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Journal articles on the topic 'Network congestion'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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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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2

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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Liu, Jia-Bao, Arul Jeya Shalini, Micheal Arockiaraj, and J. Nancy Delaila. "Characterization of the Congestion Lemma on Layout Computation." Journal of Mathematics 2021 (October 27, 2021): 1–5. http://dx.doi.org/10.1155/2021/2984703.

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An embedding of a guest network G N into a host network H N is to find a suitable bijective function between the vertices of the guest and the host such that each link of G N is stretched to a path in H N . The layout measure is attained by counting the length of paths in H N corresponding to the links in G N and with a complexity of finding the best possible function overall graph embedding. This measure can be computed by summing the minimum congestions on each link of H N , called the congestion lemma. In the current study, we discuss and characterize the congestion lemma by considering the

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Li, He, Hongxi Yin, and Shanshan Lin. "A novel optical network model for network burden release and congestion reduction based on passive optical network." International Journal of Distributed Sensor Networks 14, no. 10 (2018): 155014771880765. http://dx.doi.org/10.1177/1550147718807652.

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In this article, a new optical network structure coping with network congestion is proposed, which is based on passive optical network, and adopts data storage devices coupled with optical line terminal to release network burden. It is shown by our network performance simulation that this network has many merits such as free-scale, fewer connections, larger clustering coefficient, and smaller average shortest path length in comparison to the passive optical network. The novel network structure can replace the far-end service connections with the near-end ones, reduce congestions in an optical

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Ali, Inayat, Seungwoo Hong, and Tae Yeon Kim. "A multilevel network-assisted congestion feedback mechanism for network congestion control." Computers and Electrical Engineering 123 (April 2025): 110067. https://doi.org/10.1016/j.compeleceng.2025.110067.

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Jain, Vinesh Kumar, Arka Prokash Mazumdar, and Mahesh Chandra Govil. "Congestion Prediction in Internet of Things Network using Temporal Convolutional Network A Centralized Approach." Defence Science Journal 72, no. 6 (2022): 810–23. http://dx.doi.org/10.14429/dsj.72.17447.

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The unprecedented ballooning of network traffic flow, specifically, Internet of Things (IoT) network traffic, has big stressed of congestion on todays Internet. Non-recurring network traffic flow may be caused by temporary disruptions, such as packet drop, poor quality of services, delay, etc. Hence, the network traffic flow estimation is important in IoT networks to predict congestion. As the data in IoT networks is collected from a large number of diversified devices which have unlike format of data and also manifest complex correlations, so the generated data is heterogeneous and nonlinear

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MVPanduranga Rao SBasavaraj, AshakiranGN. "Congestion Control Mechanism using Network Border Protocol." International Journal of Science and Research (IJSR) 1, no. 2 (2012): 35–39. http://dx.doi.org/10.21275/ijsr12120301.

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16

Liu, Heyu, and Fuchun Sun. "A QoS-Oriented Congestion Control Mechanism for Satellite Networks." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/487483.

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The sharply increasing amount of data, which are transferred by the satellite network, requires the satellite network to provide quality-of-service (QoS). However, the upsurge in the data flow leads to the network congestion, impeding its ability to offer QoS. Congestion control mechanisms, deployed in the ground networks, have been thoroughly studied. But those deployed in the satellite networks have not been studied yet. As satellite networks are now important supplements to the ground backbone networks, this paper carefully analyzes the current challenges of developing the QoS-oriented cong

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Zhang, Zhi Jing, and Zeng Xin Xie. "Study on the Adaptive Congestion Control Algorithms for Wireless Sensor Networks." Advanced Materials Research 989-994 (July 2014): 4493–96. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4493.

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As the study on and promotion of wireless sensor networks (WSN) are deepening, people have increasingly higher requirements for the transmission speed and transmission performance of wireless sensor networks. Network congestion is an important factor of the transmission performance of a network, so congestion control becomes a hot research topic in the studies on the improvement of WSN services. Based on the study on WSN congestion control mechanism, this paper proposes an adaptive congestion control algorithm and simulates the algorithm. The simulation result shows that this algorithm can ens

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Ayorinde, Akangbe, Adepoju Abiola, and Adebayo Isaiah. "Power Wheeling Pricing Considering Congestion in Power Network: A Review." American Journal of Engineering and Technology Management 9, no. 3 (2024): 51–55. http://dx.doi.org/10.11648/j.ajetm.20240903.11.

