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Journal articles on the topic 'Delay-based congestion control'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Guo, Wenlan, Jin Huang, and Yun Zhang. "Delay-based Congestion Control for Multipath TCP." International Journal of Future Generation Communication and Networking 7, no. 1 (2014): 97–104. http://dx.doi.org/10.14257/ijfgcn.2014.7.1.10.

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2

Haeri, Mohammad, and Amir Hamed Mohsenian Rad. "Adaptive model predictive TCP delay-based congestion control." Computer Communications 29, no. 11 (2006): 1963–78. http://dx.doi.org/10.1016/j.comcom.2005.12.004.

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3

Yuan, Cao, and Ya Qin Li. "A New Delay-Based Congestion Control for Ad-Hoc Wireless Network." Applied Mechanics and Materials 160 (March 2012): 223–26. http://dx.doi.org/10.4028/www.scientific.net/amm.160.223.

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The traditional congestion control mechanism of transport control protocol (TCP) has been proved cannot satisfy the wireless scenario. The extensive research has been done to understand the drawback of TCP in wireless networks. In this paper, we proposed a new congestion control algorithms for mobile ad-hoc networks (MANET) at the TCP sender side which efficiently adapts to the maximum transmission rate of a mobile wireless link, the new algorithms follow the idea of FAST TCP which uses delay as congestion measure. However, FAST TCP has limitations when used over a dynamic mobile wireless link

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4

Deepak, Kanojia. "Hybrid Congestion Control Mechanisms for Next-Generation Communication Networks." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 14, no. 3 (2025): 9–14. https://doi.org/10.35940/ijitee.B1034.14030225.

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<strong>Abstract: </strong>In the rapidly evolving realm of next-generation communication systems, characterized by ultra-low latency and high-speed data transmission, effectively managing network congestion remains a critical challenge. Traditional congestion control mechanisms often struggle to meet the demands of these advanced environments. This paper presents a novel approach that integrates both delay and loss metrics, specifically designed for 5G and beyond. By utilizing real-time variations in delay and packet loss as indicators of congestion, the proposed method enables dynamic adjust

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5

Verma, Lal Pratap, Varun Kumar Sharma, Mahesh Kumar, and Dimitris Kanellopoulos. "A novel Delay-based Adaptive Congestion Control TCP variant." Computers and Electrical Engineering 101 (July 2022): 108076. http://dx.doi.org/10.1016/j.compeleceng.2022.108076.

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6

D'Aronco, Stefano, Laura Toni, Sergio Mena, Xiaoqing Zhu, and Pascal Frossard. "Improved Utility-Based Congestion Control for Delay-Constrained Communication." IEEE/ACM Transactions on Networking 25, no. 1 (2017): 349–62. http://dx.doi.org/10.1109/tnet.2016.2587579.

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7

Liu, Yuxin, Danhong Zhu, and Dong Zhang. "Delay-based virtual congestion control in multi-tenant datacenters." IOP Conference Series: Materials Science and Engineering 322 (March 2018): 052040. http://dx.doi.org/10.1088/1757-899x/322/5/052040.

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8

Cavendish, Dirceu, Yuji Oie, Masayuki Murata, and Hideo Miyahara. "Proportional rate-based congestion control under long propagation delay." International Journal of Communication Systems 8, no. 2 (1995): 79–89. http://dx.doi.org/10.1002/dac.4500080202.

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9

Testa, Claudio, and Dario Rossi. "Delay-based congestion control: Flow vs. BitTorrent swarm perspectives." Computer Networks 60 (February 2014): 115–28. http://dx.doi.org/10.1016/j.bjp.2013.12.018.

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10

Khan, Muhammad, Yasir Zaki, Shiva Iyer, et al. "The case for model-driven interpretability of delay-based congestion control protocols." ACM SIGCOMM Computer Communication Review 51, no. 1 (2021): 18–25. http://dx.doi.org/10.1145/3457175.3457179.

