing
2017-01-01
As an essential part of Internet of Things (IoT), wireless sensor networks (WSNs) have touched every aspect of our lives, such as health monitoring, environmental monitoring and traffic monitoring. However, due to its openness, wireless sensor networks are vulnerable to various security threats. User authentication, as the first fundamental step to protect systems from various attacks, has attracted much attention. Numerous user authentication protocols armed with formal proof are springing up. Recently, two biometric-based schemes were proposed with confidence to be resistant to the known attacks including offline dictionary attack, impersonation attack and so on. However, after a scrutinization of these two schemes, we found them not secure enough as claimed, and then demonstrated that these schemes suffer from various attacks, such as offline dictionary attack, impersonation attack, no user anonymity, no forward secrecy, etc. Furthermore, we proposed an enhanced scheme to overcome the identified weaknesses, and proved its security via Burrows–Abadi–Needham (BAN) logic and the heuristic analysis. Finally, we compared our scheme with other related schemes, and the results showed the superiority of our scheme. PMID:29257066
Queuing theory models for computer networks
NASA Technical Reports Server (NTRS)
Galant, David C.
1989-01-01
A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.
Traffic prediction using wireless cellular networks : final report.
DOT National Transportation Integrated Search
2016-03-01
The major objective of this project is to obtain traffic information from existing wireless : infrastructure. : In this project freeway traffic is identified and modeled using data obtained from existing : wireless cellular networks. Most of the prev...
NASA Technical Reports Server (NTRS)
Hall, Brendan (Inventor); Bonk, Ted (Inventor); Varadarajan, Srivatsan (Inventor); Smithgall, William Todd (Inventor); DeLay, Benjamin F. (Inventor)
2017-01-01
Systems and methods for systematic hybrid network scheduling for multiple traffic classes with host timing and phase constraints are provided. In certain embodiments, a method of scheduling communications in a network comprises scheduling transmission of virtual links pertaining to a first traffic class on a global schedule to coordinate transmission of the virtual links pertaining to the first traffic class across all transmitting end stations on the global schedule; and scheduling transmission of each virtual link pertaining to a second traffic class on a local schedule of the respective transmitting end station from which each respective virtual link pertaining to the second traffic class is transmitted such that transmission of each virtual link pertaining to the second traffic class is coordinated only at the respective end station from which each respective virtual link pertaining to the second traffic class is transmitted.
Genetic expression programming-based DBA for enhancing peer-assisted music-on-demand service in EPON
NASA Astrophysics Data System (ADS)
Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar; Lee, Jhong-Yue
2015-03-01
Today, the popularity of peer-assisted music-on-demand (MoD) has increased significantly worldwide. This service allows users to access large music library tracks, listen to music, and share their playlist with other users. Unlike the conventional voice traffic, such an application maintains music quality that ranges from 160 kbps to 320 kbps, which most likely consumes more bandwidth than other traffics. In the access network, Ethernet passive optical network (EPON) is one of the best candidates for delivering such a service because of being cost-effective and with high bandwidth. To maintain music quality, a stutter needs to be prevented because of either network effects or when the due user was not receiving enough resources to play in a timely manner. Therefore, in this paper, we propose two genetic expression programming (GEP)-based dynamic bandwidth allocations (DBAs). The first DBA is a generic DBA that aims to find an optimum formula for voice, video, and data services. The second DBA aims to find optimum formulas so that Optical Line Terminal (OLT) can satisfy not only the voice and Peer-to-Peer (P2P) MoD traffics but also reduce the stutter. Optical Network Unit (ONU) traits such as REPORT and GATE messages, cycle time, and mean packet delay are set to be predictor variables. Simulation results show that our proposed DBAs can satisfy the voice and P2P MoD services packet delay and monitor other overall system performances such as expedited forwarding (EF) jitter, packet loss, bandwidth waste, and system throughputs.
A reaction-diffusion-based coding rate control mechanism for camera sensor networks.
Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki
2010-01-01
A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs
2014-11-15
Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less
Topics on data transmission problem in software definition network
NASA Astrophysics Data System (ADS)
Gao, Wei; Liang, Li; Xu, Tianwei; Gan, Jianhou
2017-08-01
In normal computer networks, the data transmission between two sites go through the shortest path between two corresponding vertices. However, in the setting of software definition network (SDN), it should monitor the network traffic flow in each site and channel timely, and the data transmission path between two sites in SDN should consider the congestion in current networks. Hence, the difference of available data transmission theory between normal computer network and software definition network is that we should consider the prohibit graph structures in SDN, and these forbidden subgraphs represent the sites and channels in which data can't be passed by the serious congestion. Inspired by theoretical analysis of an available data transmission in SDN, we consider some computational problems from the perspective of the graph theory. Several results determined in the paper imply the sufficient conditions of data transmission in SDN in the various graph settings.
Traffic Signal Synchronization in the Saturated High-Density Grid Road Network
Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye
2015-01-01
Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835
Price of anarchy on heterogeneous traffic-flow networks.
Rose, A; O'Dea, R; Hopcraft, K I
2016-09-01
The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability-parameterized by the proportion of variable-cost links in the network-changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.
NASA Astrophysics Data System (ADS)
Ren, Yihui
As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the network and we demonstrate that the changes can propagate globally, affecting traffic several hundreds of miles away. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events. In the second part of the thesis we focus on network deconstruction and community detection problems, both intensely studied topics in network science, using a weighted betweenness centrality approach. We present an algorithm that solves both problems efficiently and accurately and demonstrate that on both benchmark networks and data networks.
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie
2017-03-01
A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.
NASA Astrophysics Data System (ADS)
Dimond, David A.; Burgess, Robert; Barrios, Nolan; Johnson, Neil D.
2000-05-01
Traditionally, to guarantee the network performance of medical image data transmission, imaging traffic was isolated on a separate network. Organizations are depending on a new generation of multi-purpose networks to transport both normal information and image traffic as they expand access to images throughout the enterprise. These organi want to leverage their existing infrastructure for imaging traffic, but are not willing to accept degradations in overall network performance. To guarantee 'on demand' network performance for image transmissions anywhere at any time, networks need to be designed with the ability to 'carve out' bandwidth for specific applications and to minimize the chances of network failures. This paper will present the methodology Cincinnati Children's Hospital Medical Center (CHMC) used to enhance the physical and logical network design of the existing hospital network to guarantee a class of service for imaging traffic. PACS network designs should utilize the existing enterprise local area network i.e. (LAN) infrastructure where appropriate. Logical separation or segmentation provides the application independence from other clinical and administrative applications as required, ensuring bandwidth and service availability.
Traffic Generator (TrafficGen) Version 1.4.2: Users Guide
2016-06-01
events, the user has to enter them manually . We will research and implement a way to better define and organize the multicast addresses so they can be...the network with Transmission Control Protocol and User Datagram Protocol Internet Protocol traffic. Each node generating network traffic in an...TrafficGen Graphical User Interface (GUI) 3 3.1 Anatomy of the User Interface 3 3.2 Scenario Configuration and MGEN Files 4 4. Working with
Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.
DOT National Transportation Integrated Search
2010-05-01
Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...
DOT National Transportation Integrated Search
2009-11-01
One of the most common traffic volume parameters reported by statewide traffic monitoring programs is annual average daily traffic (AADT). Departments of Transportation (DOT) and other state agencies use a series of continuous vehicle detection devic...
Dynamic autonomous routing technology for IP-based satellite ad hoc networks
NASA Astrophysics Data System (ADS)
Wang, Xiaofei; Deng, Jing; Kostas, Theresa; Rajappan, Gowri
2014-06-01
IP-based routing for military LEO/MEO satellite ad hoc networks is very challenging due to network and traffic heterogeneity, network topology and traffic dynamics. In this paper, we describe a traffic priority-aware routing scheme for such networks, namely Dynamic Autonomous Routing Technology (DART) for satellite ad hoc networks. DART has a cross-layer design, and conducts routing and resource reservation concurrently for optimal performance in the fluid but predictable satellite ad hoc networks. DART ensures end-to-end data delivery with QoS assurances by only choosing routing paths that have sufficient resources, supporting different packet priority levels. In order to do so, DART incorporates several resource management and innovative routing mechanisms, which dynamically adapt to best fit the prevailing conditions. In particular, DART integrates a resource reservation mechanism to reserve network bandwidth resources; a proactive routing mechanism to set up non-overlapping spanning trees to segregate high priority traffic flows from lower priority flows so that the high priority flows do not face contention from low priority flows; a reactive routing mechanism to arbitrate resources between various traffic priorities when needed; a predictive routing mechanism to set up routes for scheduled missions and for anticipated topology changes for QoS assurance. We present simulation results showing the performance of DART. We have conducted these simulations using the Iridium constellation and trajectories as well as realistic military communications scenarios. The simulation results demonstrate DART's ability to discriminate between high-priority and low-priority traffic flows and ensure disparate QoS requirements of these traffic flows.
Deconvolution of mixing time series on a graph
Blocker, Alexander W.; Airoldi, Edoardo M.
2013-01-01
In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt, where the projection mechanism provides information on A. We consider problems in which A specifies mixing on a graph of times series that are bursty and sparse. We develop a multilevel state-space model for mixing times series and an efficient approach to inference. A simple model is used to calibrate regularization parameters that lead to efficient inference in the multilevel state-space model. We apply this method to the problem of estimating point-to-point traffic flows on a network from aggregate measurements. Our solution outperforms existing methods for this problem, and our two-stage approach suggests an efficient inference strategy for multilevel models of multivariate time series. PMID:25309135
Network-wide BGP route prediction for traffic engineering
NASA Astrophysics Data System (ADS)
Feamster, Nick; Rexford, Jennifer
2002-07-01
The Internet consists of about 13,000 Autonomous Systems (AS's) that exchange routing information using the Border Gateway Protocol (BGP). The operators of each AS must have control over the flow of traffic through their network and between neighboring AS's. However, BGP is a complicated, policy-based protocol that does not include any direct support for traffic engineering. In previous work, we have demonstrated that network operators can adapt the flow of traffic in an efficient and predictable fashion through careful adjustments to the BGP policies running on their edge routers. Nevertheless, many details of the BGP protocol and decision process make predicting the effects of these policy changes difficult. In this paper, we describe a tool that predicts traffic flow at network exit points based on the network topology, the import policy associated with each BGP session, and the routing advertisements received from neighboring AS's. We present a linear-time algorithm that computes a network-wide view of the best BGP routes for each destination prefix given a static snapshot of the network state, without simulating the complex details of BGP message passing. We describe how to construct this snapshot using the BGP routing tables and router configuration files available from operational routers. We verify the accuracy of our algorithm by applying our tool to routing and configuration data from AT&T's commercial IP network. Our route prediction techniques help support the operation of large IP backbone networks, where interdomain routing is an important aspect of traffic engineering.
DOT National Transportation Integrated Search
2009-09-01
The purpose of this guide is to aid the Texas Department of Transportation (TxDOT), Metropolitan Planning Organizations (MPO), and other state and local agencies to develop an effective traffic monitoring system for new major traffic generators in th...
Downlink power distributions for 2G and 3G mobile communication networks.
Colombi, Davide; Thors, Björn; Persson, Tomas; Wirén, Niklas; Larsson, Lars-Eric; Jonsson, Mikael; Törnevik, Christer
2013-12-01
Knowledge of realistic power levels is key when conducting accurate EMF exposure assessments. In this study, downlink output power distributions for radio base stations in 2G and 3G mobile communication networks have been assessed. The distributions were obtained from network measurement data collected from the Operations Support System, which normally is used for network monitoring and management. Significant amounts of data were gathered simultaneously for large sets of radio base stations covering wide geographical areas and different environments. The method was validated with in situ measurements. For the 3G network, the 90th percentile of the averaged output power during high traffic hours was found to be 43 % of the maximum available power. The corresponding number for 2G, with two or more transceivers installed, was 65 % or below.
Adaptive route choice modeling in uncertain traffic networks with real-time information.
DOT National Transportation Integrated Search
2013-03-01
The objective of the research is to study travelers' route choice behavior in uncertain traffic networks : with real-time information. The research is motivated by two observations of the traffic system: 1) : the system is inherently uncertain with r...
Emily A. Carter; Timothy P. McDonald; John L. Torbert
1999-01-01
A study was initiated in the Winter of 1998 to examine the utility of employing Global Positioning Systems (GPS) to monitor harvest traffic throughout a loblolly pine plantation and utilize traffic intensity information to assess impacts of select soil physical properties. Traffic maps prepared from GPS positional data indicated the highest concentration of traffic...
Rethinking Traffic Management: Design of Optimizable Networks
2008-06-01
Though this paper used optimization theory to design and analyze DaVinci , op- timization theory is one of many possible tools to enable a grounded...dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci : Dynamically Adaptive VIrtual Networks for a Customized...Internet. In DaVinci , each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated
iSAFT Protocol Validation Platform for On-Board Data Networks
NASA Astrophysics Data System (ADS)
Tavoularis, Antonis; Kollias, Vangelis; Marinis, Kostas
2014-08-01
iSAFT is an integrated powerful HW/SW environmentfor the simulation, validation & monitoring of satellite/spacecraft on-board data networks supporting simultaneously a wide range of protocols (RMAP, PTP, CCSDS Space Packet, TM/TC, CANopen, etc.) and network interfaces (SpaceWire, ECSS MIL-STD-1553, ECSS CAN). It is based on over 20 years of TELETEL's experience in the area of protocol validation in the telecommunications and aeronautical sectors, and it has been fully re-engineered in cooperation of TELETEL with ESA & space Primes, to comply with space on-board industrial validation requirements (ECSS, EGSE, AIT, AIV, etc.). iSAFT is highly modular and expandable to support new network interfaces & protocols and it is based on the powerful iSAFT graphical tool chain (Protocol Analyser / Recorder, TestRunner, Device Simulator, Traffic Generator, etc.).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr
2015-03-10
We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less
NASA Astrophysics Data System (ADS)
Tomkos, I.; Zakynthinos, P.; Klonidis, D.; Marom, D.; Sygletos, S.; Ellis, A.; Salvadori, E.; Siracusa, D.; Angelou, M.; Papastergiou, G.; Psaila, N.; Ferran, J. F.; Ben-Ezra, S.; Jimenez, F.; Fernández-Palacios, J. P.
2013-12-01
The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution.
Traffic-driven epidemic spreading on scale-free networks with tunable degree distribution
NASA Astrophysics Data System (ADS)
Yang, Han-Xin; Wang, Bing-Hong
2016-04-01
We study the traffic-driven epidemic spreading on scale-free networks with tunable degree distribution. The heterogeneity of networks is controlled by the exponent γ of power-law degree distribution. It is found that the epidemic threshold is minimized at about γ=2.2. Moreover, we find that nodes with larger algorithmic betweenness are more likely to be infected. We expect our work to provide new insights in to the effect of network structures on traffic-driven epidemic spreading.
The Loss of Efficiency Caused by Agents’ Uncoordinated Routing in Transport Networks
Wang, Junjie; Wang, Pu
2014-01-01
Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers’ uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks. PMID:25349995
23 CFR 500.204 - TMS components for highway traffic data.
Code of Federal Regulations, 2010 CFR
2010-04-01
... INFRASTRUCTURE MANAGEMENT MANAGEMENT AND MONITORING SYSTEMS Traffic Monitoring System § 500.204 TMS components for highway traffic data. (a) General. Each State's TMS, including those using alternative procedures... 23 Highways 1 2010-04-01 2010-04-01 false TMS components for highway traffic data. 500.204 Section...
Traffic signal coordination and queue management in oversaturated intersection.
DOT National Transportation Integrated Search
2011-03-18
Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...
Traffic signal coordination and queue management in oversaturated intersections.
DOT National Transportation Integrated Search
2011-03-18
Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...
Directional MAC approach for wireless body area networks.
Hussain, Md Asdaque; Alam, Md Nasre; Kwak, Kyung Sup
2011-01-01
Wireless Body Area Networks (WBANs) designed for medical, sports, and entertainment applications, have drawn the attention of academia and industry alike. A WBAN is a special purpose network, designed to operate autonomously to connect various medical sensors and appliances, located inside and/or outside of a human body. This network enables physicians to remotely monitor vital signs of patients and provide real time feedback for medical diagnosis and consultations. The WBAN system can offer two significant advantages: patient mobility due to their use of portable monitoring devices and a location independent monitoring facility. With its appealing dimensions, it brings about a new set of challenges, which we do not normally consider in such small sensor networks. It requires a scalable network in terms of heterogeneous data traffic, low power consumption of sensor nodes, integration in and around the body networking and coexistence. This work presents a medium access control protocol for WBAN which tries to overcome the aforementioned challenges. We consider the use of multiple beam adaptive arrays (MBAA) at BAN Coordinator (BAN_C) node. When used as a BAN_C, an MBAA can successfully receive two or more overlapping packets at the same time. Each beam captures a different packet by automatically pointing its pattern toward one packet while annulling other contending packets. This paper describes how an MBAA can be integrated into a single hope star topology as a BAN_C. Simulation results show the performance of our proposed protocol.
DOT National Transportation Integrated Search
2015-07-01
Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...
DOT National Transportation Integrated Search
2014-04-01
Trip origin-destination (O-D) demand matrices are critical components in transportation network : modeling, and provide essential information on trip distributions and corresponding spatiotemporal : traffic patterns in traffic zones in vehicular netw...