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Limited capacity of the power system infrastructure has a limiting effect on the quantity of electrical power that can be transmitted thereby resulting in the system been congested which also affects the quality of electrical energy supplied. Congestion is an undesired effect in power system with serious economic, reliability and security effect on power system infrastructure, which are yet to be adequately quantify in term of cost. Congestion occurrence and management on the power system network has been studied extensively, causes of congestion and various management techniques have been pro

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Shukur, Marwan Ihsan. "S-CDCA: a semi-cluster directive-congestion protocol for priority-based data in WSNs." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (2021): 438–44. https://doi.org/10.11591/ijeecs.v23.i1.pp438-444.

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The internet of things (IoT) protocols and regulations are being developed for various applications includes: habitat monitoring, machinery control, general health-care, smart-homes and more. A great part of I0T comprised of sensors nodes in connected networks (i.e. sensor networks.). A sensor network is a group of nodes with sensory module and computational elements connected through network interfaces. The most interesting type of sensor networks are wireless sensor networks. The nodes here are connected through wirless interfaces. The shared medium between these nodes, creates different cha

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Shukur, Marwan Ihsan. "S-CDCA: a semi-cluster directive-congestion protocol for priority-based data in WSNs." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (2021): 438. http://dx.doi.org/10.11591/ijeecs.v23.i1.pp438-444.

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The internet of things (IoT) protocols and regulations are being developed forvarious applications includes: habitat monitoring, machinery control, general health-care, smart-homes and more. A great part of I0T comprised of sensors nodes in connected networks (i.e. sensor networks.). A sensor network is a group of nodes with sensory module and computational elements connected through network interfaces. The most interesting type of sensor networks are wireless sensor networks. The nodes here are connected through wirless interfaces. The shared medium between these nodes, creates different chal

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Zhang, Yongqiang, Yaming Li, Min Li, Jinlong Ma, and Zhaohui Qi. "An efficient resource allocation strategy for multilayer networks." International Journal of Modern Physics B 35, no. 05 (2021): 2150073. http://dx.doi.org/10.1142/s0217979221500739.

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The resource allocation strategy plays an important role in the improvement of network traffic capacity. In order to solve the problem of network congestion, an efficient resource allocation strategy is proposed for multilayer networks to optimize the utilization efficiency of network resources. With the proposed strategy, the network resources are allocated to nodes more reasonable and the network congestions are evidently reduced. Simulation experiments show that the proposed resource allocation strategy can greatly improve the traffic capacity of the multilayer networks compared with the av

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D. Kavitha. "Optimal Congestion Control Mechanism For Intelligent Routing To Improve QoS Using Temporal Deep Learning." Communications on Applied Nonlinear Analysis 32, no. 9s (2025): 362–69. https://doi.org/10.52783/cana.v32.3933.

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Congestion in Mobile Ad-hoc Networks (MANETs) leads to connection failures, node loss, and affects network setup. MANETs, lacking permanent infrastructure and central management, suffer from buffer overflow and packet loss under high traffic. Machine Learning (ML) enhances Quality of Service (QoS) in network routing. This paper introduces a congestion control system model with node-level states, control strategies, and network optimization objectives. It analyzes congestion state transitions and real-time control to minimize network delay and congestion cost, deriving optimal strategies using

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Kirtiraj, Mohan Desai, and Ms. T. T. Mohite Patil Prof. "Performance Analysis of Congestion Control Algorithm for Mobility Model in Mobile Ad Hoc Networks MANET." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 2348–53. https://doi.org/10.31142/ijtsrd18335.

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The mobile ad hoc networks MANET is network where the mobile nodes move randomly and freely without any centralized administration or control. Where mobile nodes in MANET works both as routers and as hosts. As we know the challenges faced by the wireless and distributed nature of ad hoc networks such the chances of losing packets over the network increases to a great extent as well as the packet loss occurring with the increase in size of the data packets which are often responsible for congestion in the network. Now In order to detect congestion in the network, there are various congestion co

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Boraiah, Dr Ramesh. "Network Traffic Congestion Prediction done using Machine Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50176.

