Improved Bottleneck Bandwidth and Round-Trip Propagation Congestion Control Algorithm for Round-Trip Time Fairness

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-05-20 DOI:10.20965/jaciii.2023.p0346
Zhicheng Zhao, Weihua Cao
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Abstract

Traditional congestion-control algorithms based on packet loss are more favorable for short round-trip time (RTT) flows. However, when the flow occupies the bottleneck bandwidth, the effect of bottleneck bandwidth and round-trip propagation time (BBR) congestion-control algorithm is on contrary. A short RTT flow may become “starved” after multiple iterations, which leads to a significant fairness problem in the BBR. This study analyzed the convergence using the BBR algorithm principle and the effect of RTT on fairness. Thereafter, we proposed an improved algorithm termed BBR-f, constructed an inverse proportional function of RTT, and added a gain function to the congestion window (CWND) gain. A simulation experiment using the ns-3 network simulator platform shows that the algorithm can optimize fairness and improve bottleneck-linked bandwidth utilization. Finally, the Jain fair index was used to evaluate its effectiveness, and a comparison experiment with traditional algorithms was performed to verify the efficiency of the proposed method.
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基于往返时间公平性的改进瓶颈带宽和往返传播拥塞控制算法
传统的基于丢包的拥塞控制算法更适合于短往返时间(RTT)流。然而,当流量占用瓶颈带宽时,瓶颈带宽与往返传播时间(BBR)拥塞控制算法的效果相反。在多次迭代后,短RTT流可能会变得“饥饿”,这导致BBR中的严重公平性问题。本研究分析了BBR算法原理的收敛性以及RTT对公平性的影响。在此基础上,提出了改进的BBR-f算法,构造了RTT的反比函数,并在拥塞窗口(CWND)增益中增加了增益函数。在ns-3网络仿真平台上进行的仿真实验表明,该算法可以优化公平性,提高瓶颈链路带宽利用率。最后,利用Jain公平指数对该方法的有效性进行了评价,并与传统算法进行了对比实验,验证了该方法的有效性。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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