Traffic handling capability of a broadband indoor wireless network using CDMA multiple access
NASA Astrophysics Data System (ADS)
Zhang, Chang G.; Hafez, H. M.; Falconer, David D.
1994-05-01
CDMA (code division multiple access) may be an attractive technique for wireless access to broadband services because of its multiple access simplicity and other appealing features. In order to investigate traffic handling capabilities of a future network providing a variety of integrated services, this paper presents a study of a broadband indoor wireless network supporting high-speed traffic using CDMA multiple access. The results are obtained through the simulation of an indoor environment and the traffic capabilities of the wireless access to broadband 155.5 MHz ATM-SONET networks using the mm-wave band. A distributed system architecture is employed and the system performance is measured in terms of call blocking probability and dropping probability. The impacts of the base station density, traffic load, average holding time, and variable traffic sources on the system performance are examined. The improvement of system performance by implementing various techniques such as handoff, admission control, power control and sectorization are also investigated.
An optimal routing strategy on scale-free networks
NASA Astrophysics Data System (ADS)
Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin
Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.
Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis.
Chao, Qianwen; Deng, Zhigang; Ren, Jiaping; Ye, Qianqian; Jin, Xiaogang
2018-02-01
We present a novel data-driven approach to populate virtual road networks with realistic traffic flows. Specifically, given a limited set of vehicle trajectories as the input samples, our approach first synthesizes a large set of vehicle trajectories. By taking the spatio-temporal information of traffic flows as a 2D texture, the generation of new traffic flows can be formulated as a texture synthesis process, which is solved by minimizing a newly developed traffic texture energy. The synthesized output captures the spatio-temporal dynamics of the input traffic flows, and the vehicle interactions in it strictly follow traffic rules. After that, we position the synthesized vehicle trajectory data to virtual road networks using a cage-based registration scheme, where a few traffic-specific constraints are enforced to maintain each vehicle's original spatial location and synchronize its motion in concert with its neighboring vehicles. Our approach is intuitive to control and scalable to the complexity of virtual road networks. We validated our approach through many experiments and paired comparison user studies.
On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.
Amanowicz, Marek; Krygier, Jaroslaw
2018-05-26
In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.
Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon
2015-08-11
Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.
Developing an Approach for Analyzing and Verifying System Communication
NASA Technical Reports Server (NTRS)
Stratton, William C.; Lindvall, Mikael; Ackermann, Chris; Sibol, Deane E.; Godfrey, Sally
2009-01-01
This slide presentation reviews a project for developing an approach for analyzing and verifying the inter system communications. The motivation for the study was that software systems in the aerospace domain are inherently complex, and operate under tight constraints for resources, so that systems of systems must communicate with each other to fulfill the tasks. The systems of systems requires reliable communications. The technical approach was to develop a system, DynSAVE, that detects communication problems among the systems. The project enhanced the proven Software Architecture Visualization and Evaluation (SAVE) tool to create Dynamic SAVE (DynSAVE). The approach monitors and records low level network traffic, converting low level traffic into meaningful messages, and displays the messages in a way the issues can be detected.
Price of anarchy on heterogeneous traffic-flow networks
NASA Astrophysics Data System (ADS)
Rose, A.; O'Dea, R.; Hopcraft, K. I.
2016-09-01
The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.
Teaching Network Security with IP Darkspace Data
ERIC Educational Resources Information Center
Zseby, Tanja; Iglesias Vázquez, Félix; King, Alistair; Claffy, K. C.
2016-01-01
This paper presents a network security laboratory project for teaching network traffic anomaly detection methods to electrical engineering students. The project design follows a research-oriented teaching principle, enabling students to make their own discoveries in real network traffic, using data captured from a large IP darkspace monitor…
Ran, Bin; Song, Li; Cheng, Yang; Tan, Huachun
2016-01-01
Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%. PMID:27448326
Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun
2016-01-01
Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.
A reliable transmission protocol for ZigBee-based wireless patient monitoring.
Chen, Shyr-Kuen; Kao, Tsair; Chan, Chia-Tai; Huang, Chih-Ning; Chiang, Chih-Yen; Lai, Chin-Yu; Tung, Tse-Hua; Wang, Pi-Chung
2012-01-01
Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation. In a multihop ZigBee network, the existing systems usually use broadcast or multicast schemes to increase the reliability of signals transmission; however, both the schemes lead to significantly higher network traffic and end-to-end transmission delay. In this paper, we present a reliable transmission protocol based on anycast routing for wireless patient monitoring. Our scheme automatically selects the closest data receiver in an anycast group as a destination to reduce the transmission latency as well as the control overhead. The new protocol also shortens the latency of path recovery by initiating route recovery from the intermediate routers of the original path. On the basis of a reliable transmission scheme, we implement a ZigBee device for fall monitoring, which integrates fall detection, indoor positioning, and ECG monitoring. When the triaxial accelerometer of the device detects a fall, the current position of the patient is transmitted to an emergency center through a ZigBee network. In order to clarify the situation of the fallen patient, 4-s ECG signals are also transmitted. Our transmission scheme ensures the successful transmission of these critical messages. The experimental results show that our scheme is fast and reliable. We also demonstrate that our devices can seamlessly integrate with the next generation technology of wireless wide area network, worldwide interoperability for microwave access, to achieve real-time patient monitoring.
Traffic Management in ATM Networks Over Satellite Links
NASA Technical Reports Server (NTRS)
Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas
1999-01-01
This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.
NASA Technical Reports Server (NTRS)
Huber, Hans
2006-01-01
Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.
Traffic-aware energy saving scheme with modularization supporting in TWDM-PON
NASA Astrophysics Data System (ADS)
Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun
2017-01-01
Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.
DOT National Transportation Integrated Search
2014-07-01
Street networks designed to support Transit Oriented Development (TOD) increase accessibility for non-motorized traffic. However, the implications of TOD supportive networks for still dominant vehicular : traffic are rarely addressed. Due to this lac...
23 CFR 658.21 - Identification of National Network.
Code of Federal Regulations, 2012 CFR
2012-04-01
... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...
23 CFR 658.21 - Identification of National Network.
Code of Federal Regulations, 2013 CFR
2013-04-01
... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...
23 CFR 658.21 - Identification of National Network.
Code of Federal Regulations, 2014 CFR
2014-04-01
... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...
DOT National Transportation Integrated Search
2015-06-01
Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...
Analysis of road traffic obstructions caused by the central European flood in June 2013 in Germany
NASA Astrophysics Data System (ADS)
Bessel, Tina
2014-05-01
The flood in June 2013 caused in Germany severe damage to infrastructure and has had a great impact on transportation. Traffic was disrupted in the interregional transportation network including federal highways and long distance railways. Researchers from the Center for Disaster Management and Risk Reduction Technology (CEDIM) aim to develop rapid assessment tools which allow a science based estimation of disaster impacts. This is part of a larger project called Forensic Disaster Analysis (FDA). During the flood event, the CEDIM FDA group on transportation disruptions monitored and recorded traffic reports in Germany to obtain accurate information on road traffic obstructions due to the flood. A rapid initial evaluation of the data was carried out for federal and interstate highways on a district level for the period of May 31 till June 4 2013. In this evaluation, the causes and types of traffic obstruction, as well as the number and duration of flood-caused disruptions are considered. In the evaluated time period of five days, an amount of more than 4,800 hours of flood-related traffic obstructions could be observed in a total of 89 districts. Major traffic disruptions were located in the districts along the Mulde and in the foothills of the Alps. This first initial evaluation will be followed by a detailed statistical analysis including all data collected during the flood event. To assess the impacts of the flood on traffic, a simple traffic simulation considering the disruptions will be carried out using a gravity model.
Multi-Layer Approach for the Detection of Selective Forwarding Attacks
Alajmi, Naser; Elleithy, Khaled
2015-01-01
Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable. PMID:26610499
Multi-Layer Approach for the Detection of Selective Forwarding Attacks.
Alajmi, Naser; Elleithy, Khaled
2015-11-19
Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.
Potential of dynamic spectrum allocation in LTE macro networks
NASA Astrophysics Data System (ADS)
Hoffmann, H.; Ramachandra, P.; Kovács, I. Z.; Jorguseski, L.; Gunnarsson, F.; Kürner, T.
2015-11-01
In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic (i.e. the requested traffic from the users) increases the LTE deployment evolves with macro cells expanded with additional capacity boosting LTE carriers in higher frequency bands complemented with micro or small cells in traffic hotspot areas. For MNOs it is crucial to use the LTE spectrum assets, as well as the installed network infrastructure, in the most cost efficient way. The dynamic spectrum allocation (DSA) aims at (de)activating the available LTE frequency carriers according to the temporal and spatial traffic variations in order to increase the overall LTE system performance in terms of total network capacity by reducing the interference. This paper evaluates the DSA potential of achieving the envisaged performance improvement and identifying in which system and traffic conditions the DSA should be deployed. A self-optimised network (SON) DSA algorithm is also proposed and evaluated. The evaluations have been carried out in a hexagonal and a realistic site-specific urban macro layout assuming a central traffic hotspot area surrounded with an area of lower traffic with a total size of approximately 8 × 8 km2. The results show that up to 47 % and up to 40 % possible DSA gains are achievable with regards to the carried system load (i.e. used resources) for homogenous traffic distribution with hexagonal layout and for realistic site-specific urban macro layout, respectively. The SON DSA algorithm evaluation in a realistic site-specific urban macro cell deployment scenario including realistic non-uniform spatial traffic distribution shows insignificant cell throughput (i.e. served traffic) performance gains. Nevertheless, in the SON DSA investigations, a gain of up to 25 % has been observed when analysing the resource utilisation in the non-hotspot cells.
Ullah, Sana; Kwak, Kyung Sup
2012-06-01
Wireless Body Area Network (WBAN) consists of low-power, miniaturized, and autonomous wireless sensor nodes that enable physicians to remotely monitor vital signs of patients and provide real-time feedback with medical diagnosis and consultations. It is the most reliable and cheaper way to take care of patients suffering from chronic diseases such as asthma, diabetes and cardiovascular diseases. Some of the most important attributes of WBAN is low-power consumption and delay. This can be achieved by introducing flexible duty cycling techniques on the energy constraint sensor nodes. Stated otherwise, low duty cycle nodes should not receive frequent synchronization and control packets if they have no data to send/receive. In this paper, we introduce a Traffic-adaptive MAC protocol (TaMAC) by taking into account the traffic information of the sensor nodes. The protocol dynamically adjusts the duty cycle of the sensor nodes according to their traffic-patterns, thus solving the idle listening and overhearing problems. The traffic-patterns of all sensor nodes are organized and maintained by the coordinator. The TaMAC protocol is supported by a wakeup radio that is used to accommodate emergency and on-demand events in a reliable manner. The wakeup radio uses a separate control channel along with the data channel and therefore it has considerably low power consumption requirements. Analytical expressions are derived to analyze and compare the performance of the TaMAC protocol with the well-known beacon-enabled IEEE 802.15.4 MAC, WiseMAC, and SMAC protocols. The analytical derivations are further validated by simulation results. It is shown that the TaMAC protocol outperforms all other protocols in terms of power consumption and delay.
Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco
2017-01-01
The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks. PMID:28134822
Dynamic traffic grooming with Spectrum Engineering (TG-SE) in flexible grid optical networks
NASA Astrophysics Data System (ADS)
Yu, Xiaosong; Zhao, Yongli; Zhang, Jiawei; Wang, Jianping; Zhang, Guoying; Chen, Xue; Zhang, Jie
2015-12-01
Flexible grid has emerged as an evolutionary technology to satisfy the ever increasing demand for higher spectrum efficiency and operational flexibility. To optimize the spectrum resource utilization, this paper introduces the concept of Spectrum Engineering in flex-grid optical networks. The sliceable optical transponder has been proposed to offload IP traffic to the optical layer and reduce the number of IP router ports and transponders. We discuss the impact of sliceable transponder in traffic grooming and propose several traffic-grooming schemes with Spectrum Engineering (TG-SE). Our results show that there is a tradeoff among different traffic grooming policies, which should be adopted based on the network operator's objectives. The proposed traffic grooming with Spectrum Engineering schemes can reduce OPEX as well as increase spectrum efficiency by efficiently utilizing the bandwidth variability and capability of sliceable optical transponders.
Risk analysis of Safety Service Patrol (SSP) systems in Virginia.
Dickey, Brett D; Santos, Joost R
2011-12-01
The transportation infrastructure is a vital backbone of any regional economy as it supports workforce mobility, tourism, and a host of socioeconomic activities. In this article, we specifically examine the incident management function of the transportation infrastructure. In many metropolitan regions, incident management is handled primarily by safety service patrols (SSPs), which monitor and resolve roadway incidents. In Virginia, SSP allocation across highway networks is based typically on average vehicle speeds and incident volumes. This article implements a probabilistic network model that partitions "business as usual" traffic flow with extreme-event scenarios. Results of simulated network scenarios reveal that flexible SSP configurations can improve incident resolution times relative to predetermined SSP assignments. © 2011 Society for Risk Analysis.
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks
Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming
2016-01-01
The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.
Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming
2016-03-14
The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.
Visualization of Traffic Accidents
NASA Technical Reports Server (NTRS)
Wang, Jie; Shen, Yuzhong; Khattak, Asad
2010-01-01
Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.
Measuring Road Network Vulnerability with Sensitivity Analysis
Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin
2017-01-01
This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706
Neural-tree call admission controller for ATM networks
NASA Astrophysics Data System (ADS)
Rughooputh, Harry C. S.
1999-03-01
Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.
Improved efficient routing strategy on two-layer complex networks
NASA Astrophysics Data System (ADS)
Ma, Jinlong; Han, Weizhan; Guo, Qing; Zhang, Shuai; Wang, Junfang; Wang, Zhihao
2016-10-01
The traffic dynamics of multi-layer networks has become a hot research topic since many networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the traditional shortest path routing (SPR) protocol is susceptible to congestion on two-layer complex networks. In this paper, we propose an efficient routing strategy named improved global awareness routing (IGAR) strategy which is based on the betweenness centrality of nodes in the two layers. With the proposed strategy, the routing paths can bypass hub nodes of both layers to enhance the transport efficiency. Simulation results show that the IGAR strategy can bring much better traffic capacity than the SPR and the global awareness routing (GAR) strategies. Because of the significantly improved traffic performance, this study is helpful to alleviate congestion of the two-layer complex networks.
Methods and systems for detecting abnormal digital traffic
Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA
2011-03-22
Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.
A knowledge-based system for controlling automobile traffic
NASA Technical Reports Server (NTRS)
Maravas, Alexander; Stengel, Robert F.
1994-01-01
Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.
Road Network State Estimation Using Random Forest Ensemble Learning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hou, Yi; Edara, Praveen; Chang, Yohan
Network-scale travel time prediction not only enables traffic management centers (TMC) to proactively implement traffic management strategies, but also allows travelers make informed decisions about route choices between various origins and destinations. In this paper, a random forest estimator was proposed to predict travel time in a network. The estimator was trained using two years of historical travel time data for a case study network in St. Louis, Missouri. Both temporal and spatial effects were considered in the modeling process. The random forest models predicted travel times accurately during both congested and uncongested traffic conditions. The computational times for themore » models were low, thus useful for real-time traffic management and traveler information applications.« less
Code of Federal Regulations, 2011 CFR
2011-04-01
... AND MONITORING SYSTEMS Traffic Monitoring System § 500.201 Purpose. The purpose of this subpart is to... traffic monitoring system for highways and public transportation facilities and equipment (TMS) in each...
Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian
2016-10-27
To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.
Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian
2016-01-01
To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794
Optimal resource allocation strategy for two-layer complex networks
NASA Astrophysics Data System (ADS)
Ma, Jinlong; Wang, Lixin; Li, Sufeng; Duan, Congwen; Liu, Yu
2018-02-01
We study the traffic dynamics on two-layer complex networks, and focus on its delivery capacity allocation strategy to enhance traffic capacity measured by the critical value Rc. With the limited packet-delivering capacity, we propose a delivery capacity allocation strategy which can balance the capacities of non-hub nodes and hub nodes to optimize the data flow. With the optimal value of parameter αc, the maximal network capacity is reached because most of the nodes have shared the appropriate delivery capacity by the proposed delivery capacity allocation strategy. Our work will be beneficial to network service providers to design optimal networked traffic dynamics.
VSAT communications networks - An overview
NASA Astrophysics Data System (ADS)
Chakraborty, D.
1988-05-01
The very-small-aperture-terminal (VSAT) fixed satellite communication network is a star network in which many dispersed micro terminals attempt to send data in a packet form through a random access/time-division multiple-access (RA/TDMA) satellite channel with transmission delay. The basic concept of the VSAT and its service potential are discussed. Two classes of traffic are addressed, namely, business-oriented low-rate-data traffic and bulk data traffic of corporate networks. Satellite access, throughput, and delay are considered. The size of the network population that can be served in an RA/TDMA environment is calculated. User protocols are examined. A typical VSAT business scenario is described.