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Abstract— Too much traffic on networks has become a significant problem for communication systems, leading to slower network performance, worse QoS and uneasy user experiences in many types of infrastructure. As networks advance at lightning speed, from the first (1G) analog to the fifth (5G) generation, the rising complexity of network data calls for using advanced monitoring and predictive techniques. Even though legacy network traffic monitors detect issues in real-time and spot intrusions, they tend to lack the ability to predict congestion which is important for being proactive. This work

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Xiao, Fei. "Congestion and Computer Program Control Algorithm Strategy for Wireless Sensor Networks Based on Cloud Model." Wireless Communications and Mobile Computing 2022 (April 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/9160484.

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Cloud model and sensor network are the research hotspots in recent years. This paper proposes a congestion and rate control strategy for wireless sensor networks based on cloud model. It adjusts the input rate of nodes based on cloud model through node congestion detection. Aiming at the problem of network congestion control, two congestion adjustment algorithms based on red are improved. Congestion threshold and congestion degree are used as the basis of packet transmission rate adjustment to realize network support plug control. In this paper, the congestion control strategy NP starts to all

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Wen, Guoyi, Ning Huang, and Chunlin Wang. "Network Congestion Diffusion Model Considering Congestion Distribution Information." IEEE Access 7 (2019): 102064–72. http://dx.doi.org/10.1109/access.2019.2931354.

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Yang, Xinhao, Sheng Xu, and Ze Li. "Consensus Congestion Control in Multirouter Networks Based on Multiagent System." Complexity 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/3574712.

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Due to the unbalance distribution of network resources and network traffic, congestion is an inherent property of the Internet. The consensus congestion controller based on the multiagent system theory is designed for the multirouter topology, which improves the performance of the whole networks. Based on the analysis of the causes of congestion, the topology of multirouter networks is modeled based on the graph theory and the network congestion control problem is described as a consensus problem in multiagent systems. Simulation results by MATLAB and Ns2 indicate that the proposed algorithm m

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Adaramola, O. J., and J. R. Olasina. "Machine Learning-Driven Congestion Prediction in Mobile Ad-Hoc Networks Through Modelling Approaches." International Journal of Scientific Research in Computer Science and Engineering 13, no. 2 (2025): 30–38. https://doi.org/10.26438/ijsrcse.v13i2.666.

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Mobile Ad Hoc Networks (MANETs) operate autonomously through decentralized configurations for military as well as emergency and academic applications. The adaptable network structure and unstable nature of MANETs result in major traffic jam occurrences when network activity is at the peak. This research studies the congestion issue of MANETs by implementing network simulation with Machine Learning analytics to identify and control traffic congestion effectively. The investigation employed OPNET 14.5v to simulate office scenarios that contained five, ten and fifteen mobile nodes to study conges

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Huang, Tairan, Xiaojuan Lu, Dian Zhang, Haoran Cheng, Pingping Dong, and Lianming Zhang. "ACC-RL: Adaptive Congestion Control Based on Reinforcement Learning in Power Distribution Networks with Data Centers." Energies 16, no. 14 (2023): 5385. http://dx.doi.org/10.3390/en16145385.

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Modern data center power distribution networks place greater demands on the stability and reliability of power supply. Growing network computing demands and complex network environments can cause network congestion, which in turn leads to network traffic overload and power supply equipment overload. Therefore, network congestion is one of the most important problems faced by data center power distribution networks. In this paper, we propose an approach called ACC-RL based on reinforcement learning (RL), which can effectively avoid network congestion and improve energy performance. ACC-RL model

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Shiltagh, Nadia, and Zainab Faisal. "Traffic Management in Wireless Sensor Network Based on Modified Neural Networks." Iraqi Journal for Computers and Informatics 41, no. 1 (2014): 4–8. http://dx.doi.org/10.25195/ijci.v41i1.90.

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Wireless Sensor Networks (WSNs) are event-driven network systems consist of many sensors node which aredensely deployed and wirelessly interconnected that allow retrieving of monitoring data. In Wireless sensor network,whenever an event is detected, the data related to the event need to be sent to the sink node (data collection node). Sink nodeis the bottleneck of network there may be chance for congestion due to heavy data traffic. Due to congestion, it leads to dataloss; it may be important data also. To achieve this objective, soft computing based on Neural Networks (NNs) CongestionControll

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Hu, Xi, and Wei Guo. "A robust congestion control scheme for cluster wireless multimedia sensor networks with propagation delay and external interference." International Journal of Distributed Sensor Networks 12, no. 12 (2016): 155014771668340. http://dx.doi.org/10.1177/1550147716683407.

