Hybrid Congestion Control Mechanisms for Next-Generation Communication Networks
Main Article Content
Abstract
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 adjustments of data transmission rates to mitigate congestion proactively. This strategy aims to minimize packet loss, reduce latency, and enhance throughput, addressing the needs of modern applications such as IoT and autonomous vehicles. Extensive simulations demonstrate significant improvements in network efficiency and reliability compared to traditional algorithms, contributing to the development of adaptive congestion control mechanisms that ensure consistent, high-quality service in complex network conditions.
Downloads
Article Details
Section

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
References
M. Allman, V. Paxson, W. Stevens, "TCP Congestion Control," RFC 2581, IETF, 1999. DOI: https://doi.org/10.17487/RFC2581
Allman, M., & Floyd, S. (1996). Increased TCP Performance for Large Transfers. In ACM SIGCOMM Computer Communication Review (Vol. 26, No. 4, pp. 259-268). DOI: https://doi.org/10.1145/293927.295114.
L. S. Brakmo, L. L. Peterson, "TCP Vegas: End-to-End Congestion Avoidance on a Global Internet," IEEE Journal on Selected Areas in Communications, vol. 13, no. 8, pp. 1465-1480, Oct. 1995. https://cseweb.ucsd.edu/classes/wi01/cse222/papers/brakmo-vegas-jsac95.pdf
C. P. Fu, S. C. Liew, "TCP Veno: TCP Enhancement for Transmission Over Wireless Access Networks," *IEEE Journal on Selected Areas in Communications, vol. 21, no. 2, pp. 216-228, Feb. 2003. DOI: https://doi.org/10.1109/JSAC.2002.807347.
K. Tan, J. Song, Q. Zhang, M. Sridharan, "A Compound TCP Approach for High-speed and Long Distance Networks," in Proc. of IEEE INFOCOM, 2006. DOI: https://doi.org/10.1109/INFOCOM.2006.188 .
Xu, L., & Wang, H. (2004). TCP Illinois: A New TCP Congestion Control Algorithm for High-Speed Networks. In Proceedings of the 2004 IEEE International Conference on Communications (ICC 2004) (pp. 2702-2706). DOI: https://doi.org/10.1145/1190095.1190166
N. Cardwell, Y. Cheng, C. S. Gunn, S. H. Yeganeh, V. Jacobson, "BBR: Congestion-Based Congestion Control," Communications of the ACM, vol. 60, no. 2, pp. 58-66, Feb. 2017. DOI: https://doi.org/10.1145/3009824
N. Cardwell, Y. Cheng, V. Jacobson, I. Swett, B. H. V. Jacobson, "BBRv2: A Model-based Congestion Control," ACM SIGCOMM Computer Communication Review, vol. 51, no. 4, pp. 44-52, Oct. 2021. https://datatracker.ietf.org/meeting/105/materials/slides-105-iccrg-bbr-v2-a-model-based-congestion-control-00
Cardwell, N., Cheng, Y., & Jacobson, V. (2013). TCP Recent Acknowledgment (TCP RACK). In Proceedings of the 2013 IEEE 14th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) (pp. 1-6). DOI: https://doi.org/10.1109/WoWMoM.2013.6583543.
Rizzo, L., & S. & M. (2019). TCP Prague: A TCP Congestion Control Algorithm for High Speed Networks. In Proceedings of the ACM SIGCOMM 2019 Conference (pp. 1-12). DOI: https://doi.org/10.1145/3341302.3342057.
K. Anbazhagan, T. Lakshman, R. Rajaraman, "Machine Learning-Based Congestion Control for 5G Networks," IEEE Transactions on Mobile Computing, vol. 20, no. 5, pp. 2003-2017, 2021. DOI: https://doi.org/10.1155/2022/1781952
Verma, L. P., & Kumar, M. (2020). An IoT based Congestion Control Algorithm. Internet of Things, 9, 100157. DOI: https://doi.org/10.1016/j.iot.2019.100157.
Mishra, N., Verma, L. P., Srivastava, P. K., & Gupta, A. (2018). An Analysis of IoT Congestion Control Policies. Procedia Computer Science, 132, 444-450. DOI: https://doi.org/10.1016/j.procs.2018.05.158.
Verma, L. P., Sharma, V. K., Kumar, M., & Kanellopoulos, D. (2022). A novel Delay-based Adaptive Congestion Control TCP variant. Computers and Electrical Engineering, 101. DOI: https://doi.org/10.1016/j.compeleceng.2022.108076
Mishra, N., Verma, L. P., & Kumar, M. (2019). Comparative Analysis of Transport Layer Congestion Control Algorithms. In 2019 International Conference on Cutting-edge Technologies in Engineering (ICon-CuTE) (pp. 46-49). Uttar Pradesh, India. DOI: http://dx.doi.org/10.1109/ICon-CuTE47290.2019.8991530
Patil, M. R., & Agilandeeswari, L. (2019). Rate Based Congestion Control for Wireless Links in Information Centric Network. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 1s3, pp. 1–5). DOI: https://doi.org/10.35940/ijeat.a1001.1291s319
Swarna, M., & GODHAVARI, Dr. T. (2019). Coap Based Congestion Control Mechanism For Low Power Iot Networks. In International Journal of Innovative Technology and Exploring Engineering (Vol. 8, Issue 10, pp. 958–962). DOI: https://doi.org/10.35940/ijitee.j9114.0881019
Shanthini, S., & Devakumari, Dr. D. (2020). Red Congestion Control with Energy Aware Auction Based
Route Selection in MANET. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 5, pp. 1970–1974). DOI: https://doi.org/10.35940/ijrte.e5933.018520