Residual Network Data Structures in Android Devices
2011-09-01
Apple’s iOS, Google’s Android, RIM’s Blackberry and Nokia’s Symbian. Each Smartphone presents unique characteristics for forensic examiners. In...another. • Home Agent: A router on mobile node’s home network that tunnels traffic to mobile node when not on home network. Also maintains mobile nodes...Address notification to the Home Agent. When traffic arrives at the Home Agent for the mobile node, the Home Agent tunnels the traffic to the Care-of
Comparative analysis of the performance of One-Way and Two-Way urban road networks
NASA Astrophysics Data System (ADS)
Gheorghe, Carmen
2017-10-01
The fact that the number of vehicles is increasing year after year represents a challenge in road traffic management because it is necessary to adjust the road traffic, in order to prevent any incidents, using mostly the same road infrastructure. At this moment one-way road network provides efficient traffic flow for vehicles but it is not ideal for pedestrians. Therefore, a proper solution must be found and applied when and where it is necessary. Replacing one-way road network with two-way road network may be a viable solution especially if in the area is high pedestrian traffic. The paper aims to highlight the influence of both, one-way and two-way urban road networks through an experimental research which was performed by using traffic data collected in the field. Each of the two scenarios analyzed were based on the same traffic data, the same geometrical conditions of the road (lane width, total road segment width, road slopes, total length of the road network) and also the same signaling conditions (signalised intersection or roundabout). The analysis which involves two-way scenario reveals changes in the performance parameters like delay average, stops average, delay stop average and vehicle speed average. Based on the values obtained, it was possible to perform a comparative analysis between the real, one-way, scenario and the theoretical, two-way, scenario.
Application of machine learning methods for traffic signs recognition
NASA Astrophysics Data System (ADS)
Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.
2018-02-01
This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.
Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Jing, Ruiquan
2017-11-27
Network operators generally provide dedicated lightpaths for customers to meet the demand for high-quality transmission. Considering the variation of traffic load, customers usually rent peak bandwidth that exceeds the practical average traffic requirement. In this case, bandwidth provisioning is unmetered and customers have to pay according to peak bandwidth. Supposing that network operators could keep track of traffic load and allocate bandwidth dynamically, bandwidth can be provided as a metered service and customers would pay for the bandwidth that they actually use. To achieve cost-effective bandwidth provisioning, this paper proposes an autonomic bandwidth adjustment scheme based on data analysis of traffic load. The scheme is implemented in a software defined networking (SDN) controller and is demonstrated in the field trial of multi-vendor optical transport networks. The field trial shows that the proposed scheme can track traffic load and realize autonomic bandwidth adjustment. In addition, a simulation experiment is conducted to evaluate the performance of the proposed scheme. We also investigate the impact of different parameters on autonomic bandwidth adjustment. Simulation results show that the step size and adjustment period have significant influences on bandwidth savings and packet loss. A small value of step size and adjustment period can bring more benefits by tracking traffic variation with high accuracy. For network operators, the scheme can serve as technical support of realizing bandwidth as metered service in the future.
Spatial distribution of traffic in a cellular mobile data network
NASA Astrophysics Data System (ADS)
Linnartz, J. P. M. G.
1987-02-01
The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.
Software defined multi-OLT passive optical network for flexible traffic allocation
NASA Astrophysics Data System (ADS)
Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Zhang, Jiawei; Li, Hui
2016-10-01
With the rapid growth of 4G mobile network and vehicular network services mobile terminal users have increasing demand on data sharing among different radio remote units (RRUs) and roadside units (RSUs). Meanwhile, commercial video-streaming, video/voice conference applications delivered through peer-to-peer (P2P) technology are still keep on stimulating the sharp increment of bandwidth demand in both business and residential subscribers. However, a significant issue is that, although wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) technology have been proposed to fulfil the ever-increasing bandwidth demand in access network, the bandwidth of optical fiber is not unlimited due to the restriction of optical component properties and modulation/demodulation technology, and blindly increase the wavelength cannot meet the cost-sensitive characteristic of the access network. In this paper, we propose a software defined multi-OLT PON architecture to support efficient scheduling of access network traffic. By introducing software defined networking technology and wavelength selective switch into TWDM PON system in central office, multiple OLTs can be considered as a bandwidth resource pool and support flexible traffic allocation for optical network units (ONUs). Moreover, under the configuration of the control plane, ONUs have the capability of changing affiliation between different OLTs under different traffic situations, thus the inter-OLT traffic can be localized and the data exchange pressure of the core network can be released. Considering this architecture is designed to be maximum following the TWDM PON specification, the existing optical distribution network (ODN) investment can be saved and conventional EPON/GPON equipment can be compatible with the proposed architecture. What's more, based on this architecture, we propose a dynamic wavelength scheduling algorithm, which can be deployed as an application on control plane and achieve effective scheduling OLT wavelength resources between different OLTs based on various traffic situation. Simulation results show that, by using the scheduling algorithm, network traffic between different OLTs can be optimized effectively, and the wavelength utilization of the multi-OLT system can be improved due to the flexible wavelength scheduling.
Heuristic approaches for energy-efficient shared restoration in WDM networks
NASA Astrophysics Data System (ADS)
Alilou, Shahab
In recent years, there has been ongoing research on the design of energy-efficient Wavelength Division Multiplexing (WDM) networks. The explosive growth of Internet traffic has led to increased power consumption of network components. Network survivability has also been a relevant research topic, as it plays a crucial role in assuring continuity of service with no disruption, regardless of network component failure. Network survivability mechanisms tend to utilize considerable resources such as spare capacity in order to protect and restore information. This thesis investigates techniques for reducing energy demand and enhancing energy efficiency in the context of network survivability. We propose two novel heuristic energy-efficient shared protection approaches for WDM networks. These approaches intend to save energy by setting on sleep mode devices that are not being used while providing shared backup paths to satisfy network survivability. The first approach exploits properties of a math series in order to assign weight to the network links. It aims at reducing power consumption at the network indirectly by aggregating traffic on a set of nodes and links with high traffic load level. Routing traffic on links and nodes that are already under utilization makes it possible for the links and nodes with no load to be set on sleep mode. The second approach is intended to dynamically route traffic through nodes and links with high traffic load level. Similar to the first approach, this approach computes a pair of paths for every newly arrived demand. It computes these paths for every new demand by comparing the power consumption of nodes and links in the network before the demand arrives with their potential power consumption if they are chosen along the paths of this demand. Simulations of two different networks were used to compare the total network power consumption obtained using the proposed techniques against a standard shared-path restoration scheme. Shared-path restoration is a network survivability method in which a link-disjoint backup path and wavelength is reserved at the time of call setup for a working path. However, in order to reduce spare capacity consumption, this reserved backup path and wavelength may be shared with other backup paths. Pool Sharing Scheme (PSS) is employed to implement shared-path restoration scheme [1]. In an optical network, the failure of a single link leads to the failure of all the lightpaths that pass through that particular link. PSS ensures that the amount of backup bandwidth required on a link to restore the failed connections will not be more than the total amount of reserved backup bandwidth on that link. Simulation results indicate that the proposed approaches lead to up to 35% power savings in WDM networks when traffic load is low. However, power saving decreases to 14% at high traffic load level. Furthermore, in terms of the total capacity consumption for working paths, PSS outperforms the two proposed approaches, as expected. In terms of total capacity consumption all the approaches behave similarly. In general, at low traffic load level, the two proposed approaches behave similar to PSS in terms of average link load, and the ratio of block demands. Nevertheless, at high traffic load, the proposed approaches result in higher ratio of blocked demands than PSS. They also lead to higher average link load than PSS for the equal number of generated demands.
Fernández-Camacho, R; Brito Cabeza, I; Aroba, J; Gómez-Bravo, F; Rodríguez, S; de la Rosa, J
2015-04-15
This study focuses on correlations between total number concentrations, road traffic emissions and noise levels in an urban area in the southwest of Spain during the winter and summer of 2009. The high temporal correlation between sound pressure levels, traffic intensity, particle number concentrations related to traffic, black carbon and NOx concentrations suggests that noise is linked to traffic emissions as a main source of pollution in urban areas. First, the association of these different variables was studied using PreFuRGe, a computational tool based on data mining and fuzzy logic. The results showed a clear association between noise levels and road-traffic intensity for non-extremely high wind speed levels. This behaviour points, therefore, to vehicular emissions being the main source of urban noise. An analysis for estimating the total number concentration from noise levels is also proposed in the study. The high linearity observed between particle number concentrations linked to traffic and noise levels with road traffic intensity can be used to calculate traffic related particle number concentrations experimentally. At low wind speeds, there are increases in noise levels of 1 dB for every 100 vehicles in circulation. This is equivalent to 2000 cm(-3) per vehicle in winter and 500 cm(-3) in summer. At high wind speeds, wind speed could be taken into account. This methodology allows low cost sensors to be used as a proxy for total number concentration monitoring in urban air quality networks. Copyright © 2015 Elsevier B.V. All rights reserved.
The Monitoring and Spatial-Temporal Evolution Characteristic Analysis for Land Subsidence in Beijing
NASA Astrophysics Data System (ADS)
Zhou, Q.; Zhao, W.; Yu, J.
2018-05-01
At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can't satisfy the need of aquifer recharge that product the land subsidence. As China's political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June-2010 August and ten TerraSAR images acquired in 2011 June-2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matthews, W.
2000-02-22
Modern High Energy Nuclear and Particle Physics (HENP) experiments at Laboratories around the world present a significant challenge to wide area networks. Petabytes (1015) or exabytes (1018) of data will be generated during the lifetime of the experiment. Much of this data will be distributed via the Internet to the experiment's collaborators at Universities and Institutes throughout the world for analysis. In order to assess the feasibility of the computing goals of these and future experiments, the HENP networking community is actively monitoring performance across a large part of the Internet used by its collaborators. Since 1995, the pingER projectmore » has been collecting data on ping packet loss and round trip times. In January 2000, there are 28 monitoring sites in 15 countries gathering data on over 2,000 end-to-end pairs. HENP labs such as SLAC, Fermi Lab and CERN are using Advanced Network's Surveyor project and monitoring performance from one-way delay of UDP packets. More recently several HENP sites have become involved with NLANR's active measurement program (AMP). In addition SLAC and CERN are part of the RIPE test-traffic project and SLAC is home for a NIMI machine. The large End-to-end performance monitoring infrastructure allows the HENP networking community to chart long term trends and closely examine short term glitches across a wide range of networks and connections. The different methodologies provide opportunities to compare results based on different protocols and statistical samples. Understanding agreement and discrepancies between results provides particular insight into the nature of the network. This paper will highlight the practical side of monitoring by reviewing the special needs of High Energy Nuclear and Particle Physics experiments and provide an overview of the experience of measuring performance across a large number of interconnected networks throughout the world with various methodologies. In particular, results from each project will be compared and disagreement will be analyzed. The goal is to address issues for improving understanding for gathering and analysis of accurate monitoring data, but the outlook for the computing goals of HENP will also be examined.« less
Performance evaluation of NASA/KSC CAD/CAE graphics local area network
NASA Technical Reports Server (NTRS)
Zobrist, George
1988-01-01
This study had as an objective the performance evaluation of the existing CAD/CAE graphics network at NASA/KSC. This evaluation will also aid in projecting planned expansions, such as the Space Station project on the existing CAD/CAE network. The objectives were achieved by collecting packet traffic on the various integrated sub-networks. This included items, such as total number of packets on the various subnetworks, source/destination of packets, percent utilization of network capacity, peak traffic rates, and packet size distribution. The NASA/KSC LAN was stressed to determine the useable bandwidth of the Ethernet network and an average design station workload was used to project the increased traffic on the existing network and the planned T1 link. This performance evaluation of the network will aid the NASA/KSC network managers in planning for the integration of future workload requirements into the existing network.
A MAC Protocol for Medical Monitoring Applications of Wireless Body Area Networks
Shu, Minglei; Yuan, Dongfeng; Zhang, Chongqing; Wang, Yinglong; Chen, Changfang
2015-01-01
Targeting the medical monitoring applications of wireless body area networks (WBANs), a hybrid medium access control protocol using an interrupt mechanism (I-MAC) is proposed to improve the energy and time slot utilization efficiency and to meet the data delivery delay requirement at the same time. Unlike existing hybrid MAC protocols, a superframe structure with a longer length is adopted to avoid unnecessary beacons. The time slots are mostly allocated to nodes with periodic data sources. Short interruption slots are inserted into the superframe to convey the urgent data and to guarantee the real-time requirements of these data. During these interruption slots, the coordinator can break the running superframe and start a new superframe. A contention access period (CAP) is only activated when there are more data that need to be delivered. Experimental results show the effectiveness of the proposed MAC protocol in WBANs with low urgent traffic. PMID:26046596
Traffic-Sensitive Live Migration of Virtual Machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deshpande, Umesh; Keahey, Kate
2015-01-01
In this paper we address the problem of network contention between the migration traffic and the VM application traffic for the live migration of co-located Virtual Machines (VMs). When VMs are migrated with pre-copy, they run at the source host during the migration. Therefore the VM applications with predominantly outbound traffic contend with the outgoing migration traffic at the source host. Similarly, during post-copy migration, the VMs run at the destination host. Therefore the VM applications with predominantly inbound traffic contend with the incoming migration traffic at the destination host. Such a contention increases the total migration time of themore » VMs and degrades the performance of VM application. Here, we propose traffic-sensitive live VM migration technique to reduce the contention of migration traffic with the VM application traffic. It uses a combination of pre-copy and post-copy techniques for the migration of the co-located VMs, instead of relying upon any single pre-determined technique for the migration of all the VMs. We base the selection of migration techniques on VMs' network traffic profiles so that the direction of migration traffic complements the direction of the most VM application traffic. We have implemented a prototype of traffic-sensitive migration on the KVM/QEMU platform. In the evaluation, we compare traffic-sensitive migration against the approaches that use only pre-copy or only post-copy for VM migration. We show that our approach minimizes the network contention for migration, thus reducing the total migration time and the application degradation.« less
NASA Astrophysics Data System (ADS)
Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan
2016-02-01
With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.
Technology Developments Integrating a Space Network Communications Testbed
NASA Technical Reports Server (NTRS)
Kwong, Winston; Jennings, Esther; Clare, Loren; Leang, Dee
2006-01-01
As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.
Architectural impact of FDDI network on scheduling hard real-time traffic
NASA Technical Reports Server (NTRS)
Agrawal, Gopal; Chen, Baio; Zhao, Wei; Davari, Sadegh
1991-01-01
The architectural impact on guaranteeing synchronous message deadlines in FDDI (Fiber Distributed Data Interface) token ring networks is examined. The FDDI network does not have facility to support (global) priority arbitration which is a useful facility for scheduling hard real time activities. As a result, it was found that the worst case utilization of synchronous traffic in an FDDI network can be far less than that in a centralized single processor system. Nevertheless, it is proposed and analyzed that a scheduling method can guarantee deadlines of synchronous messages having traffic utilization up to 33 pct., the highest to date.
High-Speed Optical Wide-Area Data-Communication Network
NASA Technical Reports Server (NTRS)
Monacos, Steve P.
1994-01-01
Proposed fiber-optic wide-area network (WAN) for digital communication balances input and output flows of data with its internal capacity by routing traffic via dynamically interconnected routing planes. Data transmitted optically through network by wavelength-division multiplexing in synchronous or asynchronous packets. WAN implemented with currently available technology. Network is multiple-ring cyclic shuffle exchange network ensuring traffic reaches its destination with minimum number of hops.
Tien, Nguyen Xuan; Kim, Semog; Rhee, Jong Myung; Park, Sang Yoon
2017-07-25
Fault tolerance has long been a major concern for sensor communications in fault-tolerant cyber physical systems (CPSs). Network failure problems often occur in wireless sensor networks (WSNs) due to various factors such as the insufficient power of sensor nodes, the dislocation of sensor nodes, the unstable state of wireless links, and unpredictable environmental interference. Fault tolerance is thus one of the key requirements for data communications in WSN applications. This paper proposes a novel path redundancy-based algorithm, called dual separate paths (DSP), that provides fault-tolerant communication with the improvement of the network traffic performance for WSN applications, such as fault-tolerant CPSs. The proposed DSP algorithm establishes two separate paths between a source and a destination in a network based on the network topology information. These paths are node-disjoint paths and have optimal path distances. Unicast frames are delivered from the source to the destination in the network through the dual paths, providing fault-tolerant communication and reducing redundant unicast traffic for the network. The DSP algorithm can be applied to wired and wireless networks, such as WSNs, to provide seamless fault-tolerant communication for mission-critical and life-critical applications such as fault-tolerant CPSs. The analyzed and simulated results show that the DSP-based approach not only provides fault-tolerant communication, but also improves network traffic performance. For the case study in this paper, when the DSP algorithm was applied to high-availability seamless redundancy (HSR) networks, the proposed DSP-based approach reduced the network traffic by 80% to 88% compared with the standard HSR protocol, thus improving network traffic performance.
Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.
Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing
2017-01-01
Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.
The improved degree of urban road traffic network: A case study of Xiamen, China
NASA Astrophysics Data System (ADS)
Wang, Shiguang; Zheng, Lili; Yu, Dexin
2017-03-01
The complex network theory is applied to the study of urban road traffic network topology, and we constructed a new measure to characterize an urban road network. It is inspiring to quantify the interaction more appropriately between nodes in complex networks, especially in the field of traffic. The measure takes into account properties of lanes (e.g. number of lanes, width, traffic direction). As much, it is a more comprehensive measure in comparison to previous network measures. It can be used to grasp the features of urban street network more clearly. We applied this measure to the road network in Xiamen, China. Based on a standard method from statistical physics, we examined in more detail the distribution of this new measure and found that (1) due to the limitation of space geographic attributes, traditional research conclusions acquired by using the original definition of degree to study the primal approach modeled urban street network are not very persuasive; (2) both of the direction of the network connection and the degree's odd or even classifications need to be analyzed specifically; (3) the improved degree distribution presents obvious hierarchy, and hierarchical values conform to the power-law distribution, and correlation of our new measure shows some significant segmentation of the urban road network.