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Congestion control in cluster wireless multimedia sensor networks is capable of delivering and gathering multimedia information, while propagation delay and external interference may cause it unable to achieve the maximal network throughput without congestion control. To solve the problem, based on the additive-increase multiplicative-decrease adjustment strategy, a robust congestion control model is proposed with a scheduling scheme in cluster wireless multimedia sensor networks considering the neighbor feedback. The robust congestion control model is a Lur’e-type system. The cluster wireless

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Hsiao, T. Y., C. N. Lu, and E. Liu. "Network Congestion Warning Indices." IEEE Transactions on Power Systems 23, no. 3 (2008): 1527–28. http://dx.doi.org/10.1109/tpwrs.2008.923652.

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Wang, Jian Ling, and Hong Bo Lai. "Congestion Analysis on Urban Traffic Network." Advanced Materials Research 756-759 (September 2013): 1635–38. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1635.

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this paper explores the urban traffic congestion problems, from four angles: the discrimination of the traffic congestion, cause of traffic congestion, congestion characteristics of urban traffic network, measures to solve traffic congestion, to conduct in-depth analysis of traffic congestion.

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Sun, Yi, Min Li, and Peng Xu. "A Cross-Layer Congestion Control Algorithm Based on Traffic Prediction in Wireless Sensor Networks." Applied Mechanics and Materials 397-400 (September 2013): 2641–46. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2641.

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Congestion in wireless sensor networks can affect the networks performance seriously,not only it has impact on data transmission and the quality of service, but also wastes energy and shortens the network lifetime. Aiming at this issue, this paper proposed a cross-layer congestion control algorithm based on traffic prediction (CCATP), it can take congestion mitigation measures in advance according to the prediction result. CCATP comprises three mechanisms: (i) congestion prediction; (ii) local congestion control mechanism based on backoff time adjustment; (iii) transmission route selection bas

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Halepoto, Imtiaz Ali, Fayaz Ahmed, Sajida Parveen, Muhammad Asif Khan, Ali Raza Bhangwar, and Shafaq Rafique Memon. "Evaluating Congestion Control Methods for enhanced Throughput." VFAST Transactions on Software Engineering 12, no. 2 (2024): 155–63. http://dx.doi.org/10.21015/vtse.v12i2.1843.

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With easy access and many services such as social networks, online shopping, video streaming the data traffic over the Internet is increasing. On the other side, the traditional congestion control strategies of TCP due to the huge data are not sufficient. The TCP protocol uses such traditional techniques to minimize the network congestion. Moreover, handling applications with smartphones is challenging in terms of congestion due to the long delay networks such as 4G. Many TCP variants have been proposed for the network congestion particularly for long delay networks such as TCP (Binary increas

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Liu, Xingliang, Jian Wang, Tangzhi Liu, and Jin Xu. "Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity." Sustainability 13, no. 21 (2021): 12195. http://dx.doi.org/10.3390/su132112195.

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Emergency events can induce serious traffic congestions in a local area which may propagate to the upstream roads, and even the whole network. Until now, the methodology forecasting spatiotemporal boundary propagation of emergency-event-based traffic congestions, with both explicitness and road network availability, has not been found. This study develops a new method for predicting spatiotemporal boundary of the congestion caused by emergency events, which is more applicable and practical than cell transmission model (CTM)-derived methods. This method divides the expressway network into diffe

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Zhang, Sen, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, and Jianjun Hu. "Deep Autoencoder Neural Networks for Short-Term Traffic Congestion Prediction of Transportation Networks." Sensors 19, no. 10 (2019): 2229. http://dx.doi.org/10.3390/s19102229.

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Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow

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Majeed, Uzma, Aqdas Naveed Malik, Nasim Abbas, and Waseem Abbass. "An Energy-Efficient Distributed Congestion Control Protocol for Wireless Multimedia Sensor Networks." Electronics 11, no. 20 (2022): 3265. http://dx.doi.org/10.3390/electronics11203265.

