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Relevant bibliographies by topics / Network congestion

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Academic literature on the topic 'Network congestion'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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Journal articles on the topic "Network congestion"

1

Agbonaye, Osaru, Patrick Keatley, Ye Huang, Motasem Bani Mustafa, and Neil Hewitt. "Design, Valuation and Comparison of Demand Response Strategies for Congestion Management." Energies 13, no. 22 (2020): 6085. http://dx.doi.org/10.3390/en13226085.

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Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping str

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Zhang, Liangliang, Yuanhua Jia, Zhonghai Niu, and Cheng Liao. "Widespread Traffic Congestion Prediction for Urban Road Network Based on Synergetic Theory." Journal of Systems Science and Information 2, no. 4 (2014): 366–71. http://dx.doi.org/10.1515/jssi-2014-0366.

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AbstractThe traffic congestion often occurs in urban road network. When one of the sections becomes congested, it will lead to a series of congestions in other sections. The traffic congestion spreads rapidly until part of road network becomes congestion ultimately. In this case, the paper investigates the mechanism of the traffic congestion in urban road network and points out that subsystems of the traffic congestion always perform completive and cooperative functions in the process of traffic congestion. The process behaves in a manner of self-organized criticality, which can be forecasted.

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Langa, Makhulu Relebogile, and Michael Nthabiseng Moeti. "A Real-Time Notification System for Traffic Congestion on South African National Routes." International Conference on Intelligent and Innovative Computing Applications 2022 (December 31, 2022): 79–91. http://dx.doi.org/10.59200/iconic.2022.009.

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Transportation is an integral part of our daily life, and now with an ever increasing number of cars on the roads, traffic congestion is inevitable. Traffic congestion has a huge impact on service delivery and, in turn, on the economy of the country. Social network has revolutionized our lives, and commuters are now able to vent their frustrations and post live updates regarding these congestions. Social networks have enabled humans to become active live sensors participating in the network communication paradigm. This paper leverages Naïve Bayes classifier of Artificial Intelligence (AI) for

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J P, Hemalatha. "Congestion Control Techniques for Mobile Network." International Journal of Scientific Engineering and Research 4, no. 2 (2016): 14–17. https://doi.org/10.70729/ijser15675.

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Qin, Jiayu, Gang Mei, and Lei Xiao. "Building the Traffic Flow Network with Taxi GPS Trajectories and Its Application to Identify Urban Congestion Areas for Traffic Planning." Sustainability 13, no. 1 (2020): 266. http://dx.doi.org/10.3390/su13010266.

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Traffic congestion is becoming a critical problem in urban traffic planning. Intelligent transportation systems can help expand the capacity of urban roads to alleviate traffic congestion. As a key concept in intelligent transportation systems, urban traffic networks, especially dynamic traffic networks, can serve as potential solutions for traffic congestion, based on the complex network theory. In this paper, we build a traffic flow network model to investigate traffic congestion problems through taxi GPS trajectories. Moreover, to verify the effectiveness of the traffic flow network, an act

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Manoj, Rathore, and Anuj Kumar Pal Prof. "Review on Congestion Control Algorithm for VANET." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 1720–24. https://doi.org/10.31142/ijtsrd17162.

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Vehicular ad hoc networks VANETs , which is a subclass of Mobile ad hoc networks, have recently been developed as a standard means of communication among moving vehicles because it has tremendous potential to improve vehicle and road safety, traffic efficiency. VANET applications have the characteristics such as fast change of topology, bandwidth limitation and lack of central coordination that causes network congestion which restricts the network performance. Number of solutions proposed to overcome these challenges and to reduce congestion on VANET. These solutions include congestion control

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DUMRAUF, DOMINIC, and BURKHARD MONIEN. "COMPUTING NASH EQUILIBRIA FOR TWO-PLAYER RESTRICTED NETWORK CONGESTION GAMES IS $\mathcal{PLS}$-COMPLETE." Parallel Processing Letters 22, no. 04 (2012): 1250014. http://dx.doi.org/10.1142/s0129626412500144.

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We determine the complexity of computing pure Nash equilibria in restricted network congestion games. Restricted network congestion games are network congestion games, where for each player there exits a set of edges which he is not allowed to use. Rosenthal's potential function guarantees the existence of a Nash Equilibrium. We show that computing a Nash equilibrium in a restricted network congestion game with two players is [Formula: see text]-complete, using a tight reduction from MAXCUT. The result holds for directed networks and for undirected networks.

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Hu, Yao, Ting Peng, and Lianming Zhang. "Software-Defined Congestion Control Algorithm for IP Networks." Scientific Programming 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/3579540.