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Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a Model-Driven Interpretability (MDI) congestion control framework, which derives a model version of a delay-based protocol by simplifying a congestion control protocol's response into a guided random walk over a two-dimensional Markov model. We demonstrate the case for the MDI framework by using MDI to analyze and interpret the behavior of two delay-based protoco

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11

G. Srinivasan. "Fuzzy based Congestion Control and Congestion Aware Routing Technique for IoT Networks." Journal of Information Systems Engineering and Management 10, no. 13s (2025): 160–65. https://doi.org/10.52783/jisem.v10i13s.2016.

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Introduction: In Internet of Things (IoT) networks, the existing congestion control mechanisms did not often scale efficiently or maintain the heterogeneity of devices, causing performance bottlenecks and uneven network performance. Existing congestion control protocols may not adjust well to these dynamics, causing increased packet loss, suboptimal performance, and higher latency. Objectives: The main objectives of this work are to detect congestion at node level or link level and to determine congestion aware routing paths. Methods: A Fuzzy-based congestion control and congestion aware routi

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12

Song, Yaqin, Hong Ni, and Xiaoyong Zhu. "Two-Level Congestion Control Mechanism (2LCCM) for Information-Centric Networking." Future Internet 13, no. 6 (2021): 149. http://dx.doi.org/10.3390/fi13060149.

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As an emerging network architecture, Information-Centric Networking (ICN) is considered to have the potential to meet the new requirements of the Fifth Generation (5G) networks. ICN uses a name decoupled from location to identify content, supports the in-network caching technology, and adopts a receiver-driven model for data transmission. Existing ICN congestion control mechanisms usually first select a nearby replica by opportunistic cache-hits and then insist on adjusting the transmission rate regardless of the congestion state, which cannot fully utilize the characteristics of ICN to improv

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13

Diao, Wenlan, Jianping An, Tong Li, Yu Zhang, and Zhoujie Liu. "Lossless and High-Throughput Congestion Control in Satellite-Based Cloud Platforms." Electronics 14, no. 6 (2025): 1206. https://doi.org/10.3390/electronics14061206.

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Low Earth Orbit (LEO) satellite networks are promising for satellite-based cloud platforms. Due to frequent link switching and long transmission distances in LEO satellite networks, applying the TCP/IP architecture introduces challenges such as packet loss and significant transmission delays. These issues can trigger excessive retransmissions, leading to link congestion and increased data acquisition delay. Deploying Named Data Networking (NDN) with connectionless communication and link-switching tolerance can help address these problems. However, the existing congestion control methods in NDN

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14

Xie, Jun, Lu Yu, and Feng-lin Jin. "Congestion Control Based on Queuing Delay and Packet Loss Probability." Journal of Electronics & Information Technology 32, no. 9 (2010): 2058–64. http://dx.doi.org/10.3724/sp.j.1146.2009.01228.

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15

., Amardeep, Devendar Gahlot, and H. S. Bindra. "Buffer based Analysis of Congestion Control in Delay Tolerant Network." International Journal of Computer Sciences and Engineering 6, no. 10 (2018): 561–67. http://dx.doi.org/10.26438/ijcse/v6i10.561567.

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16

Rodriguez-Perez, M., S. Herreria-Alonso, M. Fernandez-Veiga, A. Suarez-Gonzalez, and C. Lopez-Garcia. "Achieving fair network equilibria with delay-based congestion control algorithms." IEEE Communications Letters 12, no. 7 (2008): 535–37. http://dx.doi.org/10.1109/lcomm.2008.080372.

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17

Rathod, Vishal, Natasha Jeppu, Samanvita Sastry, Shruti Singala, and Mohit P. Tahiliani. "CoCoA++: Delay gradient based congestion control for Internet of Things." Future Generation Computer Systems 100 (November 2019): 1053–72. http://dx.doi.org/10.1016/j.future.2019.04.054.

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18

Liu, Yan, Kun Wang, Huang Guo, Qing Lu, and Yanfei Sun. "Social-Aware Computing based Congestion Control in Delay Tolerant Networks." Mobile Networks and Applications 22, no. 2 (2016): 174–85. http://dx.doi.org/10.1007/s11036-016-0759-8.

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19

Zhu, Hong Gao, and Qi Feng. "Network Video Transmission Quality Assurance Algorithm Based on Congestion Control." Applied Mechanics and Materials 347-350 (August 2013): 849–53. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.849.