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.
Unsupervised Ensemble Anomaly Detection Using Time-Periodic Packet Sampling
NASA Astrophysics Data System (ADS)
Uchida, Masato; Nawata, Shuichi; Gu, Yu; Tsuru, Masato; Oie, Yuji
We propose an anomaly detection method for finding patterns in network traffic that do not conform to legitimate (i.e., normal) behavior. The proposed method trains a baseline model describing the normal behavior of network traffic without using manually labeled traffic data. The trained baseline model is used as the basis for comparison with the audit network traffic. This anomaly detection works in an unsupervised manner through the use of time-periodic packet sampling, which is used in a manner that differs from its intended purpose — the lossy nature of packet sampling is used to extract normal packets from the unlabeled original traffic data. Evaluation using actual traffic traces showed that the proposed method has false positive and false negative rates in the detection of anomalies regarding TCP SYN packets comparable to those of a conventional method that uses manually labeled traffic data to train the baseline model. Performance variation due to the probabilistic nature of sampled traffic data is mitigated by using ensemble anomaly detection that collectively exploits multiple baseline models in parallel. Alarm sensitivity is adjusted for the intended use by using maximum- and minimum-based anomaly detection that effectively take advantage of the performance variations among the multiple baseline models. Testing using actual traffic traces showed that the proposed anomaly detection method performs as well as one using manually labeled traffic data and better than one using randomly sampled (unlabeled) traffic data.
Ad Hoc Network Architecture for Multi-Media Networks
2007-12-01
sensor network . Video traffic is modeled and simulations are performed via the use of the Sun Small Programmable Object Technology (Sun SPOT) Java...characteristics of video traffic must be studied and understood. This thesis focuses on evaluating the possibility of routing video images over a wireless
Magnetic-Based NDE of Prestressed and Post-Tensioned Concrete Members: The MFL System.
DOT National Transportation Integrated Search
1997-07-01
Many metropolitan areas have begun or are planning to implement traffic monitoring programs to meet the many demands for traffic data. The purpose of this project is to document a series of examples of urban traffic monitoring data collection program...
DOT National Transportation Integrated Search
2007-10-01
Accurate, complete, and timely traffic data is critical to the effective management of Arizonas highway system. Limitations in current traffic monitoring abilities are an ongoing challenge for the Arizona Department of Transportation (ADOT) and fo...
Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.
Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush
2016-08-01
This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.
New MPLS network management techniques based on adaptive learning.
Anjali, Tricha; Scoglio, Caterina; de Oliveira, Jaudelice Cavalcante
2005-09-01
The combined use of the differentiated services (DiffServ) and multiprotocol label switching (MPLS) technologies is envisioned to provide guaranteed quality of service (QoS) for multimedia traffic in IP networks, while effectively using network resources. These networks need to be managed adaptively to cope with the changing network conditions and provide satisfactory QoS. An efficient strategy is to map the traffic from different DiffServ classes of service on separate label switched paths (LSPs), which leads to distinct layers of MPLS networks corresponding to each DiffServ class. In this paper, three aspects of the management of such a layered MPLS network are discussed. In particular, an optimal technique for the setup of LSPs, capacity allocation of the LSPs and LSP routing are presented. The presented techniques are based on measurement of the network state to adapt the network configuration to changing traffic conditions.
Adaptive Bloom Filter: A Space-Efficient Counting Algorithm for Unpredictable Network Traffic
NASA Astrophysics Data System (ADS)
Matsumoto, Yoshihide; Hazeyama, Hiroaki; Kadobayashi, Youki
The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundamental modules in several network processing algorithms and applications such as route lookups, cache hits, packet classification, per-flow state management or network monitoring. BF is a simple space-efficient randomized data structure used to represent a data set in order to support membership queries. However, BF generates false positives, and cannot count the number of distinct elements. A counting Bloom Filter (CBF) can count the number of distinct elements, but CBF needs more space than BF. We propose an alternative data structure of CBF, and we called this structure an Adaptive Bloom Filter (ABF). Although ABF uses the same-sized bit-vector used in BF, the number of hash functions employed by ABF is dynamically changed to record the number of appearances of a each key element. Considering the hash collisions, the multiplicity of a each key element on ABF can be estimated from the number of hash functions used to decode the membership of the each key element. Although ABF can realize the same functionality as CBF, ABF requires the same memory size as BF. We describe the construction of ABF and IABF (Improved ABF), and provide a mathematical analysis and simulation using Zipf's distribution. Finally, we show that ABF can be used for an unpredictable data set such as real network traffic.
Spatially- explicit Fossil Fuel Carbon Dioxide Inventories for Transportation in the U.S.
NASA Astrophysics Data System (ADS)
Hutchins, M.; Gurney, K. R.
2016-12-01
The transportation sector is the second largest source of Fossil Fuel CO2 (FFCO2) emissions, and is unique in that federal, state, and municipal levels of government are all able to enact transportation policy. However, since data related to transportation activities are reported by multiple different government agencies, the data are not always consistent. As a result, the methods and data used to inventory and account for transportation related FFCO2 emissions have important implications for both science and policy. Aggregate estimates of transportation related FFCO2 emissions can be spatially distributed using traffic data, such as the Highway Performance Monitoring System (HPMS) Average Annual Daily Traffic (AADT). There are currently two datasets that estimate the spatial distribution of transportation related FFCO2 in the United States- Vulcan 3.0 and the Database of Road Transportation Emissions (DARTE). Both datasets are at 1 km resolution, for the year 2011, and utilize HPMS AADT traffic data. However, Vulcan 3.0 and DARTE spatially distribute emissions using different methods and inputs, resulting in a number of differences. Vulcan 3.0 and DARTE estimate national transportation related FFCO2 emissions within 2.5% of each other, with more significant differences at the county and state level. The differences are most notable in urban versus rural regions, and for specific road classes. The origin of these differences are explored in depth to understand the implication of using specific data sources, such as the National Emissions Inventory and other aggregate transportation statistics from the Federal Highway Administration (FHWA). In addition to comparing Vulcan 3.0 and DARTE to each other, the results from both data sets are compared to independent traffic volume measurements acquired from the FHWA Continuous Count Station (CCS) network. The CCS records hourly traffic counts at fixed locations in space throughout the U.S. We calculate transportation related FFCO2 emissions at a CCS stations using fuel specific emissions factors combined with the raw traffic counts. The CCS network provides a unique opportunity to compare spatially explicit, "bottom-up" models of transportation related FFCO2 emissions to measured traffic volume at over 300 specific locations.
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-01-01
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
Quantification of Road Network Vulnerability and Traffic Impacts to Regional Landslide Hazards.
NASA Astrophysics Data System (ADS)
Postance, Benjamin; Hillier, John; Dixon, Neil; Dijkstra, Tom
2015-04-01
Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 - 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards.
Traffic management simulation development : summary.
DOT National Transportation Integrated Search
2011-01-01
Increasingly, Florida traffic is monitored electronically by components of the Intelligent Traffic System (ITS), which send data to regional traffic management centers and assist management of traffic flows and incident response using software called...
Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network
NASA Astrophysics Data System (ADS)
Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.
2016-12-01
City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.
NASA Technical Reports Server (NTRS)
Foytik, Peter; Robinson, Mike
2010-01-01
As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.
Traffic off-balancing algorithm for energy efficient networks
NASA Astrophysics Data System (ADS)
Kim, Junhyuk; Lee, Chankyun; Rhee, June-Koo Kevin
2011-12-01
Physical layer of high-end network system uses multiple interface arrays. Under the load-balancing perspective, light load can be distributed to multiple interfaces. However, it can cause energy inefficiency in terms of the number of poor utilization interfaces. To tackle this energy inefficiency, traffic off-balancing algorithm for traffic adaptive interface sleep/awake is investigated. As a reference model, 40G/100G Ethernet is investigated. We report that suggested algorithm can achieve energy efficiency while satisfying traffic transmission requirement.
40 CFR 52.1164 - Localized high concentrations-carbon monoxide.
Code of Federal Regulations, 2010 CFR
2010-07-01
... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...
40 CFR 52.1164 - Localized high concentrations-carbon monoxide.
Code of Federal Regulations, 2014 CFR
2014-07-01
... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...
40 CFR 52.1164 - Localized high concentrations-carbon monoxide.
Code of Federal Regulations, 2013 CFR
2013-07-01
... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...
40 CFR 52.1164 - Localized high concentrations-carbon monoxide.
Code of Federal Regulations, 2011 CFR
2011-07-01
... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...
40 CFR 52.1164 - Localized high concentrations-carbon monoxide.
Code of Federal Regulations, 2012 CFR
2012-07-01
... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...
Carvalho-Oliveira, Regiani; Amato-Lourenço, Luís F; Moreira, Tiana C L; Silva, Douglas R Rocha; Vieira, Bruna D; Mauad, Thais; Saiki, Mitiko; Saldiva, Paulo H Nascimento
2017-02-01
The majority of epidemiological studies correlate the cardiorespiratory effects of air pollution exposure by considering the concentrations of pollutants measured from conventional monitoring networks. The conventional air quality monitoring methods are expensive, and their data are insufficient for providing good spatial resolution. We hypothesized that bioassays using plants could effectively determine pollutant gradients, thus helping to assess the risks associated with air pollution exposure. The study regions were determined from different prevalent respiratory death distributions in the Sao Paulo municipality. Samples of tree flower buds were collected from twelve sites in four regional districts. The genotoxic effects caused by air pollution were tested through a pollen abortion bioassay. Elements derived from vehicular traffic that accumulated in tree barks were determined using energy-dispersive X-ray fluorescence spectrometry (EDXRF). Mortality data were collected from the mortality information program of Sao Paulo City. Principal component analysis (PCA) was applied to the concentrations of elements accumulated in tree barks. Pearson correlation and exponential regression were performed considering the elements, pollen abortion rates and mortality data. PCA identified five factors, of which four represented elements related to vehicular traffic. The elements Al, S, Fe, Mn, Cu, and Zn showed a strong correlation with mortality rates (R 2 >0.87) and pollen abortion rates (R 2 >0.82). These results demonstrate that tree barks and pollen abortion rates allow for correlations between vehicular traffic emissions and associated outcomes such as genotoxic effects and mortality data. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cross-layer model design in wireless ad hoc networks for the Internet of Things.
Yang, Xin; Wang, Ling; Xie, Jian; Zhang, Zhaolin
2018-01-01
Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods.
Cross-layer model design in wireless ad hoc networks for the Internet of Things
Wang, Ling; Xie, Jian; Zhang, Zhaolin
2018-01-01
Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods. PMID:29734355
Designing Two-Layer Optical Networks with Statistical Multiplexing
NASA Astrophysics Data System (ADS)
Addis, B.; Capone, A.; Carello, G.; Malucelli, F.; Fumagalli, M.; Pedrin Elli, E.
The possibility of adding multi-protocol label switching (MPLS) support to transport networks is considered an important opportunity by telecom carriers that want to add packet services and applications to their networks. However, the question that arises is whether it is suitable to have MPLS nodes just at the edge of the network to collect packet traffic from users, or also to introduce MPLS facilities on a subset of the core nodes in order to exploit packet switching flexibility and multiplexing, thus providing induction of a better bandwidth allocation. In this article, we address this complex decisional problem with the support of a mathematical programming approach. We consider two-layer networks where MPLS is overlaid on top of transport networks-synchronous digital hierarchy (SDH) or wavelength division multiplexing (WDM)-depending on the required link speed. The discussions' decisions take into account the trade-off between the cost of adding MPLS support in the core nodes and the savings in the link bandwidth allocation due to the statistical multiplexing and the traffic grooming effects induced by MPLS nodes. The traffic matrix specifies for each point-to-point request a pair of values: a mean traffic value and an additional one. Using this traffic model, the effect of statistical multiplexing on a link allows the allocation of a capacity equal to the sum of all the mean values of the traffic demands routed on the link and only the highest additional one. The proposed approach is suitable to solve real instances in reasonable time.
Massively parallel processor networks with optical express channels
Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.
1999-08-24
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.
NASA Astrophysics Data System (ADS)
Vîlcan, A.; Neagu, E.; Badarau Suster, H.; Boroiu, A. A.
2017-10-01
Road traffic congestion has become a daily phenomenon in the central area of Pitesti in the peak traffic periods. In order to achieve the mobility plan of Pitesti, an important stage is the diagnostic analysis of the road traffic. For this purpose, the urban road network was formalized through a graph containing the most important 40 intersections and traffic measurements were made at all these intersections and on the main roads connecting the peri-urban area. The data obtained by traffic macrosimulation confirmed the overloading of the street network during peak traffic hours and the analyzes made for various road traffic organization scenarios have shown that there are sustainable solutions for urban mobility only if the road network is fundamentally reconfigured (a belt outside the city and a median ring). Thus, the necessity of realizing the road passage in the Prundu neighbourhood and the finishing of the city belt by realizing the “detour West” of the city is argued. The importance of the work is that it brings scientific arguments for the realization of these road infrastructure projects, integrated in the urban mobility plan, which will base the development strategy of the Pitesti municipality.
Massively parallel processor networks with optical express channels
Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.
1999-01-01
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.
The CARFAX road traffic information system
NASA Astrophysics Data System (ADS)
Sandell, R. S.
1984-02-01
A description of the development work and field trials which led to the completion of the dedicated traffic information service "CARFAX' is presented. The system employs a single medium frequency channel, and involves a network of low powered transmitters that operate in time division multiplex to provide traffic announcements. A description of the network distribution, equipment test, results and future system utilization is included.
Best response game of traffic on road network of non-signalized intersections
NASA Astrophysics Data System (ADS)
Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying
2018-01-01
This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.
DOT National Transportation Integrated Search
2008-08-01
Report Abstract: : The purpose of this guide is to aid the Texas Department of Transportation (TxDOT), Metropolitan Planning Organizations (MPO), and other state and local agencies to develop an effective traffic monitoring system for new major traff...
DOT National Transportation Integrated Search
2009-11-01
One objective of statewide traffic monitoring : programs is to accurately estimate the Annual : Average Daily Traffic (AADT) for many roadway : segments within the state. The majority of the : departments of transportation (DOT) in the United : State...
Flow-aggregated traffic-driven label mapping in label-switching networks
NASA Astrophysics Data System (ADS)
Nagami, Kenichi; Katsube, Yasuhiro; Esaki, Hiroshi; Nakamura, Osamu
1998-12-01
Label switching technology enables high performance, flexible, layer-3 packet forwarding based on the fixed length label information mapped to the layer-3 packet stream. A Label Switching Router (LSR) forwards layer-3 packets based on their label information mapped to the layer-3 address information as well as their layer-3 address information. This paper evaluates the required number of labels under traffic-driven label mapping policy using the real backbone traffic traces. The evaluation shows that the label mapping policy requires a large number of labels. In order to reduce the required number of labels, we propose a label mapping policy which is a traffic-driven label mapping for the traffic toward the same destination network. The evaluation shows that the proposed label mapping policy requires only about one tenth as many labels compared with the traffic-driven label mapping for the host-pair packet stream,and the topology-driven label mapping for the destination network packet stream.
Game Theoretic, Multi-agent Approach to Network Traffic Monitoring
2012-01-16
cases. That is why the symmetrized form of Kullback - Leibler divergence is often used Dskl = Dkl(P‖Q) +Dkl(Q‖P ) (3.9) We use a similar metric. If both...as a sequence of single-stage games with no transfer of information between the stages. This model is used as a formalism for the regret minimization...content of the transmitted information , but use the statistics (Fig. 1.1) in the NetFlow/IPFIX format [15, 14] to build, maintain and combine behav
NASA Astrophysics Data System (ADS)
Glamočanin, D.
2017-05-01
In order to maintain the continuity of the telecom operators’ network construction, while monitoring development needs, increasing customers’ demands and application of technological improvements, it is necessary to migrate optical transport core network to the next generation networks - Carrier Grade Ethernet Optical Transport Network (OTN CE). The primary objective of OTN CE is to realize an environment that is based solely on the switching in the optical domain, i.e. the realization of transparent optical networks and optical switching to the second layer of ISO / OSI model. The realization of such a network provides opportunities for further development of existing, but also technologically more demanding, new services. It is also a prerequisite to provide higher scalability, reliability, security and quality of QoS service, as well as prerequisites for the establishment of SLA (Service Level Agreement) for existing services, especially traffic in real time. This study aims to clarify the proposed model, which has the potential to be eventually adjusted in accordance with new scientific knowledge in this field as well as market requirements.
Adding signals to coordinated traffic signal systems.
DOT National Transportation Integrated Search
1983-08-01
The purpose of this research was to investigate the effect of adding or : removing traffic signals within a coordinated, signal-controlled street network. : The report includes a discussion of coordinated signal systems; arterial street : network con...