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The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP) must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP) network. However, it is possible that a software-defined approach can relieve the network congestion problem more effi

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Liu, Xiaojie, and Ulrich Speidel. "RAODV Routing Protocol for Congestion Detection and Relief in Ad Hoc Wireless Networks." International Journal of Interdisciplinary Telecommunications and Networking 13, no. 4 (2021): 21–34. http://dx.doi.org/10.4018/ijitn.2021100103.

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Ad hoc wireless networks depend on mutual collaboration among nodes. Congestion in ad hoc wireless networks thus presents more of a challenge than for other network types. This article proposes RAODV (relieving AODV), a modification of the AODV routing protocol, to handle congestion via third party neighbour nodes in dense and static ad hoc networks. RAODV nodes use a T-entropy threshold-based congestion detection algorithm to determine the congestion status of their neighbours. If RAODV determines that congestion is occurring, it then tries to relieve congestion via a local repair modificatio

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Umar, Abdullah, Zubair Khalid, Mohammed Ali, et al. "A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based Solutions." Applied Sciences 13, no. 22 (2023): 12384. http://dx.doi.org/10.3390/app132212384.

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The Internet of Things (IoT) and wireless sensor networks (WSNs) have evolved rapidly due to technological breakthroughs. WSNs generate high traffic due to the growing number of sensor nodes. Congestion is one of several problems caused by the huge amount of data in WSNs. When wireless network resources are limited and IoT devices require more and more resources, congestion occurs in extremely dense WSN-based IoT networks. Reduced throughput, reduced network capacity, and reduced energy efficiency within WSNs are all effects of congestion. These consequences eventually lead to network outages

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Dissertations / Theses on the topic "Network congestion"

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Yang, Yang. "Network congestion control." Access restricted to users with UT Austin EID, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3037028.

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Daneryd, Oscar. "Congestion Management at the Network Edge." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-26082.

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In the Internet of today there is a demand for both high bandwidth and low delays. Bandwidth-heavy applications such as large downloads or video streaming compete with more delay-sensitive applications; web-browsing, VoIP and video games. These applications represent a growing share of Internet traffic. Buffers are an essential part of network equipment. They prevent packet loss and help maintain hight throughput. As bandwidths have increased so have the buffer sizes. In some cases way to much. This, and the fact that Active Queue Management (AQM) is seldom implemented, has given rise to a phe

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Welzl, Michael. "Network congestion control : managing Internet traffic /." Chichester [u.a.] : Wiley, 2005. http://www.loc.gov/catdir/toc/ecip0513/2005015429.html.

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Arpaci, Mutlu. "Congestion avoidance in TCP/IP networks." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/15356.

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Chung, Jae Won. "Congestion control for streaming media." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-081805-084831/.

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Dissertation (Ph.D.) -- Worcester Polytechnic Institute.<br>Keywords: streaming media; streaming transport protocol; active queue management (AQM); Internet congestion control. Includes bibliographical references (p. 236-248).

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Huang, Shimin. "Cross-Layer Congestion Control with Deep Neural Network in Cellular Network." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264239.

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A significant fraction of data traffic is transmitted via cellular networks. When introducing fifth-generation (5G) radio access technology, the maximum bitrate of the radio link increases significantly, and the delay is lowered. Network congestion occurs when the sender attempts to send data at a higher rate than the network link or nodes can handle. In order to improve the performance of the mobile networks, many congestion control techniques and approaches have been developed over the years. Varying radio conditions in mobile networks make it challenging to indicate the occurrence of the co

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Lee, Etty J. (Etty Joanne). "Free-space optical networks : fade and interference mitigation and network congestion control." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/60154.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 337-341).<br>Optical communication through the atmospheric channel is commonly known as free-space optical (FSO) communication. When communicating through a clear FSO channel, not only is there atmospheric turbulence which results in fading of the received signal, but there may also be interference that scatters into the receiver and deteriorates performance. In this thesis, we consider mitigating

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Glazer, D. W. (David W. ). "On routing and congestion control in computer communications networks." Thesis, McGill University, 1986. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66146.

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Fabregat, Gesa Ramon. "Congestion probability routing in virtual path ATM network." Doctoral thesis, Universitat de Girona, 1998. http://hdl.handle.net/10803/31897.

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This dissertation focuses on the problem of providing mechanisms for routing point to point and multipoint connections in ATM networks. In general the notion of multipoint connection refers to connections that involve a group of users with more than two members. The main objective of this dissertation is to contribute to design efficient routing protocols with alterative routes in fully connected VP-based ATM Networks for call establishment of point to point and multipoint VC connections. An efficient route should be computed during this connection establishment phase.

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Zhang, Zaichen, and 張在琛. "Network-supported internet multicast congestion and error control." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31243915.

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Books on the topic "Network congestion"

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Welzl, Michael. Network Congestion Control. John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/047002531x.

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Welzl, Michael. Network Congestion Control. John Wiley & Sons, Ltd., 2005.