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Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network surpasses the available capacity. This article presents an energy-efficient distributed congestion control protocol (DCCP) to mitigate congestion and improve end-to-end delay. Compared to the other protocols, the DCCP protocol proposed in this article can alleviate congestion by intelligently selecting the best pa

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Hu, Ling Yi. "A Research of Network Congestion Pricing Mechanism in TCP Connection Based on Utility Model." Advanced Materials Research 756-759 (September 2013): 2790–94. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2790.

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Network externality is a vital characteristic of the products in economics of networks. Network congestion will lead to negative network externality when digital products are communicated in the net. It will effectively decrease the negative network externality via developing a suitable pricing mechanism. This paper begins with the utility of a single user and that of the whole network to build a network congestion utility model to analyze it. As TCP connection has an autonomous congestion-detecting mechanism which can increase the utilization of network resources, we regard the TCP connection

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Ganesan, Sangeetha, Vijayalakshmi Muthuswamy, Ganapathy Sannasi, and Kannan Arputharaj. "A Comprehensive Analysis of Congestion Control Models in Wireless Sensor Networks." International Journal of Strategic Information Technology and Applications 9, no. 4 (2018): 15–37. http://dx.doi.org/10.4018/ijsita.2018100102.

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Congestion control is an important factor for performance improvement in wireless sensor networks (WSNs). Congestion occurs due to various reasons including a variation in the data rate between incoming and outgoing links, buffer size, flooding attacks and multiple inputs and minimum output capability. Various outcomes of congestion in sensor networks include immense packet loss or packet drop, fast energy depletion, unfairness across the network, reduced node performance and increased delay in packet delivery. Hence, there is an extreme need to check channel congestion in order to enhance the

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Hussain, Maab. "A RADIAL BASIS NEURAL NETWORK CONTROLLER TO SOLVE CONGESTION IN WIRELESS SENSOR NETWORKS." Iraqi Journal for Computers and Informatics 44, no. 1 (2018): 40–48. http://dx.doi.org/10.25195/ijci.v44i1.103.

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In multihop networks, such as the Internet and the Mobile Ad-hoc Networks, routing is one of the most importantissues that has an important effect on the network’s performance. This work explores the possibility of using the shortest path routingin wireless sensor network . An ideal routing algorithm should combat to find an perfect path for data that transmitted within anexact time. First an overview of shortest path algorithm is given. Then a congestion estimation algorithm based on multilayerperceptron neural networks (MLP-NNs) with sigmoid activation function, (Radial Basis Neural Network

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Fuentes, Joan, Sebastian Zapata, Enrique Angel, Camila Ochoa, and Valentina Betancur. "Modeling Infrastructure Delays and Congestion for Large-Scale Power Systems." Energies 18, no. 12 (2025): 3047. https://doi.org/10.3390/en18123047.

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This paper analyzes the electricity dispatch process and the importance of predicting infrastructure construction delays and network congestion using a system dynamics methodology. Two scenarios of renewable energy integration within Colombia are examined, together with their impact on electrical generation, pricing, and the growth of transmission networks. The results indicate that delays significantly influence the system’s long-term development. Incorporating network congestion into energy dispatch significantly alters investment requirements for generation and transmission, emphasizing net

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Chitra, P., and M. Chandrasekaran. "Novel Energy-Efficient Congestion Control Protocol in Wireless Networks Using Evolutionary Game Paradigm." Journal of Computational and Theoretical Nanoscience 14, no. 1 (2017): 460–67. http://dx.doi.org/10.1166/jctn.2017.6346.

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In recent years, Wireless Network technology was designed for short distance communications like ZigBee, Bluetooth and Infrared Transmission. Congestion degrades the performance of the wireless network and also reduces the battery life of a mobile node. Congestion control is very much essential in the transport layer to prevent performance degradation in a wireless network. Congestion control mechanism restricts the packet transmission rate with respect to the shared network resources. In this work, we designed a novel Energy-Efficient Congestion Control Protocol using Evolutionary Game model

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Hiremath, Parnita, Mourya Teja Yalamanchili, and Kethan Mulpuri. "Smart ECN and RSVP Protocols for QOS and Congestion Optimization in 5G Networks Using Advanced AI Techniques." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–9. https://doi.org/10.55041/ijsrem40383.