SCADA Protocol Anomaly Detection Utilizing Compression (SPADUC) 2013
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gordon Rueff; Lyle Roybal; Denis Vollmer
2013-01-01
There is a significant need to protect the nation’s energy infrastructures from malicious actors using cyber methods. Supervisory, Control, and Data Acquisition (SCADA) systems may be vulnerable due to the insufficient security implemented during the design and deployment of these control systems. This is particularly true in older legacy SCADA systems that are still commonly in use. The purpose of INL’s research on the SCADA Protocol Anomaly Detection Utilizing Compression (SPADUC) project was to determine if and how data compression techniques could be used to identify and protect SCADA systems from cyber attacks. Initially, the concept was centered on howmore » to train a compression algorithm to recognize normal control system traffic versus hostile network traffic. Because large portions of the TCP/IP message traffic (called packets) are repetitive, the concept of using compression techniques to differentiate “non-normal” traffic was proposed. In this manner, malicious SCADA traffic could be identified at the packet level prior to completing its payload. Previous research has shown that SCADA network traffic has traits desirable for compression analysis. This work investigated three different approaches to identify malicious SCADA network traffic using compression techniques. The preliminary analyses and results presented herein are clearly able to differentiate normal from malicious network traffic at the packet level at a very high confidence level for the conditions tested. Additionally, the master dictionary approach used in this research appears to initially provide a meaningful way to categorize and compare packets within a communication channel.« less
NASA Astrophysics Data System (ADS)
Nadarajah, Nishaanthan; Attygalle, Manik; Wong, Elaine; Nirmalathas, Ampalavanapillai
2005-10-01
This paper proposes two novel optical layer schemes for intercommunication between customers in a passive optical network (PON). The proposed schemes use radio frequency (RF) subcarrier multiplexed transmission for intercommunication between customers in conjunction with upstream access to the central office (CO) at baseband. One scheme employs a narrowband fiber Bragg grating (FBG) placed close to the star coupler in the feeder fiber of the PON, while the other uses an additional short-length distribution fiber from the star coupler to each customer unit for the redirection of customer traffic. In both schemes, only one optical transmitter is required at each optical network unit (ONU) for the transmission of customer traffic and upstream access traffic. Moreover, downstream bandwidth is not consumed by customer traffic unlike in previously reported techniques. The authors experimentally verify the feasibility of both schemes with 1.25 Gb/s upstream baseband transmission to the CO and 155 Mb/s customer data transmission on the RF carrier. The experimental results obtained from both schemes are compared, and the power budgets are calculated to analyze the scalability of each scheme. Further, the proposed schemes were discussed in terms of upgradability of the transmission bit rates for the upstream access traffic, bandwidth requirements at the customer premises, dispersion tolerance, and stability issues for the practical implementations of the network.
The INTELSAT VI SSTDMA network diagnostic system
NASA Astrophysics Data System (ADS)
Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.
The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.
Radiation detection and situation management by distributed sensor networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jan, Frigo; Mielke, Angela; Cai, D Michael
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 detectorsmore » 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.« less
Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model
NASA Astrophysics Data System (ADS)
Lawniczak, A. T.; Tang, X.
2006-05-01
The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.
NASA Astrophysics Data System (ADS)
Radev, Dimitar; Lokshina, Izabella
2010-11-01
The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
Prediction based active ramp metering control strategy with mobility and safety assessment
NASA Astrophysics Data System (ADS)
Fang, Jie; Tu, Lili
2018-04-01
Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.
Health monitoring of Binzhou Yellow River highway bridge using fiber Bragg gratings
NASA Astrophysics Data System (ADS)
Ou, Jinping; Zhao, Xuefeng; Li, Hui; Zhou, Zhi; Zhang, Zhichun; Wang, Chuan
2005-05-01
Binzhou yellow river Highway Bridge with 300 meter span and 768 meter length is located in the Shandong province of China and is the first cable stayed bridge with three towers along the yellow river, one of the biggest rivers in China. In order to monitoring the strain and temperature of the bridge and evaluate the health condition, one fiber Bragg grating sensing network consists of about one hundred and thirty FBG sensors mounted in 31 monitoring sections respectively, had been built during three years time. Signal cables of sensors were led to central control room located near the main tower. One four-channel FBG interrogator was used to read the wavelengths from all the sensors, associated with four computer-controlled optic switches connected to each channel. One program was written to control the interrogator and optic switches simultaneously, and ensure signal input precisely. The progress of the monitoring can be controlled through the internet. The sensors embedded were mainly used to monitor the strain and temperature of the steel cable and reinforced concrete beam. PE jacket opening embedding technique of steel cable had been developed to embed FBG sensors safely, and ensure the reliability of the steel cable opened at the same time. Data obtained during the load test can show the strain and temperature status of elements were in good condition. The data obtained via internet since the bridge's opening to traffic shown the bridge under various load such as traffic load, wind load were in good condition.
Oscillations in interconnected complex networks under intentional attack
NASA Astrophysics Data System (ADS)
Zhang, Wen-Ping; Xia, Yongxiang; Tan, Fei
2016-01-01
Many real-world networks are interconnected with each other. In this paper, we study the traffic dynamics in interconnected complex networks under an intentional attack. We find that with the shortest time delay routing strategy, the traffic dynamics can show the stable state, periodic, quasi-periodic and chaotic oscillations, when the capacity redundancy parameter changes. Moreover, compared with isolated complex networks, oscillations always take place in interconnected networks more easily. Thirdly, in interconnected networks, oscillations are affected strongly by the coupling probability and coupling preference.
Integrating Network Management for Cloud Computing Services
2015-06-01
abstraction and system design. In this dissertation, we make three major contributions. We rst propose to consolidate the tra c and infrastructure management...abstraction and system design. In this dissertation, we make three major contributions. We first propose to consolidate the traffic and infrastructure ...1.3.1 Safe Datacenter Traffic/ Infrastructure Management . . . . . . 9 1.3.2 End-host/Network Cooperative Traffic Management . . . . . . 10 1.3.3 Direct
On the ability of consumer electronics microphones for environmental noise monitoring.
Van Renterghem, Timothy; Thomas, Pieter; Dominguez, Frederico; Dauwe, Samuel; Touhafi, Abdellah; Dhoedt, Bart; Botteldooren, Dick
2011-03-01
The massive production of microphones for consumer electronics, and the shift from dedicated processing hardware to PC-based systems, opens the way to build affordable, extensive noise measurement networks. Applications include e.g. noise limit and urban soundscape monitoring, and validation of calculated noise maps. Microphones are the critical components of such a network. Therefore, in a first step, some basic characteristics of 8 microphones, distributed over a wide range of price classes, were measured in a standardized way in an anechoic chamber. In a next step, a thorough evaluation was made of the ability of these microphones to be used for environmental noise monitoring. This was done during a continuous, half-year lasting outdoor experiment, characterized by a wide variety of meteorological conditions. While some microphones failed during the course of this test, it was shown that it is possible to identify cheap microphones that highly correlate to the reference microphone during the full test period. When the deviations are expressed in total A-weighted (road traffic) noise levels, values of less than 1 dBA are obtained, in excess to the deviation amongst reference microphones themselves.
Coexistence of ZigBee-Based WBAN and WiFi for Health Telemonitoring Systems.
Kim, Yena; Lee, SeungSeob; Lee, SuKyoung
2016-01-01
The development of telemonitoring via wireless body area networks (WBANs) is an evolving direction in personalized medicine and home-based mobile health. A WBAN consists of small, intelligent medical sensors which collect physiological parameters such as electrocardiogram, electroencephalography, and blood pressure. The recorded physiological signals are sent to a coordinator via wireless technologies, and are then transmitted to a healthcare monitoring center. One of the most widely used wireless technologies in WBANs is ZigBee because it is targeted at applications that require a low data rate and long battery life. However, ZigBee-based WBANs face severe interference problems in the presence of WiFi networks. This problem is caused by the fact that most ZigBee channels overlap with WiFi channels, severely affecting the ability of healthcare monitoring systems to guarantee reliable delivery of physiological signals. To solve this problem, we have developed an algorithm that controls the load in WiFi networks to guarantee the delay requirement for physiological signals, especially for emergency messages, in environments with coexistence of ZigBee-based WBAN and WiFi. Since WiFi applications generate traffic with different delay requirements, we focus only on WiFi traffic that does not have stringent timing requirements. In this paper, therefore, we propose an adaptive load control algorithm for ZigBee-based WBAN/WiFi coexistence environments, with the aim of guaranteeing that the delay experienced by ZigBee sensors does not exceed a maximally tolerable period of time. Simulation results show that our proposed algorithm guarantees the delay performance of ZigBee-based WBANs by mitigating the effects of WiFi interference in various scenarios.
A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.
Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming
2015-01-01
Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.
Achieving QoS for TCP Traffic in Satellite Networks with Differentiated Services
NASA Technical Reports Server (NTRS)
Durresi, Arjan; Kota, Sastri; Goyal, Mukul; Jain, Raj; Bharani, Venkata
2001-01-01
Satellite networks play an indispensable role in providing global Internet access and electronic connectivity. To achieve such a global communications, provisioning of quality of service (QoS) within the advanced satellite systems is the main requirement. One of the key mechanisms of implementing the quality of service is traffic management. Traffic management becomes a crucial factor in the case of satellite network because of the limited availability of their resources. Currently, Internet Protocol (IP) only has minimal traffic management capabilities and provides best effort services. In this paper, we presented a broadband satellite network QoS model and simulated performance results. In particular, we discussed the TCP flow aggregates performance for their good behavior in the presence of competing UDP flow aggregates in the same assured forwarding. We identified several factors that affect the performance in the mixed environments and quantified their effects using a full factorial design of experiment methodology.
Energy conservation in ad hoc multimedia networks using traffic-shaping mechanisms
NASA Astrophysics Data System (ADS)
Chandra, Surendar
2003-12-01
In this work, we explore network traffic shaping mechanisms that deliver packets at pre-determined intervals; allowing the network interface to transition to a lower power consuming sleep state. We focus our efforts on commodity devices, IEEE 802.11b ad hoc mode and popular streaming formats. We argue that factors such as the lack of scheduling clock phase synchronization among the participants and scheduling delays introduced by back ground tasks affect the potential energy savings. Increasing the periodic transmission delays to transmit data infrequently can offset some of these effects at the expense of flooding the wireless channel for longer periods of time; potentially increasing the time to acquire the channel for non-multimedia traffic. Buffering mechanisms built into media browsers can mitigate the effects of these added delays from being mis-interpreted as network congestion. We show that practical implementations of such traffic shaping mechanisms can offer significant energy savings.
Satellite ATM Networks: Architectures and Guidelines Developed
NASA Technical Reports Server (NTRS)
vonDeak, Thomas C.; Yegendu, Ferit
1999-01-01
An important element of satellite-supported asynchronous transfer mode (ATM) networking will involve support for the routing and rerouting of active connections. Work published under the auspices of the Telecommunications Industry Association (http://www.tiaonline.org), describes basic architectures and routing protocol issues for satellite ATM (SATATM) networks. The architectures and issues identified will serve as a basis for further development of technical specifications for these SATATM networks. Three ATM network architectures for bent pipe satellites and three ATM network architectures for satellites with onboard ATM switches were developed. The architectures differ from one another in terms of required level of mobility, supported data rates, supported terrestrial interfaces, and onboard processing and switching requirements. The documentation addresses low-, middle-, and geosynchronous-Earth-orbit satellite configurations. The satellite environment may require real-time routing to support the mobility of end devices and nodes of the ATM network itself. This requires the network to be able to reroute active circuits in real time. In addition to supporting mobility, rerouting can also be used to (1) optimize network routing, (2) respond to changing quality-of-service requirements, and (3) provide a fault tolerance mechanism. Traffic management and control functions are necessary in ATM to ensure that the quality-of-service requirements associated with each connection are not violated and also to provide flow and congestion control functions. Functions related to traffic management were identified and described. Most of these traffic management functions will be supported by on-ground ATM switches, but in a hybrid terrestrial-satellite ATM network, some of the traffic management functions may have to be supported by the onboard satellite ATM switch. Future work is planned to examine the tradeoffs of placing traffic management functions onboard a satellite as opposed to implementing those functions at the Earth station components.
NASA Astrophysics Data System (ADS)
Cao, Xiaojun; Anand, Vishal; Qiao, Chunming
2006-12-01
Optical networks using wavelength-division multiplexing (WDM) are the foremost solution to the ever-increasing traffic in the Internet backbone. Rapid advances in WDM technology will enable each fiber to carry hundreds or even a thousand wavelengths (using dense-WDM, or DWDM, and ultra-DWDM) of traffic. This, coupled with worldwide fiber deployment, will bring about a tremendous increase in the size of the optical cross-connects, i.e., the number of ports of the wavelength switching elements. Waveband switching (WBS), wherein wavelengths are grouped into bands and switched as a single entity, can reduce the cost and control complexity of switching nodes by minimizing the port count. This paper presents a detailed study on recent advances and open research issues in WBS networks. In this study, we investigate in detail the architecture for various WBS cross-connects and compare them in terms of the number of ports and complexity and also in terms of how flexible they are in adjusting to dynamic traffic. We outline various techniques for grouping wavelengths into bands for the purpose of WBS and show how traditional wavelength routing is different from waveband routing and why techniques developed for wavelength-routed networks (WRNs) cannot be simply applied to WBS networks. We also outline how traffic grooming of subwavelength traffic can be done in WBS networks. In part II of this study [Cao , submitted to J. Opt. Netw.], we study the effect of wavelength conversion on the performance of WBS networks with reconfigurable MG-OXCs. We present an algorithm for waveband grouping in wavelength-convertible networks and evaluate its performance. We also investigate issues related to survivability in WBS networks and show how waveband and wavelength conversion can be used to recover from failures in WBS networks.
Analysis of the Chinese air route network as a complex network
NASA Astrophysics Data System (ADS)
Cai, Kai-Quan; Zhang, Jun; Du, Wen-Bo; Cao, Xian-Bin
2012-02-01
The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.
Cascade defense via routing in complex networks
NASA Astrophysics Data System (ADS)
Xu, Xiao-Lan; Du, Wen-Bo; Hong, Chen
2015-05-01
As the cascading failures in networked traffic systems are becoming more and more serious, research on cascade defense in complex networks has become a hotspot in recent years. In this paper, we propose a traffic-based cascading failure model, in which each packet in the network has its own source and destination. When cascade is triggered, packets will be redistributed according to a given routing strategy. Here, a global hybrid (GH) routing strategy, which uses the dynamic information of the queue length and the static information of nodes' degree, is proposed to defense the network cascade. Comparing GH strategy with the shortest path (SP) routing, efficient routing (ER) and global dynamic (GD) routing strategies, we found that GH strategy is more effective than other routing strategies in improving the network robustness against cascading failures. Our work provides insight into the robustness of networked traffic systems.
DOT National Transportation Integrated Search
2009-10-15
In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic c...
NASA Astrophysics Data System (ADS)
Wang, H. F.; Fratta, D.; Lancelle, C.; Ak, E. Ms; Lord, N. E.
2017-12-01
Monitoring traffic is important for many technical reasons. It allows for better design of future roads and assessment of the state of current roads. The number, size, weight, and speed of vehicles control deterioration rate. Also, real-time information supplies data to intelligent information systems to help control traffic. Recently there have been studies looking at monitoring traffic seismically as vibrations from traffic are not sensitive to weather and poor visibility. Furthermore, traffic noise can be used to image S-wave velocity distribution in the near surface by capturing and interpreting Rayleigh and Love waves (Nakata, 2016; Zeng et al. 2016). The capability of DAS for high spatial sampling (1 m), temporal sampling (up to 10 kHz), and distributed nature (tens of kilometers) allows for a closer look at the traffic as it passes and how the speed of the vehicle may change over the length of the array. The potential and difficulties of using DAS for these objectives were studied using two DAS arrays. One at Garner Valley in Southern California (a 700-meter array adjacent to CA Highway 74) and another in Brady Hot Springs, Nevada (an 8700-meter array adjacent to Interstate 80). These studies experimentally evaluated the use of DAS data for monitoring traffic and assessing the use of traffic vibration as non-localized sources for seismic imaging. DAS arrays should also be resilient to issues with lighting conditions that are problematic for video monitoring and it may be sensitive to the weight of a vehicle. This study along a major interstate provides a basis for examining DAS' potential and limitations as a key component of intelligent highway systems.
QoS-aware health monitoring system using cloud-based WBANs.
Almashaqbeh, Ghada; Hayajneh, Thaier; Vasilakos, Athanasios V; Mohd, Bassam J
2014-10-01
Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.
Propagation of Disturbances in Traffic Flow
DOT National Transportation Integrated Search
1977-09-01
The system-optimized static traffic-assignment problem in a freeway corridor network is the problem of choosing a distribution of vehicles in the network to minimize average travel time. It is of interest to know how sensitive the optimal steady-stat...
Performance Evaluation of FAST TCP Traffic-Flows in Multihomed MANETs
NASA Astrophysics Data System (ADS)
Mudassir, Mumajjed Ul; Akram, Adeel
In Mobile Ad hoc Networks (MANETs) an efficient communication protocol is required at the transport layer. Mobile nodes moving around will have temporary and rather short-lived connectivity with each other and the Internet, thus requiring efficient utilization of network resources. Moreover the problems arising due to high mobility, collision and congestion must also be considered. Multihoming allows higher reliability and enhancement of network throughput. FAST TCP is a new promising transport layer protocol developed for high-speed high-latency networks. In this paper, we have analyzed the performance of FAST TCP traffic flows in multihomed MANETs and compared it with standard TCP (TCP Reno) traffic flows in non-multihomed MANETs.