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Nasser, Thomas-Olivier. Congestion pricing and network expansion. World Bank, Private Sector Development Department, Private Participation in Infrastructure Group, 1998.

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Low, Steven H. Analytical Methods for Network Congestion Control. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79275-5.

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Welzl, Michael. Scalable Performance Signalling and Congestion Avoidance. Springer US, 2003.

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Shefer, Daniel. Urban transport externalities and Pigouvian taxes: A network approach. Center for Urban and Regional Studies, Faculty of Architecture and Twon Planning, Technion-Israel Institute of Telchnology, 1994.

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7

Srikant, R. The Mathematics of Internet Congestion Control. Birkhäuser Boston, 2004.

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Srikant, R. The mathematics of Internet congestion control. Birkhäuser, 2004.

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9

1968-, Rovithakis George A., ed. End to end adaptive congestion control in TCP/IP networks. Taylor & Francis, 2012.

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International Telecommunication Union. Telecommunication Standardization Sector. Integrated services digital network (ISDN) overall network aspects and functions: Traffic control and congestion control in B-ISDN. International Telecommunication Union, 1993.

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Book chapters on the topic "Network congestion"

1

Weik, Martin H. "network congestion." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_12216.

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Eiselt, H. A., and C. L. Sandblom. "Networks with Congestion." In Integer Programming and Network Models. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04197-0_20.

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Kao, Ming-Yang. "Atomic Network Congestion Games." In Encyclopedia of Algorithms. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_40.

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Osipov, Vasiliy, and Dmitriy Miloserdov. "Neural Network Forecasting of Traffic Congestion." In Communications in Computer and Information Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37858-5_20.

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Yu, Bencheng, and Chao Xu. "Efficient QoS Scheme in Network Congestion." In Lecture Notes in Electrical Engineering. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4805-0_14.

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Baydal, E., P. López, and J. Duato. "Avoiding Network Congestion with Local Information." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47847-7_6.

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Low, Steven H. "Global Stability: Passivity Method." In Analytical Methods for Network Congestion Control. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79275-5_4.

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Low, Steven H. "Equilibrium Structure." In Analytical Methods for Network Congestion Control. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79275-5_2.

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Low, Steven H. "Local Stability with Delay." In Analytical Methods for Network Congestion Control. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79275-5_6.

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Low, Steven H. "Global Stability: Gradient Projection Method." In Analytical Methods for Network Congestion Control. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79275-5_5.

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Conference papers on the topic "Network congestion"

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Choi, Hyeongrak, Marc G. Davis, Álvaro G. Iñesta, and Dirk Englund. "Scalable Photonic Quantum Network." In CLEO: Fundamental Science. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_fs.2024.ftu3f.4.

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Aoki, Keita, and Miki Yamamoto. "Poster: The Congestion Path Multiplicity Problem in RDMA Multicast Congestion Control." In 2024 IEEE 32nd International Conference on Network Protocols (ICNP). IEEE, 2024. https://doi.org/10.1109/icnp61940.2024.10858580.

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Toledo, Kfir, and Isaac Keslassy. "2SYN: Congestion-Aware Multihoming." In NOMS 2025-2025 IEEE Network Operations and Management Symposium. IEEE, 2025. https://doi.org/10.1109/noms57970.2025.11073638.

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Misa Moreira, Carmen, and Edoardo Martelli. "NOTED: a congestion driven network controller." In International Symposium on Grids & Clouds (ISGC) 2024. Sissa Medialab, 2024. http://dx.doi.org/10.22323/1.458.0013.

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Nunes, Diego Cardoso, Theophilus A. Benson, and Alberto E. Schaeffer-Filho. "SafeNetCC: Towards Safety-Oriented Congestion Control." In NOMS 2025-2025 IEEE Network Operations and Management Symposium. IEEE, 2025. https://doi.org/10.1109/noms57970.2025.11073635.

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Kunze, Ike, Constantin Sander, Mike Kosek, Lars Tissen, Jan Pennekamp, and Klaus Wehrle. "Congestion-Responsive Queuing for Internet Flows." In NOMS 2025-2025 IEEE Network Operations and Management Symposium. IEEE, 2025. https://doi.org/10.1109/noms57970.2025.11073697.

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Huang, Yukai, Lulu Chen, Chunpu Huang, et al. "Mitigating Intra-host Network Congestion with SmartNIC." In 2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS). IEEE, 2024. http://dx.doi.org/10.1109/iwqos61813.2024.10682939.

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Vaidya, Rahul, Chitresh Yadav, Jyothish Kunkumath, and Prasad Yadati. "Network congestion control." In the 1st International Conference. ACM Press, 2011. http://dx.doi.org/10.1145/2185216.2185276.