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In the rapidly evolving landscape of 5G networks, ensuring Quality of Service (QoS) and efficient congestion management are paramount to meet the high demands of modern applications. This paper presents a comprehensive study on the integration of Smart Explicit Congestion Notification (ECN) and Resource Reservation Protocol (RSVP) protocols, enhanced by advanced Artificial Intelligence (AI) techniques, to optimize QoS and manage congestion in 5G networks. We propose a novel framework that combines AI-driven algorithms with traditional congestion control mechanisms to dynamically adjust network

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Yan, Jiangyu, and Bing Qi. "CARA: A Congestion-Aware Routing Algorithm for Wireless Sensor Networks." Algorithms 14, no. 7 (2021): 199. http://dx.doi.org/10.3390/a14070199.

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Congestion control is one of the key research topics in relation to the routing algorithms of wireless sensor networks (WSNs). In this paper, we propose a congestion-aware routing algorithm (CARA) for unlimited-lifetime wireless sensor networks by integrating the geographic distance and traffic load of sensor nodes. The algorithm takes alleviating congestion as the primary purpose and considers the traffic of the node itself and local network traffic. According to the geographic distance between nodes, CARA defines four decision parameters (node load factor, forward rate, cache remaining rate,

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Xia, Jiqiang, Surong Zhang, and Julong Lan. "MFUC: Mitigating Transient Congestion for Multi-flow Updating in SDN." Journal of Physics: Conference Series 2289, no. 1 (2022): 012007. http://dx.doi.org/10.1088/1742-6596/2289/1/012007.

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Abstract Through the logically centralized control plane, software-defined network (SDN) provides giant convenience for the design of the network strategies, like load balancing, fault recovery, etc. However, when deploying those strategies on the data plane, transient link congestions may occur since the updating process among the distributed switches is asynchronous. To address this issue, we propose a congestion-aware mechanism for multi-flow updating in SDN. We first obtain the real-time traffic size of each flow to be updated through the link monitoring model. Then we use the congestion-a

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Lim, Chansook. "A Survey on Congestion Control for RPL-Based Wireless Sensor Networks." Sensors 19, no. 11 (2019): 2567. http://dx.doi.org/10.3390/s19112567.

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RPL (IPv6 routing protocol for low power and lossy networks) proposed by the IETF (Internet Engineering Task Force) ROLL (routing over low-power and lossy networks) working group is a de facto standard routing protocol for IoT environments. Since the standardization was proposed, RPL has been extensively improved for diverse application scenarios and environments. Congestion control is one of the most important reasons why RPL has been improved. In an LLN (low power and lossy network), congestion may even lead to network lifetime reduction. In resource-constrained networks where end-to-end con

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Kalinic, Maja, and Jukka M. Krisp. "Determining traffic congestion utilizing a fuzzy logic model and Floating Car Data (FCD)." Proceedings of the ICA 4 (December 3, 2021): 1–8. http://dx.doi.org/10.5194/ica-proc-4-55-2021.

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Abstract. Traffic congestion is a dynamic spatial and temporal process and as such might not be possible to model with linear functions of various dependent variables. That leaves a lot of space for non-linear approximates, such as neutral networks and fuzzy logic. In this paper, the focus is on the fuzzy logic as a possible approach for dealing with the problems of measuring traffic congestion. We investigate the application of this framework on a selected case study, and use floating car data (FCD) collected in Augsburg, Germany. A fuzzy inference system is built to detect degrees of congest

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Kaur, Mankiran, and Jagjit Kaur. "Security Technique and Congestion Avoidance in Mesh Network." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (2017): 1080–84. http://dx.doi.org/10.31142/ijtsrd4690.

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Zhang, Sen, Shaobo Li, Xiang Li, and Yong Yao. "Representation of Traffic Congestion Data for Urban Road Traffic Networks Based on Pooling Operations." Algorithms 13, no. 4 (2020): 84. http://dx.doi.org/10.3390/a13040084.

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In order to improve the efficiency of transportation networks, it is critical to forecast traffic congestion. Large-scale traffic congestion data have become available and accessible, yet they need to be properly represented in order to avoid overfitting, reduce the requirements of computational resources, and be utilized effectively by various methodologies and models. Inspired by pooling operations in deep learning, we propose a representation framework for traffic congestion data in urban road traffic networks. This framework consists of grid-based partition of urban road traffic networks a

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