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Time delay and packet loss rate during the network video transmission are the two important factors in network video transmission quality. The purpose of congestion control is to reduce the bad impact of network video transmission quality caused by time delay and packet loss rate. This paper proposed a network video transmission quality assurance algorithm based on unbalanced multiple descriptions coding scheme. The new algorithm predicts the congestion state of network by means of Markov model based on available bandwidth detection, changes video transmission path on the basis of the predicti

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20

Mohan, S., and P. Vimala. "Enhancing Congestion Control and QoS Scheduling Using Novel Rate Aware-Neuro-Fuzzy Algorithm in MANET." WSEAS TRANSACTIONS ON COMMUNICATIONS 22 (July 20, 2023): 58–74. http://dx.doi.org/10.37394/23204.2023.22.6.

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Mobile Ad Hoc Networks (MANET) provides a vibrant atmosphere wherein data may be substituted deprived of the necessity of human authority or a centralized server, as long as nodes work together for routing. As long as security throughout the multipath routing protocol and data transfer over many routes in a MANET is a difficult problem, this work offers a message security technique. This study presents the congestion control and QoS scheduling mechanism. The goal of this study is to examine standardized MAC protocols on MANET, to measure performance under various node densities and MAC protoco

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21

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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22

NOGUCHI, Masahiro, Daisuke SUGAHARA, and Miki YAMAMOTO. "Timer-Based Increase and Delay-Based Decrease Algorithm for RDMA Congestion Control." IEICE Transactions on Communications E105.B, no. 4 (2022): 421–31. http://dx.doi.org/10.1587/transcom.2021wwp0005.

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23

Yu, Xiao Hu. "An Improved Congestion Control Mechanism Based on Mobile Agent for Wireless Sensor Networks." Applied Mechanics and Materials 519-520 (February 2014): 1239–42. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1239.

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An improved congestion control mechanism based on mobile agent for wireless sensor networks is proposed, which includes node-level congestion and link-level congestion control. The formers congestion information is collected and distributed by mobile agents (MA). When mobile agent travels through the networks, it can select a less-loaded neighbor node as its next hop and update the routing table according to the nodes congestion status. Minimum package of node outgoing traffic was preferentially transmitted in the link-level congestion. Simulation result shows that proposed mechanism attains h

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24

Beulah Jayakumari, R., and V. Jawahar Senthilkumar. "Priority Based Congestion Control Dynamic Clustering Protocol in Mobile Wireless Sensor Networks." Scientific World Journal 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/596138.

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Wireless sensor network is widely used to monitor natural phenomena because natural disaster has globally increased which causes significant loss of life, economic setback, and social development. Saving energy in a wireless sensor network (WSN) is a critical factor to be considered. The sensor nodes are deployed to sense, compute, and communicate alerts in a WSN which are used to prevent natural hazards. Generally communication consumes more energy than sensing and computing; hence cluster based protocol is preferred. Even with clustering, multiclass traffic creates congested hotspots in the

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25

Kim, Geon-Hwan, Yeong-Jun Song, Imtiaz Mahmud, and You-Ze Cho. "Adaptive Decrease Window for BALIA (ADW-BALIA): Congestion Control Algorithm for Throughput Improvement in Nonshared Bottlenecks." Electronics 10, no. 3 (2021): 294. http://dx.doi.org/10.3390/electronics10030294.

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The main design goals of the multipath transmission control protocol (MPTCP) are to improve the throughput and share a common bottleneck link fairly with a single-path transmission control protocol (TCP). The existing MPTCP congestion control algorithms achieve the goal of fairness with single-path TCP flows in a shared bottleneck, but they cannot maximize the throughput in nonshared bottlenecks, where multiple subflows traverse different bottleneck links. This is because the MPTCP is designed not to exceed the throughput of a single-path TCP competing in the bottleneck. Therefore, we believe

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26

Ahsan, Muhammad, and Sajid S. Muhammad. "TCP BBR-n interplay with modern AQM in Wireless-N/AC networks: Quest for the golden pair." PLOS ONE 19, no. 9 (2024): e0304609. http://dx.doi.org/10.1371/journal.pone.0304609.