DOT National Transportation Integrated Search
2014-04-01
This report summarizes a project undertaken by the University of Illinois on behalf of the Illinois Department of : Transportation to evaluate a smartphone application called TrafficTurk for traffic safety and traffic monitoring : applications. Traff...
Comparative analysis of quantitative efficiency evaluation methods for transportation networks
He, Yuxin; Hong, Jian
2017-01-01
An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess’s Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified. PMID:28399165
Comparative analysis of quantitative efficiency evaluation methods for transportation networks.
He, Yuxin; Qin, Jin; Hong, Jian
2017-01-01
An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess's Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified.
Evaluation of traffic responsive control on the Reston Parkway arterial network.
DOT National Transportation Integrated Search
2009-01-01
Traffic responsive plan selection (TRPS) control is considered an effective operational mode in traffic signal systems. Its efficiency stems from the fact that it can capture variations in traffic patterns and switch timing plans based on existing tr...
Self-control of traffic lights and vehicle flows in urban road networks
NASA Astrophysics Data System (ADS)
Lämmer, Stefan; Helbing, Dirk
2008-04-01
Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.
NASA Astrophysics Data System (ADS)
Klumpp, Andreas; Ansel, Wolfgang; Klumpp, Gabriele; Breuer, Jörn; Vergne, Philippe; Sanz, María José; Rasmussen, Stine; Ro-Poulsen, Helge; Ribas Artola, Àngela; Peñuelas, Josep; He, Shang; Garrec, Jean Pierre; Calatayud, Vicent
Within a European biomonitoring programme, Italian ryegrass ( Lolium multiflorum Lam.) was employed as accumulative bioindicator of airborne trace elements (As, Cd, Cr, Cu, Fe, Ni, Pb, Sb, V, Zn) in urban agglomerations. Applying a highly standardised method, grass cultures were exposed for consecutive periods of four weeks each to ambient air at up to 100 sites in 11 cities during 2000-2002. Results of the 2001 exposure experiments revealed a clear differentiation of trace element pollution within and among local monitoring networks. Pollution was influenced particularly by traffic emissions. Especially Sb, Pb, Cr, Fe, and Cu exhibited a very uneven distribution within the municipal areas with strong accumulation in plants from traffic-exposed sites in the city centres and close to major roads, and moderate to low levels in plants exposed at suburban or rural sites. Accumulation of Ni and V was influenced by other emission sources. The biomonitoring sites located in Spanish city centres featured a much higher pollution load by trace elements than those in other cities of the network, confirming previously reported findings obtained by chemical analyses of dust deposition and aerosols. At some heavily-trafficked sites, legal thresholds for Cu, Pb, and V contents in foodstuff and animal feed were reached or even surpassed. The study confirmed that the standardised grass exposure is a useful and reliable tool to monitor and to assess environmental levels of potentially toxic compounds of particulate matter.
Sensor network based vehicle classification and license plate identification system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frigo, Janette Rose; Brennan, Sean M; Rosten, Edward J
Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform.more » Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.« less
Fog-Based Two-Phase Event Monitoring and Data Gathering in Vehicular Sensor Networks
Yang, Fan; Su, Jinsong; Zhou, Qifeng; Wang, Tian; Zhang, Lu; Xu, Yifan
2017-01-01
Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data. PMID:29286320
Estimated long-term outdoor air pollution concentrations in a cohort study
NASA Astrophysics Data System (ADS)
Beelen, Rob; Hoek, Gerard; Fischer, Paul; Brandt, Piet A. van den; Brunekreef, Bert
Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO 2), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO 2) was estimated. Exposure at each home address ( N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO 2, NO, BS, and SO 2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO 2, NO, BS and SO 2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.
TrafficGen Architecture Document
2016-01-01
sequence diagram ....................................................5 Fig. 5 TrafficGen traffic flows viewed in SDT3D...Scripts contain commands to have the network node listen on specific ports and flows describing the start time, stop time, and specific traffic ...arranged vertically and time presented horizontally. Individual traffic flows are represented by horizontal bars indicating the start time, stop time
Operations and safety of Super 2 corridors with higher volumes.
DOT National Transportation Integrated Search
2011-06-01
As traffic volumes increase, in both urban and rural areas, the demand on the highway network also : increases. Specifically, as rural traffic volumes rise in Texas, the pressure on the states network of two-lane : highways rises accordingly. Prev...
Forecasting the daily electricity consumption in the Moscow region using artificial neural networks
NASA Astrophysics Data System (ADS)
Ivanov, V. V.; Kryanev, A. V.; Osetrov, E. S.
2017-07-01
In [1] we demonstrated the possibility in principle for short-term forecasting of daily volumes of passenger traffic in the Moscow metro with the help of artificial neural networks. During training and predicting, a set of the factors that affect the daily passenger traffic in the subway is passed to the input of the neural network. One of these factors is the daily power consumption in the Moscow region. Therefore, to predict the volume of the passenger traffic in the subway, we must first to solve the problem of forecasting the daily energy consumption in the Moscow region.
2010-06-01
Ron’s Code 4 . . . . . . . . . . . . . . . . . . . 18 2.3.3 Virtual Private Network and Secure Shell Tunnels 19 2.3.4 Darknets ...created using Iodine. 2.2 Analyzing and Classifying Network Traffic Before the advent of Darknets and anonymizers like Tor (see Section 2.3), ana... darknets , and the Tor network. 2.3.1 Byte Padding. Byte padding is the most primitive obfuscation method used to hide payloads in network traffic. When byte
NASA Astrophysics Data System (ADS)
Lyu, H.; Ding, L.; Fan, H.; Meng, L.
2017-09-01
Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.
PLUS highway network analysis: Case of in-coming traffic burden in 2013
NASA Astrophysics Data System (ADS)
Asrah, Norhaidah Mohd; Djauhari, Maman Abdurachman; Mohamad, Ismail
2017-05-01
PLUS highway is the largest concessionary in Malaysia. The study on PLUS highway development, in order to overcome the demand for efficient road transportation, is crucial. If the highways have better interconnected network, it will help the economic activities such as trade to increase. If economic activities are increasing, the benefit will come to the people and state. In its turn, it will help the leaders to plan and conduct national development program. In this paper, network analysis approach will be used to study the in-coming traffic burden during the year of 2013. The highway network linking all the toll plazas is a dynamic network. The objective of this study is to learn and understand about highway network in terms of the in-coming traffic burden entering to each toll plazas along PLUS highway. For this purpose, the filtered network topology based on the forest of all possible minimum spanning trees is used. The in-coming traffic burden of a city is represented by the number of cars passing through the corresponding toll plaza. To interpret the filtered network, centrality measures such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality are used. An overall centrality will be proposed if those four measures are assumed to have the same role. Based on the results, some suggestions and recommendations for PLUS highway network development will be delivered to PLUS highway management.
NASA Astrophysics Data System (ADS)
He, Zhengbing; Chen, Bokui; Jia, Ning; Guan, Wei; Lin, Benchuan; Wang, Binghong
2014-12-01
To alleviate traffic congestion, a variety of route guidance strategies have been proposed for intelligent transportation systems. A number of strategies are introduced and investigated on a symmetric two-route traffic network over the past decade. To evaluate the strategies in a more general scenario, this paper conducts eight prevalent strategies on an asymmetric two-route traffic network with different slowdown behaviors on alternative routes. The results show that only mean velocity feedback strategy (MVFS) is able to equalize travel time, i.e. approximate user optimality (UO); while the others fail due to incapability of establishing relations between the feedback parameters and travel time. The paper helps better understand these strategies, and suggests MVFS if the authority intends to achieve user optimality.
State criminal justice telecommunications (STACOM). Volume 1: Executive summary
NASA Technical Reports Server (NTRS)
Fielding, J. E.; Frewing, H. K.; Lee, J. J.; Leflang, W. G.; Reilly, N. B.
1977-01-01
Techniques for identifying user requirements and network designs for criminal justice networks on a state wide basis are discussed. Topics covered include: methods for determining data required; data collection and survey; data organization procedures, and methods for forecasting network traffic volumes. Developed network design techniques center around a computerized topology program which enables the user to generate least cost network topologies that satisfy network traffic requirements, response time requirements and other specified functional requirements. The developed techniques were applied in Texas and Ohio, and results of these studies are presented.
Al-Shargabi, Mohammed A; Shaikh, Asadullah; Ismail, Abdulsamad S
2016-01-01
Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.
NASA Astrophysics Data System (ADS)
Peng, Chaorong; Chen, Chang Wen
2008-04-01
Malicious nodes are mounting increasingly sophisticated attacking operations on the Mobile Ad Hoc Networks (MANETs). This is mainly because the IP-based MANETs are vulnerable to attacks by various malicious nodes. However, the defense against malicious attack can be improved when a new layer of network architecture can be developed to separate true IP address from disclosing to the malicious nodes. In this paper, we propose a new algorithm to improve the defense against malicious attack (IDMA) that is based on a recently developed Assignment Router Identify Protocol (ARIP) for the clustering-based MANET management. In the ARIP protocol, we design the ARIP architecture based on the new Identity instead of the vulnerable IP addresses to provide the required security that is embedded seamlessly into the overall network architecture. We make full use of ARIP's special property to monitor gateway forward packets by Reply Request Route Packets (RREP) without additional intrusion detection layer. We name this new algorithm IDMA because of its inherent capability to improve the defense against malicious attacks. Through IDMA, a watching algorithm can be established so as to counterattack the malicious node in the routing path when it unusually drops up packets. We provide analysis examples for IDMA for the defense against a malicious node that disrupts the route discovery by impersonating the destination, or by responding with state of corrupted routing information, or by disseminating forged control traffic. The IDMA algorithm is able to counterattack the malicious node in the cases when the node lunch DoS attack by broadcast a large number of route requests, or make Target traffic congestion by delivering huge mount of data; or spoof the IP addresses and send forge packets with a fake ID to the same Target causing traffic congestion at that destination. We have implemented IDMA algorism using the GloMoSim simulator and have demonstrated its performance under a variety of operational conditions.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-31
... also claims that MSS networks provide the only means to create a next generation air traffic management..., articulated their plans to offer high-speed data services, especially in connection with terrestrial networks... claimed that MSS networks provide the only means to create a next generation air traffic management (ATM...
Distributed Traffic Control for Reduced Fuel Consumption and Travel Time in Transportation Networks
DOT National Transportation Integrated Search
2018-04-01
Current technology in traffic control is limited to a centralized approach that has not paid appropriate attention to efficiency of fuel consumption and is subject to the scale of transportation networks. This project proposes a transformative approa...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Masica, Ken
Additional challenges of implementing a BACnet network in a large campus environment are explored in this article: providing BACnet campus connectivity, protecting BACnet network traffic, and controlling the resulting broadcast traffic. An example of BACnet implementation is also presented, unifying concepts presented in this and Part One of the article.
Routing optimization in networks based on traffic gravitational field model
NASA Astrophysics Data System (ADS)
Liu, Longgeng; Luo, Guangchun
2017-04-01
For research on the gravitational field routing mechanism on complex networks, we further analyze the gravitational effect of paths. In this study, we introduce the concept of path confidence degree to evaluate the unblocked reliability of paths that it takes the traffic state of all nodes on the path into account from the overall. On the basis of this, we propose an improved gravitational field routing protocol considering all the nodes’ gravities on the path and the path confidence degree. In order to evaluate the transmission performance of the routing strategy, an order parameter is introduced to measure the network throughput by the critical value of phase transition from a free-flow phase to a jammed phase, and the betweenness centrality is used to evaluate the transmission performance and traffic congestion of the network. Simulation results show that compared with the shortest-path routing strategy and the previous gravitational field routing strategy, the proposed algorithm improves the network throughput considerably and effectively balances the traffic load within the network, and all nodes in the network are utilized high efficiently. As long as γ ≥ α, the transmission performance can reach the maximum and remains unchanged for different α and γ, which ensures that the proposed routing protocol is high efficient and stable.
Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations
NASA Technical Reports Server (NTRS)
Davis, Paul; Boisvert, Benjamin
2017-01-01
The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.
Hydrodynamically induced oscillations and traffic dynamics in 1D microfludic networks
NASA Astrophysics Data System (ADS)
Bartolo, Denis; Jeanneret, Raphael
2011-03-01
We report on the traffic dynamics of particles driven through a minimal microfluidic network. Even in the minimal network consisting in a single loop, the traffic dynamics has proven to yield complex temporal patterns, including periodic, multi-periodic or chaotic sequences. This complex dynamics arises from the strongly nonlinear hydrodynamic interactions between the particles, that takes place at a junction. To better understand the consequences of this nontrivial coupling, we combined theoretical, numerical and experimental efforts and solved the 3-body problem in a 1D loop network. This apparently simple dynamical system revealed a rich and unexpected dynamics, including coherent spontaneous oscillations along closed orbits. Striking similarities between Hamiltonian systems and this driven dissipative system will be explained.
Traffic routing for multicomputer networks with virtual cut-through capability
NASA Technical Reports Server (NTRS)
Kandlur, Dilip D.; Shin, Kang G.
1992-01-01
Consideration is given to the problem of selecting routes for interprocess communication in a network with virtual cut-through capability, while balancing the network load and minimizing the number of times that a message gets buffered. An approach is proposed that formulates the route selection problem as a minimization problem with a link cost function that depends upon the traffic through the link. The form of this cost function is derived using the probability of establishing a virtual cut-through route. The route selection problem is shown to be NP-hard, and an algorithm is developed to incrementally reduce the cost by rerouting the traffic. The performance of this algorithm is exemplified by two network topologies: the hypercube and the C-wrapped hexagonal mesh.
Monitoring Aircraft Motion at Airports by LIDAR
NASA Astrophysics Data System (ADS)
Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.
2016-06-01
Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.
Measurements and modelling of base station power consumption under real traffic loads.
Lorincz, Josip; Garma, Tonko; Petrovic, Goran
2012-01-01
Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.
Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †
Lorincz, Josip; Garma, Tonko; Petrovic, Goran
2012-01-01
Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026
Box, Simon
2014-01-01
Optimal switching of traffic lights on a network of junctions is a computationally intractable problem. In this research, road traffic networks containing signallized junctions are simulated. A computer game interface is used to enable a human ‘player’ to control the traffic light settings on the junctions within the simulation. A supervised learning approach, based on simple neural network classifiers can be used to capture human player's strategies in the game and thus develop a human-trained machine control (HuTMaC) system that approaches human levels of performance. Experiments conducted within the simulation compare the performance of HuTMaC to two well-established traffic-responsive control systems that are widely deployed in the developed world and also to a temporal difference learning-based control method. In all experiments, HuTMaC outperforms the other control methods in terms of average delay and variance over delay. The conclusion is that these results add weight to the suggestion that HuTMaC may be a viable alternative, or supplemental method, to approximate optimization for some practical engineering control problems where the optimal strategy is computationally intractable. PMID:26064570
Box, Simon
2014-12-01
Optimal switching of traffic lights on a network of junctions is a computationally intractable problem. In this research, road traffic networks containing signallized junctions are simulated. A computer game interface is used to enable a human 'player' to control the traffic light settings on the junctions within the simulation. A supervised learning approach, based on simple neural network classifiers can be used to capture human player's strategies in the game and thus develop a human-trained machine control (HuTMaC) system that approaches human levels of performance. Experiments conducted within the simulation compare the performance of HuTMaC to two well-established traffic-responsive control systems that are widely deployed in the developed world and also to a temporal difference learning-based control method. In all experiments, HuTMaC outperforms the other control methods in terms of average delay and variance over delay. The conclusion is that these results add weight to the suggestion that HuTMaC may be a viable alternative, or supplemental method, to approximate optimization for some practical engineering control problems where the optimal strategy is computationally intractable.
How Travel Demand Affects Detection of Non-Recurrent Traffic Congestion on Urban Road Networks
NASA Astrophysics Data System (ADS)
Anbaroglu, B.; Heydecker, B.; Cheng, T.
2016-06-01
Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London's urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.
Roads at risk - traffic detours from debris flows in southern Norway
NASA Astrophysics Data System (ADS)
Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.
2014-10-01
Globalization and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g., road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load expressed as vehicle kilometers because of debris-flow related road closures. We present two scenarios demonstrating the impact of debris flows on the road network, and quantify the associated path failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and northwestern part of the study area are associated with high link failure risk. Yet options for detours on major routes are manifold, and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying of speedy delivery of services and goods.
Roads at risk: traffic detours from debris flows in southern Norway
NASA Astrophysics Data System (ADS)
Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.
2015-05-01
Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.
GIS and Transportation Planning
DOT National Transportation Integrated Search
1998-09-16
Two main objectives of transportation planning are to simulate the current : traffic volume and to forecast the future traffic volume on a transportation : network. Traffic demand modeling typically consists of the following : tasks (1)defining traff...
DOT National Transportation Integrated Search
2010-10-25
Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...
A cost-effective traffic data collection system based on the iDEN mobile telecommunication network.
DOT National Transportation Integrated Search
2008-10-01
This report describes a cost-effective data collection system for Caltrans 170 traffic signal : controller. The data collection system is based on TCP/IP communication over existing : low-cost mobile communication networks and Motorola iDEN1 mobile...