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Vu, Thi Van Anh, and Hoang Minh Nguyen. "THE USE OF NEURAL NETWORK METHOD IN DETERMINING THE PROPORTION OF TRAFFIC FLOW REDIRECTION IN THE ROAD NETWORK." In SCIENCE AND INNOVATION IN THE MODERN WORLD. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2024. http://dx.doi.org/10.58168/simw2024_108-116.

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The article presents the results of an experimental study on traffic management in the event of unpredictable situations in the transportation network. The aim of this research is to determine the proportion of traffic flow through the network in the situation of reduced capacity of road segments (UDS), including due to traffic accidents. This work proposes a method to address congestion issues by redirecting vehicles from roads with high network load coefficients (z) to alternative routes, while determining the volume of traffic flow to eliminate the possibility of congestion in other transpo

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Sahoo, Ratneswar, Pooja Kumari, and Niranjan Kumar. "CONGESTION MANAGEMENT IN DEREGULATED POWER SYSTEM: A REVIEW." In TOPICS IN INTELLIGENT COMPUTING AND INDUSTRY DESIGN (ICID). Volkson Press, 2022. http://dx.doi.org/10.26480/icpesd.02.2022.106.110.

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Restructuring has swept through all potential fields in recent decades, including the electric supply industry. Restructuring has resulted in significant changes, such as the fact that power is now a commodity and has become deregulated. In such a competitive industry, there are a plethora of participants. Overloading transmission networks or network congestion have come from the emergence of deregulated electricity systems. Congestion has significant consequences for electricity systems, including system failure. When transmission networks fail to transfer power in accordance with load demand

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Reports on the topic "Network congestion"

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Chen, Yongzhou, Ammar Tahir, and Radhika Mittal. Controlling Congestion via In-Network Content Adaptation. Illinois Center for Transportation, 2022. http://dx.doi.org/10.36501/0197-9191/22-018.

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Realizing that it is inherently difficult to match precisely the sending rates at the endhost with the available capacity on dynamic cellular links, we built a system, Octopus, that sends real-time data streams over cellular networks using an imprecise controller (that errs on the side of overestimating network capacity) and then drops appropriate packets in the cellular-network buffers to match the actual capacity. We designed parameterized primitives for implementing the packet-dropping logic, which the applications at the endhost can configure differently to express various content-adaptati

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Goldberg, L. A., P. D. MacKenzie, and D. S. Greenberg. Network congestion can be controlled: Routing algorithms in optical networks and Ethernets. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/565650.

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Dabrowski, Christopher, and Kevin Mills. The Influence of Realism on Congestion in Network Simulations. National Institute of Standards and Technology, 2016. http://dx.doi.org/10.6028/nist.tn.1905.

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Denis-Courmont, R. Network Address Translation (NAT) Behavioral Requirements for the Datagram Congestion Control Protocol. RFC Editor, 2009. http://dx.doi.org/10.17487/rfc5597.

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Duvvuri, Sarvani, and Srinivas S. Pulugurtha. Researching Relationships between Truck Travel Time Performance Measures and On-Network and Off-Network Characteristics. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.1946.

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Trucks serve significant amount of freight tonnage and are more susceptible to complex interactions with other vehicles in a traffic stream. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel result in loss of revenue to the trucking companies. There is a significant research on the traffic congestion mitigation, but a very few studies focused on data exclusive to trucks. This research is aimed at a regional-level analysis of truck travel time data to identify roads for improving mobility and reducing congestion for truck traffic. The objectives of

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Hu, Ningning, and Peter Steenkiste. RPT: A Low Overhead Single-End Probing Tool for Detecting Network Congestion Positions. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada461141.

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Romaniak, Gregory W., David R. Beering, and Michael A. Rupar. Mechanisms for Differentiating End-to-End Loss Due to Channel Corruption and Network Congestion. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada397822.

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Zhu, X., R. Pan, M. Ramalho, and S. Mena. Network-Assisted Dynamic Adaptation (NADA): A Unified Congestion Control Scheme for Real-Time Media. RFC Editor, 2020. http://dx.doi.org/10.17487/rfc8698.

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Mayer, Christopher, and Todd Sinai. Network Effects, Congestion Externalities, and Air Traffic Delays: Or Why All Delays Are Not Evil. National Bureau of Economic Research, 2002. http://dx.doi.org/10.3386/w8701.

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Desai, Jairaj, Jijo K. Mathew, Howell Li, Rahul Suryakant Sakhare, Deborah Horton, and Darcy M. Bullock. National Mobility Report for All Interstates–December 2022. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317591.

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In January 2023, Wejo Data Services Inc. provided Purdue with a national data set comprised of approximately 503 billion connected vehicle records covering all 50 states for the month of December 2022. The goal of the evaluation data set was to create a series of summary graphics to evaluate the scalability of work zone/winter weather analytics graphics and electric/hybrid vehicle counts at a national level as well as visualize the mobility impacts of winter weather activity on the national interstate network. This report illustrates several performance measures developed using this dataset fo

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