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Effective congestion control on the internet has been a problem since its inception. Transmission Control Protocol (TCP), being the most widely used transport layer protocol tries to mitigate it using a variety of congestion control algorithms. Cubic, Reno, and Bottleneck Bandwidth and Round-trip propagation time (BBR) are the most deployed congestion controls. BBR v2 is leading the congestion control race with its superior performance in terms of better throughput and lower latency. Furthermore, Active Queue Management (AQM) algorithms try to mitigate the congestion control at the network lay

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27

Ishikura, Shotaro, and Miki Yamamoto. "Adaptive time window improving convergence of practical delay-based congestion control." IEICE Communications Express 10, no. 8 (2021): 533–37. http://dx.doi.org/10.1587/comex.2021etl0038.

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28

ZHAO, Guang-Song, and Ming CHEN. "Congestion Control Mechanism Based on Accepting Threshold in Delay Tolerant Networks." Journal of Software 24, no. 1 (2014): 153–63. http://dx.doi.org/10.3724/sp.j.1001.2013.04218.

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29

Al-Saadi, Rasool, Grenville Armitage, Jason But, and Philip Branch. "A Survey of Delay-Based and Hybrid TCP Congestion Control Algorithms." IEEE Communications Surveys & Tutorials 21, no. 4 (2019): 3609–38. http://dx.doi.org/10.1109/comst.2019.2904994.

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30

Najmuddin, Sayed, Muhammad Asim, Kashif Munir, Thar Baker, Zehua Guo, and Rajiv Ranjan. "A BBR-based congestion control for delay-sensitive real-time applications." Computing 102, no. 12 (2020): 2541–63. http://dx.doi.org/10.1007/s00607-020-00829-2.

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31

Et al., Amit Grover. "Diverse Congestion Control Schemes for Wireless Sensor Networks." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 2380–89. http://dx.doi.org/10.17762/turcomat.v12i6.5401.

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Wireless Sensor Networks (WSNs) comprised of battery operated sensor nodes that collect data from their neighbor nodes and transmit the aggregated information to the sink node or the Base Station (BS). This may result in congestion near the BS and leads to a bottleneck situation in the network. In this paper, an extensive study of earlier reported diverse congestion techniques explicitly diverse Algorithm based - and Layer based-congestion techniques is carried out. Accordingly, a recommendation is drawn based upon their performance comparison. Furthermore, a demonstration is carried out for c

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32

Khodhair, Saadi Alobaidi, Majid S. Naghmash, Riyadh Bassil Abduljabbar, and Ali Amer Ahmed ALRawi. "Minimum Delay Congestion Control in Differentiated Service Communication Networks." Open Electrical & Electronic Engineering Journal 12, no. 1 (2018): 42–51. http://dx.doi.org/10.2174/1874129001812010042.

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Introduction:This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.Methods:The effectiveness of the suggested congestion controller system is demonstrated with mathematical consequences in formal framework by using modified sliding controller (MSMC) te

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33

Luo, Yi, Min Wang, Deteng Zhao, and Chun Liu. "Performance analysis of congestion control protocols over 5G mmWave links." Journal of Physics: Conference Series 2221, no. 1 (2022): 012006. http://dx.doi.org/10.1088/1742-6596/2221/1/012006.

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Abstract Millimeter wave technology is an important basic technology in 5G applications. It has higher bandwidth and lower delay. But high dynamics of the channel poses a major challenge to the design of congestion control protocols. Based on ns3, this paper conducts extensive experiments on the TCP congestion control protocols, and analyzes the transmission performance of different protocols over 5G millimeter wave links in detail. It will lay a foundation for further research on congestion control protocols suitable for 5G millimeter wave communications.

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34

Wang, Chao. "An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 8 (2020): 1166–74. http://dx.doi.org/10.2174/2352096513999200628095848.

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Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure

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35

Dhamija, Srishti, Alolika Gon, Pradeep Varakantham, and William Yeoh. "Online Traffic Signal Control through Sample-Based Constrained Optimization." Proceedings of the International Conference on Automated Planning and Scheduling 30 (June 1, 2020): 366–74. http://dx.doi.org/10.1609/icaps.v30i1.6682.