Directing Traffic: Managing Internet Bandwidth Fairly
ERIC Educational Resources Information Center
Paine, Thomas A.; Griggs, Tyler J.
2008-01-01
Educational institutions today face budgetary restraints and scarce resources, complicating the decision of how to allot bandwidth for campus network users. Additionally, campus concerns over peer-to-peer networking (specifically outbound Internet traffic) have increased because of bandwidth and copyright issues. In this article, the authors…
A simple, effective media access protocol system for integrated, high data rate networks
NASA Technical Reports Server (NTRS)
Foudriat, E. C.; Maly, K.; Overstreet, C. M.; Khanna, S.; Zhang, L.
1992-01-01
The operation and performance of a dual media access protocol for integrated, gigabit networks are described. Unlike other dual protocols, each protocol supports a different class of traffic. The Carrier Sensed Multiple Access-Ring Network (CSMA/RN) protocol and the Circulating Reservation Packet (CRP) protocol support asynchronous and synchronous traffic, respectively. The two protocols operate with minimal impact upon each other. Performance information demonstrates that they support a complete range of integrated traffic loads, do not require call setup/termination or a special node for synchronous traffic control, and provide effective pre-use and recovery. The CRP also provides guaranteed access and fairness control for the asynchronous system. The paper demonstrates that the CSMA-CRP system fulfills many of the requirements for gigabit LAN-MAN networks most effectively and simply. To accomplish this, CSMA-CRP features are compared against similar ring and bus systems, such as Cambridge Fast Ring, Metaring, Cyclic Reservation Multiple Access, and Distributed Dual Queue Data Bus (DQDB).
Sniffer Channel Selection for Monitoring Wireless LANs
NASA Astrophysics Data System (ADS)
Song, Yuan; Chen, Xian; Kim, Yoo-Ah; Wang, Bing; Chen, Guanling
Wireless sniffers are often used to monitor APs in wireless LANs (WLANs) for network management, fault detection, traffic characterization, and optimizing deployment. It is cost effective to deploy single-radio sniffers that can monitor multiple nearby APs. However, since nearby APs often operate on orthogonal channels, a sniffer needs to switch among multiple channels to monitor its nearby APs. In this paper, we formulate and solve two optimization problems on sniffer channel selection. Both problems require that each AP be monitored by at least one sniffer. In addition, one optimization problem requires minimizing the maximum number of channels that a sniffer listens to, and the other requires minimizing the total number of channels that the sniffers listen to. We propose a novel LP-relaxation based algorithm, and two simple greedy heuristics for the above two optimization problems. Through simulation, we demonstrate that all the algorithms are effective in achieving their optimization goals, and the LP-based algorithm outperforms the greedy heuristics.
Did policies to abate atmospheric emissions from traffic have a positive effect in London?
Font, Anna; Fuller, Gary W
2016-11-01
A large number of policy initiatives are being taken at the European level, across the United Kingdom and in London to improve air quality and reduce population exposure to harmful pollutants from traffic emissions. Trends in roadside increments of nitrogen oxides (NO X ), nitrogen dioxide (NO 2 ), particulate matter (PM), black carbon (CBLK) and carbon dioxide (CO 2 ) were examined at 65 London monitoring sites for two periods of time: 2005-2009 and 2010-2014. Between 2005 and 2009 there was an overall increase in NO 2 reflecting the growing evidence of real world emissions from diesel vehicles. Conversely, NO 2 decreased by 10%·year -1 from 2010 onwards along with PM 2.5 (-28%·year -1 ) and black carbon (-11%·year -1 ). Downwards trends in air pollutants were not fully explained by changes in traffic counts therefore traffic exhaust emission abatement policies were proved to be successful in some locations. PM 10 concentrations showed no significant overall change suggesting an increase in coarse particles which offset the decrease in tailpipe emissions; this was especially the case on roads in outer London where an increase in the number of Heavy Good Vehicles (HGVs) was seen. The majority of roads with increasing NO X experienced an increase in buses and coaches. Changes in CO 2 from 2010 onwards did not match the downward predictions from reduced traffic flows and improved fleet efficiency. CO 2 increased along with increasing HGVs and buses. Polices to manage air pollution provided differential benefits across London's road network. To investigate this, k-means clustering technique was applied to group roads which behaved similarly in terms of trends to evaluate the effectiveness of policies to mitigate traffic emissions. This is the first time that London's roadside monitoring sites have been considered as a population rather than summarized as a mean behaviour only, allowing greater insight into the differential changes in air pollution abatement policies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
NASA Astrophysics Data System (ADS)
Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian
2008-04-01
Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.
Design Issues for Traffic Management for the ATM UBR + Service for TCP Over Satellite Networks
NASA Technical Reports Server (NTRS)
Jain, Raj
1999-01-01
This project was a comprehensive research program for developing techniques for improving the performance of Internet protocols over Asynchronous Transfer Mode (ATM) based satellite networks. Among the service categories provided by ATM networks, the most commonly used category for data traffic is the unspecified bit rate (UBR) service. UBR allows sources to send data into the network without any feedback control. The project resulted in the numerous ATM Forum contributions and papers.
Application of growing hierarchical SOM for visualisation of network forensics traffic data.
Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T
2012-08-01
Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.
Passive and Active Monitoring on a High Performance Research Network.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matthews, Warren
2001-05-01
The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10{sup 12}). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge hasmore » arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not!) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data.« less
NASA Technical Reports Server (NTRS)
1992-01-01
Mestech's X-15 "Eye in the Sky," a traffic monitoring system, incorporates NASA imaging and robotic vision technology. A camera or "sensor box" is mounted in a housing. The sensor detects vehicles approaching an intersection and sends the information to a computer, which controls the traffic light according to the traffic rate. Jet Propulsion Laboratory technical support packages aided in the company's development of the system. The X-15's "smart highway" can also be used to count vehicles on a highway and compute the number in each lane and their speeds, important information for freeway control engineers. Additional applications are in airport and railroad operations. The system is intended to replace loop-type traffic detectors.
NASA Astrophysics Data System (ADS)
Belloul, M.; Engl, W.; Colin, A.; Panizza, P.; Ajdari, A.
2009-05-01
By studying the repartition of monodisperse droplets at a simple T junction, we show that the traffic of discrete fluid systems in microfluidic networks results from two competing mechanisms, whose significance is driven by confinement. Traffic is dominated by collisions occurring at the junction for small droplets and by collective hydrodynamic feedback for large ones. For each mechanism, we present simple models in terms of the pertinent dimensionless parameters of the problem.
2017-09-01
unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber events, such as a...Furthermore, we identify unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber...2]. The applications build flow rules using network topology information provided by the control plane [1]. Since the control plane is able to
NASA Astrophysics Data System (ADS)
Jiang, Zhong-Yuan; Ma, Jian-Feng
Existing routing strategies such as the global dynamic routing [X. Ling, M. B. Hu, R. Jiang and Q. S. Wu, Phys. Rev. E 81, 016113 (2010)] can achieve very high traffic capacity at the cost of extremely long packet traveling delay. In many real complex networks, especially for real-time applications such as the instant communication software, extremely long packet traveling time is unacceptable. In this work, we propose to assign a finite Time-to-Live (TTL) parameter for each packet. To guarantee every packet to arrive at its destination within its TTL, we assume that a packet is retransmitted by its source once its TTL expires. We employ source routing mechanisms in the traffic model to avoid the routing-flaps induced by the global dynamic routing. We compose extensive simulations to verify our proposed mechanisms. With small TTL, the effects of packet retransmission on network traffic capacity are obvious, and the phase transition from flow free state to congested state occurs. For the purpose of reducing the computation frequency of the routing table, we employ a computing cycle Tc within which the routing table is recomputed once. The simulation results show that the traffic capacity decreases with increasing Tc. Our work provides a good insight into the understanding of effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks.
Inferring the background traffic arrival process in the Internet.
Hága, Péter; Csabai, István; Vattay, Gábor
2009-12-01
Phase transition has been found in many complex interactivity systems. Complex networks are not exception either but there are quite few real systems where we can directly understand the emergence of this nontrivial behavior from the microscopic view. In this paper, we present the emergence of the phase transition between the congested and uncongested phases of a network link. We demonstrate a method to infer the background traffic arrival process, which is one of the key state parameters of the Internet traffic. The traffic arrival process in the Internet has been investigated in several studies, since the recognition of its self-similar nature. The statistical properties of the traffic arrival process are very important since they are fundamental in modeling the dynamical behavior. Here, we demonstrate how the widely used packet train technique can be used to determine the main properties of the traffic arrival process. We show that the packet train dispersion is sensitive to the congestion on the network path. We introduce the packet train stretch as an order parameter to describe the phase transition between the congested and uncongested phases of the bottleneck link in the path. We find that the distribution of the background traffic arrival process can be determined from the average packet train dispersion at the critical point of the system.
Investigating the relationship between jobs-housing balance and traffic safety.
Xu, Chengcheng; Li, Haojie; Zhao, Jingya; Chen, Jun; Wang, Wei
2017-10-01
This study aimed to investigate the effects of jobs-housing balance on traffic safety. The crash, demographic characteristics, employment, road network, household characteristics and traffic data were collected from the Los Angeles in 2010. One-way ANOVA tests indicated that the jobs-housing ratio significantly affects traffic safety in terms of crash frequency at traffic analysis zone (TAZ). To quantify the safety impacts of jobs-housing balance, the semi-parametric geographically weighted Poisson regression (S-GWPR) was further used to link crash frequency at TAZ with jobs-housing ratio and other contributing factors. The S-GWPR provides better fitness to the data than do the generalized linear regression, as the S-GWPR accounts for the spatial heterogeneity. The S-GWPR results showed that the jobs-housing relationship has a significant association with crash frequency at TAZ when the factors of traffic, network, and household characteristics are controlled. Crash frequency at TAZ level increases with an increase in the jobs-housing ratio. To further investigate the interactive effects between jobs-housing ratio and other factors, a comparative analysis was conducted to compare the variable elasticities under different jobs-housing ratios. The results indicate considerable interactive effects that traffic conditions and road network characteristics have different effects on crash frequency under various jobs-housing ratios. Copyright © 2017 Elsevier Ltd. All rights reserved.
A new smart traffic monitoring method using embedded cement-based piezoelectric sensors
NASA Astrophysics Data System (ADS)
Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin
2015-02-01
Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h-1 to 70 km h-1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.
Fujita, Eric M; Campbell, David E; Arnott, W Patrick; Lau, Virginia; Martien, Philip T
2013-12-01
The Bay Area Air Quality Management District (BAAQMD) sponsored the West Oakland Monitoring Study (WOMS) to provide supplemental air quality monitoring that will be used by the BAAQMD to evaluate local-scale dispersion modeling of diesel emissions and other toxic air contaminants for the area within and around the Port of Oakland. The WOMS was conducted during two seasonal periods of 4 weeks in summer 2009 and winter 2009/2010. Monitoring data showed spatial patterns of pollutant concentrations that were generally consistent with proximity to vehicle traffic. Concentrations of directly emitted pollutants were highest on heavily traveled roads with consistently lower concentrations away from the roadways. Pollutants that have higher emission rates from diesel trucks (nitric oxide, black carbon) tended to exhibit sharper gradients than pollutants that are largely associated with gasoline vehicles, such as carbon monoxide and volatile organic compounds, including benzene, toluene, ethylbenzene, and xylenes (BTEX). BTEX concentrations in West Oakland were similar to those measured at the three air toxics monitoring network sites in the Bay Area (San Francisco, Fremont, and San Jose). Aldehyde levels were higher in Fremont and San Jose than in West Oakland, reflecting greater contributions from photo-oxidation of hydrocarbons downwind of the Bay Area. A 2005 modeling-based health risk assessment of diesel particulate matter concentrations is consistent with aerosol carbon concentrations measured during the WOMS after adjusting for recent mitigation measures and improved estimates of heavy-duty truck traffic volumes.
DOT National Transportation Integrated Search
2013-10-01
In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...
DOT National Transportation Integrated Search
1995-01-01
Prepared ca. 1995. This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) va...
Optimizing automatic traffic recorders network in Minnesota.
DOT National Transportation Integrated Search
2016-01-01
Accurate traffic counts are important for budgeting, traffic planning, and roadway design. With thousands of : centerline miles of roadways, it is not possible to install continuous counters at all locations of interest (e.g., : intersections). There...
DOT National Transportation Integrated Search
2012-05-01
Problem: : Most Intelligent Transportation System (ITS) applications require distributed : acquisition of various traffic metrics such as traffic speed, volume, and density. : The existing measurement technologies, such as inductive loops, infrared, ...
NASA Astrophysics Data System (ADS)
Schiavon, Marco; Redivo, Martina; Antonacci, Gianluca; Rada, Elena Cristina; Ragazzi, Marco; Zardi, Dino; Giovannini, Lorenzo
2015-11-01
Simulations of emission and dispersion of nitrogen oxides (NOx) are performed in an urban area of Verona (Italy), characterized by street canyons and typical sources of urban pollutants. Two dominant source categories are considered: road traffic and, as an element of novelty, domestic heaters. Also, to assess the impact of urban air pollution on human health and, in particular, the cancer risk, simulations of emission and dispersion of benzene are carried out. Emissions from road traffic are estimated by the COPERT 4 algorithm, whilst NOx emission factors from domestic heaters are retrieved by means of criteria provided in the technical literature. Then maps of the annual mean concentrations of NOx and benzene are calculated using the AUSTAL2000 dispersion model, considering both scenarios representing the current situation, and scenarios simulating the introduction of environmental strategies for air pollution mitigation. The simulations highlight potentially critical situations of human exposure that may not be detected by the conventional network of air quality monitoring stations. The proposed methodology provides a support for air quality policies, such as planning targeted measurement campaigns, re-locating monitoring stations and adopting measures in favour of better air quality in urban planning. In particular, the estimation of the induced cancer risk is an important starting point to conduct zoning analyses and to detect the areas where population is more directly exposed to potential risks for health.
Al-Shargabi, Mohammed A.; Ismail, Abdulsamad S.
2016-01-01
Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively. PMID:27583557
Capacity planning of link restorable optical networks under dynamic change of traffic
NASA Astrophysics Data System (ADS)
Ho, Kwok Shing; Cheung, Kwok Wai
2005-11-01
Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.
Communication efficiency and congestion of signal traffic in large-scale brain networks.
Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R
2014-01-01
The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.
Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks
Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R.
2014-01-01
The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a “rich club” of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication. PMID:24415931
Multilane Traffic Flow Modeling Using Cellular Automata Theory
NASA Astrophysics Data System (ADS)
Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina
2018-02-01
The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.
Traffic sign classification with dataset augmentation and convolutional neural network
NASA Astrophysics Data System (ADS)
Tang, Qing; Kurnianggoro, Laksono; Jo, Kang-Hyun
2018-04-01
This paper presents a method for traffic sign classification using a convolutional neural network (CNN). In this method, firstly we transfer a color image into grayscale, and then normalize it in the range (-1,1) as the preprocessing step. To increase robustness of classification model, we apply a dataset augmentation algorithm and create new images to train the model. To avoid overfitting, we utilize a dropout module before the last fully connection layer. To assess the performance of the proposed method, the German traffic sign recognition benchmark (GTSRB) dataset is utilized. Experimental results show that the method is effective in classifying traffic signs.
Improved Dynamic Lightpath Provisioning for Large Wavelength-Division Multiplexed Backbones
NASA Astrophysics Data System (ADS)
Kong, Huifang; Phillips, Chris
2007-07-01
Technology already exists that would allow future optical networks to support automatic lightpath configuration in response to dynamic traffic demands. Given appropriate commercial drivers, it is possible to foresee carrier network operators migrating away from semipermanent provisioning to enable on-demand short-duration communications. However, with traditional lightpath reservation protocols, a portion of the lightpath is idly held during the signaling propagation phase, which can significantly reduce the lightpath bandwidth efficiency in large wavelength-division multiplexed backbones. This paper proposes a prebooking mechanism to improve the lightpath efficiency over traditional reactive two-way reservation protocols, consequently liberating network resources to support higher traffic loads. The prebooking mechanism predicts the time when the traffic will appear at the optical cross connects, and intelligently schedules the lightpath components such that resources are only consumed as necessary. We describe the proposed signaling procedure for both centralized and distributed control planes and analyze its performance. This paper also investigates the aggregated flow length characteristics with the self-similar incident traffic and examines the effects of traffic prediction on the blocking probability as well as the ability to support latency sensitive traffic in a wide-area environment.
2015-08-01
Experimental environment 5 Table 1 Hardware specifications Name Manufacture Model CPU Memory Hard Drive IP Address Bilbo Dell PowerEdge R610 Intel...10 we replayed the same hour of network traffic from the CDX 20093 that we used in our theoretical2 exploration to show the impact of our packet... replay the traffic at arbitrary speeds. Table 3 lists the speed multiplier that we used and the packet loss we observed. Table 3 Network packet loss
Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju
2014-03-21
A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated.
Cluster categorization of urban roads to optimize their noise monitoring.
Zambon, G; Benocci, R; Brambilla, G
2016-01-01
Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.
Space evolution model and empirical analysis of an urban public transport network
NASA Astrophysics Data System (ADS)
Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing
2012-07-01
This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.
