Home > Published Issues > 2023 > Volume 18, No. 4, April 2023 >

Improving the TCP Newreno Congestion Avoidance Algorithm on 5G Networks

Saleh M. Abdullah1*, Mohamed S. Farag1, Hatem Abdul-Kader,2, and S. E. Abo-Youssef1,
1.Al-Azhar University, Department of Mathematics and Computer Science, Faculty of Science, Cairo, Egypt
2.Menoufia University, Information Systems, Faculty of Computers and Information, Menoufia, Egypt

Manuscript received September 5, 2022; revised November 9, 2022, accepted November 28, 2022.

Abstract—Enhancing Transmission Control Protocol (TCP) performance is one of the key solutions for improving the performance of modern wireless communication networks. It is a highly dependable protocol for communication between network hosts based on an internet protocol (IP). It uses packet sequence numbering and acknowledgment (ACK) packets to ensure that data is recoverable in the event of problems like data loss, and corruption. Loss-based Congestion Control (CC) algorithms overreact and underperform in the presence of rapid channel oscillations, resulting in buffer bloat and significant delays. The goal of this paper is to develop an efficient congestion control mechanism for the new TCP agent Newreno over the fifth generation (5G) network, as well as to improve the increment and decrement strategy for adjusting the congestion window (cwnd) during the congestion avoidance phase, It also fast adapts to the current network requirements and adjusts the transmission rate accordingly. TCP enhancements can improve performance under dynamic traffic loads and over long product channels with high bandwidth. As a result, when such a TCP congestion control mechanism is improved, the network’s throughput increases, and low packet losses, and delay are reduced.

Keywords—TCP, congestion control, 5G networks, Newreno

Cite: Saleh M. Abdullah, Mohamed S. Farag, Hatem Abdul-Kader, and S. E. Abo-Youssef, "Improving the TCP Newreno Congestion Avoidance Algorithm on 5G Networks," Journal of Communications vol. 18, no. 4, pp. 228-235, April 2023. Doi: 10.12720/jcm.18.4.228-235.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.