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Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movem

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Lakshmi, Mettu Jhansi, and Mahesh Babu Arrama. "1177Optimized Energy Utilization in Cognitive Radio Networkswith Congestion Control." International Journal of Intelligent Systems and Applications in Engineering 12, no. 22 (2024): 1177–85. http://dx.doi.org/10.36893/ijisae.2024.v12n22.6644.

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Various real-time applications can be handled through wireless sensor networks, which consist of a wide range of sensor nodes. A novel congestion control mechanism is proposed on optimized rates for energy-efficient transmissions. To reduce energy consumption across the network, a rate-based congestion control algorithm based on cluster routing is presented. By reducing the end-to-end delay, rate control improves the network life time over a large simulation period. Clustering is initially performed using novel routing algorithms. After that, rate control is implemented using an energy optimiz

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37

Ardestani, Mahdi Alinaghizadeh. "Delay Based Robust H∞ Control Algorithm for TCP Networks Congestion Control to Disturbance Attenuation." International Journal of Control and Automation 9, no. 11 (2016): 77–92. http://dx.doi.org/10.14257/ijca.2016.9.11.07.

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38

Ding, Dawei, Chun Wang, Lianghui Ding, Nian Wang, and Dong Liang. "Hopf Bifurcation Control in a FAST TCP and RED Model via Multiple Control Schemes." Journal of Control Science and Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/8342652.

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We focus on the Hopf bifurcation control problem of a FAST TCP model with RED gateway. The system gain parameter is chosen as the bifurcation parameter, and the stable region and stability condition of the congestion control model are given by use of the linear stability analysis. When the system gain passes through a critical value, the system loses the stability and Hopf bifurcation occurs. Considering the negative influence caused by Hopf bifurcation, we apply state feedback controller, hybrid controller, and time-delay feedback controller to postpone the onset of undesirable Hopf bifurcati

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39

Keerti Mishra. "Delay Driven Machine Learning Scheme for TCP Data Flow Performance Enhancement." Advances in Nonlinear Variational Inequalities 28, no. 7s (2025): 112–23. https://doi.org/10.52783/anvi.v28.4488.

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Wireless networks with a substantial Bandwidth Delay Product (BDP) often use the Transmission Control Protocol (TCP) for conventional data delivery. However, TCP expands the congestion window dramatically, often resulting in ineffective bandwidth consumption. Furthermore, its congestion monitoring system adds to significant packet loss, a problem increased by improved network devices and the growing Internet. This paper presents an intelligent solution to congestion control that uses machine learning models to automatically change the number of virtual parallel streams. This approach improves

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40

Preye, Uguta Henry, and Onyejegbu Laeticia Nneka. "An Intelligent Fuzzy Logic System for Network Congestion Control." Circulation in Computer Science 2, no. 11 (2017): 23–30. http://dx.doi.org/10.22632/ccs-2017-252-69.

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Network congestion is a major problem in all network environments as such it calls for ways to manage this problem. In this paper, we propose a Fuzzy Regulator Effective Random Early Detection (FRERED) system, which is an intelligent fuzzy logic based controller technique for early stage congestion detection, at the router buffer in the networks. The proposed technique extends the Fuzzy-Based system in the Fuzzy Hybrid ERED algorithm by considering the delay variable in its inference system to ease the problem of parameter initialization and parameter dependency. Unlike the Fuzzy-Based control

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41

Fan, Xun Li, Fei Fei Du, and Zhen Hua Xie. "Input-Rate Based Adaptive Fuzzy Neuron PID Control for AQM." Advanced Materials Research 846-847 (November 2013): 3–8. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.3.

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Internet routers play an important role during network congestion. All the routers have buffers at input and output ports to hold the packets at congestion. Various congestion control algorithms have been proposed to control the congestion. Recently, some proportional-integral-derivative (PID) controller based algorithms have been proposed as Active Queue Management (AQM) schemes to address performance degradations of end-to-end TCP congestion control. However, most of the proposed PID-controllers for AQM are validated for their performance and stability via intuitive explanation and simulatio

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42

Sebastiyar, Jaya Pratha, and Martin Sahayaraj Joseph. "Routing Optimization with Efficient Second Order Distributed Approach Using Congestion Control Rules." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (2017): 363. http://dx.doi.org/10.23956/ijarcsse/v7i7/0208.