Evaluation Study of a Wireless Multimedia Traffic-Oriented Network Model
NASA Astrophysics Data System (ADS)
Vasiliadis, D. C.; Rizos, G. E.; Vassilakis, C.
2008-11-01
In this paper, a wireless multimedia traffic-oriented network scheme over a fourth generation system (4-G) is presented and analyzed. We conducted an extensive evaluation study for various mobility configurations in order to incorporate the behavior of the IEEE 802.11b standard over a test-bed wireless multimedia network model. In this context, the Quality of Services (QoS) over this network is vital for providing a reliable high-bandwidth platform for data-intensive sources like video streaming. Therefore, the main issues concerned in terms of QoS were the metrics for bandwidth of both dropped and lost packets and their mean packet delay under various traffic conditions. Finally, we used a generic distance-vector routing protocol which was based on an implementation of Distributed Bellman-Ford algorithm. The performance of the test-bed network model has been evaluated by using the simulation environment of NS-2.
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.
Providing end-to-end QoS for multimedia applications in 3G wireless networks
NASA Astrophysics Data System (ADS)
Guo, Katherine; Rangarajan, Samapth; Siddiqui, M. A.; Paul, Sanjoy
2003-11-01
As the usage of wireless packet data services increases, wireless carriers today are faced with the challenge of offering multimedia applications with QoS requirements within current 3G data networks. End-to-end QoS requires support at the application, network, link and medium access control (MAC) layers. We discuss existing CDMA2000 network architecture and show its shortcomings that prevent supporting multiple classes of traffic at the Radio Access Network (RAN). We then propose changes in RAN within the standards framework that enable support for multiple traffic classes. In addition, we discuss how Session Initiation Protocol (SIP) can be augmented with QoS signaling for supporting end-to-end QoS. We also review state of the art scheduling algorithms at the base station and provide possible extensions to these algorithms to support different classes of traffic as well as different classes of users.
DOT National Transportation Integrated Search
2009-10-15
This research seeks to explore vehicle-to-vehicle information networks to understand the interplay : between the information communicated and traffic conditions on the network. A longer-term goal is to : develop a decision support tool for processing...
Campus Challenge - Part 2: Benefits and Challenges of BACnet
Masica, Ken
2016-01-15
Additional challenges of implementing a BACnet network in a large campus environment are explored in this article: providing BACnet campus connectivity, protecting BACnet network traffic, and controlling the resulting broadcast traffic. An example of BACnet implementation is also presented, unifying concepts presented in this and Part One of the article.
The importance of antipersistence for traffic jams
NASA Astrophysics Data System (ADS)
Krause, Sebastian M.; Habel, Lars; Guhr, Thomas; Schreckenberg, Michael
2017-05-01
Universal characteristics of road networks and traffic patterns can help to forecast and control traffic congestion. The antipersistence of traffic flow time series has been found for many data sets, but its relevance for congestion has been overseen. Based on empirical data from motorways in Germany, we study how antipersistence of traffic flow time-series impacts the duration of traffic congestion on a wide range of time scales. We find a large number of short-lasting traffic jams, which implies a large risk for rear-end collisions.
Implementation of aerial LiDAR technology to update highway feature inventory.
DOT National Transportation Integrated Search
2016-12-01
Highway assets, including traffic signs, traffic signals, light poles, and guardrails, are important components of : transportation networks. They guide, warn and protect drivers, and regulate traffic. To manage and maintain the : regular operation o...
A research of the community’s opening to the outside world
NASA Astrophysics Data System (ADS)
Xu, Lan; Liu, Xiangzhuo
2017-03-01
Closed residential areas, called community, the traffic network and result in various degrees of traffic congestion such as amputating, dead ends and T-shaped roads. In order to reveal the mechanism of the congestion, establish an effective evaluation index system and finally provide theoretical basis for the study of traffic congestion, we have done researches on factors for traffic congestion and have established a scientific evaluation index system combining experiences home and abroad, based on domestic congestion status. Firstly, we analyse the traffic network as the entry point, and then establish the evaluation model of road capacity with the method of AHP index system. Secondly, we divide the condition of urban congestion into 5 levels from congestion to smoothness. Besides, with VISSIM software, simulations about traffic capacity before and after community opening are carried out. Finally, we provide forward reasonable suggestions upon the combination of models and reality.
TTEthernet for Integrated Spacecraft Networks
NASA Technical Reports Server (NTRS)
Loveless, Andrew
2015-01-01
Aerospace projects have traditionally employed federated avionics architectures, in which each computer system is designed to perform one specific function (e.g. navigation). There are obvious downsides to this approach, including excessive weight (from so much computing hardware), and inefficient processor utilization (since modern processors are capable of performing multiple tasks). There has therefore been a push for integrated modular avionics (IMA), in which common computing platforms can be leveraged for different purposes. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and design complexity. However, the application of IMA principles introduces significant challenges, as the data network must accommodate traffic of mixed criticality and performance levels - potentially all related to the same shared computer hardware. Because individual network technologies are rarely so competent, the development of truly integrated network architectures often proves unreasonable. Several different types of networks are utilized - each suited to support a specific vehicle function. Critical functions are typically driven by precise timing loops, requiring networks with strict guarantees regarding message latency (i.e. determinism) and fault-tolerance. Alternatively, non-critical systems generally employ data networks prioritizing flexibility and high performance over reliable operation. Switched Ethernet has seen widespread success filling this role in terrestrial applications. Its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components make it desirable for inclusion in spacecraft platforms. Basic Ethernet configurations have been incorporated into several preexisting aerospace projects, including both the Space Shuttle and International Space Station (ISS). However, classical switched Ethernet cannot provide the high level of network determinism required by real-time spacecraft applications. Even with modern advancements, the uncoordinated (i.e. event-driven) nature of Ethernet communication unavoidably leads to message contention within network switches. The arbitration process used to resolve such conflicts introduces variation in the time it takes for messages to be forwarded. TTEthernet1 introduces decentralized clock synchronization to switched Ethernet, enabling message transmission according to a time-triggered (TT) paradigm. A network planning tool is used to allocate each device a finite amount of time in which it may transmit a frame. Each time slot is repeated sequentially to form a periodic communication schedule that is then loaded onto each TTEthernet device (e.g. switches and end systems). Each network participant references the synchronized time in order to dispatch messages at predetermined instances. This schedule guarantees that no contention exists between time-triggered Ethernet frames in the network switches, therefore eliminating the need for arbitration (and the timing variation it causes). Besides time-triggered messaging, TTEthernet networks may provide two additional traffic classes to support communication of different criticality levels. In the rate-constrained (RC) traffic class, the frame payload size and rate of transmission along each communication channel are limited to predetermined maximums. The network switches can therefore be configured to accommodate the known worst-case traffic pattern, and buffer overflows can be eliminated. The best-effort (BE) traffic class behaves akin to classical Ethernet. No guarantees are provided regarding transmission latency or successful message delivery. TTEthernet coordinates transmission of all three traffic classes over the same physical connections, therefore accommodating the full spectrum of traffic criticality levels required in IMA architectures. Common computing platforms (e.g. LRUs) can share networking resources in such a way that failures in non-critical systems (using BE or RC communication modes) cannot impact flight-critical functions (using TT communication). Furthermore, TTEthernet hardware (e.g. switches, cabling) can be shared by both TTEthernet and classical Ethernet traffic.
DOT National Transportation Integrated Search
2006-04-01
The objective of this part of the research study was to select and acquire a mobile traffic counter capable of providing traffic flow and average speed data in intervals of time no greater than 15 minutes and transmit the data back to a central locat...
Fallahi, Majid; Motamedzade, Majid; Heidarimoghadam, Rashid; Soltanian, Ali Reza; Miyake, Shinji
2016-01-01
This study evaluated operators' mental workload while monitoring traffic density in a city traffic control center. To determine the mental workload, physiological signals (ECG, EMG) were recorded and the NASA-Task Load Index (TLX) was administered for 16 operators. The results showed that the operators experienced a larger mental workload during high traffic density than during low traffic density. The traffic control center stressors caused changes in heart rate variability features and EMG amplitude, although the average workload score was significantly higher in HTD conditions than in LTD conditions. The findings indicated that increasing traffic congestion had a significant effect on HR, RMSSD, SDNN, LF/HF ratio, and EMG amplitude. The results suggested that when operators' workload increases, their mental fatigue and stress level increase and their mental health deteriorate. Therefore, it maybe necessary to implement an ergonomic program to manage mental health. Furthermore, by evaluating mental workload, the traffic control center director can organize the center's traffic congestion operators to sustain the appropriate mental workload and improve traffic control management. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Using temporal detrending to observe the spatial correlation of traffic.
Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David
2017-01-01
This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.
Using temporal detrending to observe the spatial correlation of traffic
2017-01-01
This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093
Intelligentization: an efficient means to get more from optical networking
NASA Astrophysics Data System (ADS)
Chen, Zhi Yun
2001-10-01
Infocom is a term used to describe the merger of Information and Communications and is used to show the radical changes in today's network traffic. The continuous growth of Infocom traffic, especially that of Internet, is driving Infocom networks to expand rapidly. To service providers, the traffic is consuming the bandwidth of their network. Simultaneously, users are complaining too slow, the net never stopped in China. It is the reality faced by both the service providers and equipment vendors. Demands from both the customers and competition in market call for an efficient network infrastructure. What should a Service Provider do? This paper will first analyze the development trends of optical networking and the formation of the concepts of Intelligent Optical Network (ION) and Automatic Switched Optical Network (ASON) as a solution to this problem. Next it will look at the ways to bring intelligence into optical networks, discussing the benefits to service providers by showing some application examples. Finally, it concludes that the development of optical networking has arrived at a point of introducing intelligence into optical networks. The intelligent optical networks and Automatic Switched Optical Networks will immediately bring a wide range of benefit to service providers, equipment vendors, and, of course, the end users.
Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network.
Prakash, R; Balaji Ganesh, A; Sivabalan, Somu
2017-05-01
The paper presents a network coded cooperative communication (NC-CC) enabled wireless hospital sensor network architecture for monitoring health as well as postural activities of a patient. A wearable device, referred as a smartband is interfaced with pulse rate, body temperature sensors and an accelerometer along with wireless protocol services, such as Bluetooth and Radio-Frequency transceiver and Wi-Fi. The energy efficiency of wearable device is improved by embedding a linear acceleration based transmission duty cycling algorithm (NC-DRDC). The real-time demonstration is carried-out in a hospital environment to evaluate the performance characteristics, such as power spectral density, energy consumption, signal to noise ratio, packet delivery ratio and transmission offset. The resource sharing and energy efficiency features of network coding technique are improved by proposing an algorithm referred as network coding based dynamic retransmit/rebroadcast decision control (LA-TDC). From the experimental results, it is observed that the proposed LA-TDC algorithm reduces network traffic and end-to-end delay by an average of 27.8% and 21.6%, respectively than traditional network coded wireless transmission. The wireless architecture is deployed in a hospital environment and results are then successfully validated.
Congestion control for a fair packet delivery in WSN: from a complex system perspective.
Aguirre-Guerrero, Daniela; Marcelín-Jiménez, Ricardo; Rodriguez-Colina, Enrique; Pascoe-Chalke, Michael
2014-01-01
In this work, we propose that packets travelling across a wireless sensor network (WSN) can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.
SDN-based path hopping communication against eavesdropping attack
NASA Astrophysics Data System (ADS)
Zhang, Chuanhao; Bu, Youjun; Zhao, Zheng
2016-10-01
Network eavesdropping is one of the most popular means used by cyber attackers, which has been a severe threat to network communication security. Adversaries could capture and analyze network communication data from network nodes or links, monitor network status and steal sensitive data such as username and password etc. Traditional network usually uses static network configuration, and existing defense methods, including firewall, IDS, IPS etc., cannot prevent eavesdropping, which has no distinguishing characteristic. Network eavesdropping become silent during most of the time of the attacking process, which is why it is difficult to discover and to defend. But A successful eavesdropping attack also has its' precondition, which is the target path should be relatively stable and has enough time of duration. So, In order to resolve this problem, it has to work on the network architecture. In this paper, a path hopping communication(PHC) mechanism based on Software Define Network (SDN) was proposed to solve this problem. In PHC, Ends in communication packets as well as the routing paths were changed dynamically. Therefore, the traffic would be distributed to multiple flows and transmitted along different paths. so that Network eavesdropping attack could be prevented effectively. It was concluded that PHC was able to increase the overhead of Network eavesdropping, as well as the difficulty of communication data recovery.
A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo
2011-01-01
The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. PMID:22163948
A wireless sensor network for vineyard monitoring that uses image processing.
Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo
2011-01-01
The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.
All-optical OFDM network coding scheme for all-optical virtual private communication in PON
NASA Astrophysics Data System (ADS)
Li, Lijun; Gu, Rentao; Ji, Yuefeng; Bai, Lin; Huang, Zhitong
2014-03-01
A novel optical orthogonal frequency division multiplexing (OFDM) network coding scheme is proposed over passive optical network (PON) system. The proposed scheme for all-optical virtual private network (VPN) does not only improve transmission efficiency, but also realize full-duplex communication mode in a single fiber. Compared with the traditional all-optical VPN architectures, the all-optical OFDM network coding scheme can support higher speed, more flexible bandwidth allocation, and higher spectrum efficiency. In order to reduce the difficulty of alignment for encoding operation between inter-communication traffic, the width of OFDM subcarrier pulse is stretched in our proposed scheme. The feasibility of all-optical OFDM network coding scheme for VPN is verified, and the relevant simulation results show that the full-duplex inter-communication traffic stream can be transmitted successfully. Furthermore, the tolerance of misalignment existing in inter-ONUs traffic is investigated and analyzed for all-optical encoding operation, and the difficulty of pulse alignment is proved to be lower.
Valiant load-balanced robust routing under hose model for WDM mesh networks
NASA Astrophysics Data System (ADS)
Zhang, Xiaoning; Li, Lemin; Wang, Sheng
2006-09-01
In this paper, we propose Valiant Load-Balanced robust routing scheme for WDM mesh networks under the model of polyhedral uncertainty (i.e., hose model), and the proposed routing scheme is implemented with traffic grooming approach. Our Objective is to maximize the hose model throughput. A mathematic formulation of Valiant Load-Balanced robust routing is presented and three fast heuristic algorithms are also proposed. When implementing Valiant Load-Balanced robust routing scheme to WDM mesh networks, a novel traffic-grooming algorithm called MHF (minimizing hop first) is proposed. We compare the three heuristic algorithms with the VPN tree under the hose model. Finally we demonstrate in the simulation results that MHF with Valiant Load-Balanced robust routing scheme outperforms the traditional traffic-grooming algorithm in terms of the throughput for the uniform/non-uniform traffic matrix under the hose model.
Raysoni, Amit U.; Armijos, Rodrigo X.; Weigel, M. Margaret; Montoya, Teresa; Eschanique, Patricia; Racines, Marcia; Li, Wen-Whai
2016-01-01
An air monitoring campaign to assess children’s environmental exposures in schools and residences, both indoors and outdoors, was conducted in 2010 in three low-income neighborhoods in Z1(north), Z2(central), and Z3(southeast) zones of Quito, Ecuador - a major urban center of 2.2 million inhabitants situated 2850 meters above sea level in a narrow mountainous basin. Z1 zone, located in northern Quito, historically experienced emissions from quarries and moderate traffic. Z2 zone was influenced by heavy traffic in contrast to Z3 zone which experienced low traffic densities. Weekly averages of PM samples were collected at schools (one in each zone) and residences (Z1=47, Z2=45, and Z3=41) every month, over a twelve-month period at the three zones. Indoor PM2.5 concentrations ranged from 10.6±4.9 μg/m3 (Z1 school) to 29.0±30.5 μg/m3 (Z1 residences) and outdoor PM2.5 concentrations varied from 10.9±3.2 μg/m3 (Z1 school) to 14.3±10.1 μg/m3 (Z2 residences), across the three zones. The lowest values for PM10–2.5 for indoor and outdoor microenvironments were recorded at Z2 school, 5.7±2.8 μg/m3 and 7.9±2.2 μg/m3, respectively. Outdoor school PM concentrations exhibited stronger associations with corresponding indoor values making them robust proxies for indoor exposures in naturally ventilated Quito public schools. Correlation analysis between the school and residential PM size fractions and the various pollutant and meteorological parameters from central ambient monitoring (CAM) sites suggested varying degrees of temporal relationship. Strong positive correlation was observed for outdoor PM2.5 at Z2 school and its corresponding CAM site (r=0.77) suggesting common traffic related emissions. Spatial heterogeneity in PM2.5 concentrations between CAM network and sampled sites was assessed using Coefficient of Divergence (COD) analysis. COD values were lower when CAM sites were paired with outdoor measurements (< 0.2) and higher when CAM and indoor values were compared (> 0.2), suggesting that CAM network in Quito may not represent actual indoor exposures. PMID:27149144
Carbon emissions tax policy of urban road traffic and its application in Panjin, China
Yang, Longhai; Fang, Lin
2018-01-01
How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers’ generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler’s generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax’s impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China. PMID:29738580
Carbon emissions tax policy of urban road traffic and its application in Panjin, China.
Yang, Longhai; Hu, Xiaowei; Fang, Lin
2018-01-01
How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers' generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler's generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax's impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China.