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Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fa

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43

Yang, Shuang, Yuquan Tang, Wansu Pan, Huadong Wang, Dandan Rong, and Zhirong Zhang. "Optimization of BBR Congestion Control Algorithm Based on Pacing Gain Model." Sensors 23, no. 9 (2023): 4431. http://dx.doi.org/10.3390/s23094431.

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In 2016, Google proposed a congestion control algorithm based on bottleneck bandwidth and round-trip propagation time (BBR). The BBR congestion control algorithm measures the network bottleneck bandwidth and minimum delay in real-time to calculate the bandwidth delay product (BDP) and then adjusts the transmission rate to maximize throughput and minimize latency. However, relevant research reveals that BBR still has issues such as RTT unfairness, high packet loss rate, and deep buffer performance degradation. This article focuses on its most prominent RTT fairness issue as a starting point for

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44

T.A., Komolafe, Oladimeji O.A., Adiamo O.O., Oyebode O.O., and Oyeniyi R.O.A. "A Simulation-Based Comparative Study of Controlled Delay (Codel) with Random early Detection (Red) for Network Performance Evaluation." British Journal of Computer, Networking and Information Technology 6, no. 1 (2023): 1–10. http://dx.doi.org/10.52589/bjcnit-nmhj4s4q.

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The rising need to use the internet for time/delay-sensitive applications with different Quality of Service (QOS) requirements has made network management and control even more challenging. The current congestion avoidance and control mechanisms for Transport Control Protocol (TCP) are insufficient to offer good service in all circumstances. A few decades ago, the TCP successfully regulated Internet congestion control. However, it is already widely acknowledged that TCP has reached its limits and that new congestion control protocols will be required in the near future. This has prompted a sig

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45

Hari K, Kokula Krishna, and Long Cai. "Enhancement of TCP congestion control based on relative delay and Bandwidth Estimation." Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology 2, no. 2 (2012): 47–62. http://dx.doi.org/10.14257/ajmscahs.2012.12.01.

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46

Wang, Jingyuan, Jiangtao Wen, Chao Li, Zhang Xiong, and Yuxing Han. "DC-Vegas: A delay-based TCP congestion control algorithm for datacenter applications." Journal of Network and Computer Applications 53 (July 2015): 103–14. http://dx.doi.org/10.1016/j.jnca.2015.03.010.

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47

Yan, Hongcheng, Qingjun Zhang, and Yong Sun. "Local information-based congestion control scheme for space delay/disruption tolerant networks." Wireless Networks 21, no. 6 (2015): 2087–99. http://dx.doi.org/10.1007/s11276-015-0911-6.

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48

Zhang, Yueping, Yong Xiong, Steve Liu, and Dmitri Loguinov. "Queuing dynamics and single-link stability of delay-based window congestion control." Computer Networks 54, no. 10 (2010): 1543–53. http://dx.doi.org/10.1016/j.comnet.2009.10.011.

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49

Rodríguez-Pérez, M., S. Herrería-Alonso, M. Fernández-Veiga, and C. López-García. "Common problems in delay-based congestion control algorithms: a gallery of solutions." European Transactions on Telecommunications 22, no. 4 (2011): 168–78. http://dx.doi.org/10.1002/ett.1485.

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Bhukya, Sreenu Naik, and Chandra Sekhara Rao Annavarapu. "Hybrid Reliable Clustering Algorithm with Heterogeneous Traffic Routing for Wireless Sensor Networks." Sensors 25, no. 3 (2025): 864. https://doi.org/10.3390/s25030864.

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Abstract:

Wireless sensor networks (WSNs) are vulnerable to several challenges. Congestion control, the utilization of trust to ensure security, and the incorporation of clustering schemes demand much attention. Algorithms designed to deal with congestion control fail to ensure security and address challenges faced due to congestion in the network. To resolve this issue, a Hybrid Trust-based Congestion-aware Cluster Routing (HTCCR) protocol is proposed to effectively detect attacker nodes and reduce congestion via optimal routing through clustering. In the proposed HTCCR protocol, node probability is de

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