MFBBR: An Optimized Fairness-aware TCP-BBR Algorithm in Wired-cum-wireless Network

Jia, Minghan; Sun, Weifeng; Wang, Zun; Yan, Yaohua; Qin, Hongyu; Meng, Kelong

doi:10.1109/infocomwkshps50562.2020.9163004

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…To improve the fairness between the streams using TCP-BBR congestion control algorithm and the ones using delaybased congestion control algorithm, Jia et al [18] proposed a TCP-BBR-based congestion control algorithm, which has moderate fairness and is called Modest Fairness BBR (MFBBR). The simulation results on Mininet showed that the algorithm can improve the fairness of BBR when coexisting with Westwood 3 Wireless Communications and Mobile Computing (a congestion control algorithm based on time delay) [19] and it has better fairness than the delay-based congestion control algorithm.…”

Section: Related Research On Bbr Congestion Control Algorithmmentioning

confidence: 99%

A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC

Han

Zuo

Yuan

et al. 2022

Wireless Communications and Mobile Computing

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Congestion control is a fundamental technology to balance the traffic load and the network. The Internet Engineering Task Force (IETF) Quick UDP Internet Connection (QUIC) protocol has flexible congestion control and at the same time possesses the advantages of high efficiency, low latency, and easy deployment at the application layer. Bottleneck bandwidth and round-trip propagation time (BBR) is an optional congestion control algorithm adopted by QUIC. BBR can significantly increase throughput and reduce latency, in particular over long-haul paths. However, BBR results in high packet loss in low bandwidth and low fairness in multi-stream scenarios. In this article, we propose the enhanced BBR congestion control (eBCC) algorithm, which improves the BBR algorithm in two aspects: (1) 10.87% higher throughput and 74.58% lower packet loss rate in the low-bandwidth scenario and (2) 8.39% higher fairness in the multi-stream scenario. This improvement makes eBCC very suitable for IoT communications to provide better QoS services.

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Section: Related Research On Bbr Congestion Control Algorithmmentioning

confidence: 99%

A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC

Han

Zuo

Yuan

et al. 2022

Wireless Communications and Mobile Computing

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“…As described in the literature [53], Jain's fairness index is used to measure equity. Equation (17) shows a method to calculate Jain's fairness index.…”

Section: Multiple Flows With Different Start Times and Buffer Sizesmentioning

confidence: 99%

“…Mathis et al [7] claimed that BBR opens a new era in congestion control and obsoletes Jacobson88. However, some evaluations [12][13][14][15][16][17][18] found that there are some problems in BBR, such as the unfairness when BBR and Reno/CUBIC share bottlenecks, the intraprotocol fairness, and RTT fairness. For the problem of the BBR algorithm, researchers are also making continuous efforts to obtain better performance by modifying some control parameters of BBR [19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Improvement of BBRv2 Congestion Control Algorithm Based on Flow-aware ECN

Pan

Tan

et al. 2022

Security and Communication Networks

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Google proposed a new congestion control algorithm (CCA) based on bottleneck bandwidth and round-trip propagation time (BBR), which is considered to open a new era of congestion control. BBR creates a network path model by measuring the available bottleneck bandwidth and the minimum round-trip time (RTT) to maximize delivery rate and minimize latency. The BBR v2 algorithm is a recently updated version by Google, which aims to improve some of the problems in the original BBR (BBRv1) algorithm, such as interprotocol fairness issues, RTT fairness issues, and excessive retransmissions. The BBRv2 evaluation results show that it can improve the coexistence with the loss_based algorithm and alleviate some of the shortcomings in BBRv1. However, when multiple BBRv2 flows enter the same link at different times, fair convergence cannot be achieved, and RTT fairness still exists. Based on these problems, we analyze the root cause and proposed an improved algorithm BBRv2+, which uses flow-aware explicit congestion notification (ECN) to quantify queue information and feedback on the accurate congestion degree. BBRv2+ algorithm can avoid blind window constraints and selectively mark packets so that different flows can converge to fairness. In the simulation experiment of Network Simulator 3 (NS3), the results show that the BBRv2+ algorithm can improve intraprotocol fairness and RTT fairness and ensure bandwidth utilization and interprotocol fairness.

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“…We refer to the analysis of the complexity of the congestion control algorithm in literature [ 20 ]. The time complexity of the algorithm reflects the magnitude of the increase of program execution time with the increase of input size.…”

Section: The Proposed Algorithm: Bbr-gcmentioning

confidence: 99%

“…Aware of the problem of BBR algorithm, some scholars have modified the regulation factors of BBR to improve the defects of BBR itself [ 15 , 16 , 17 ]. On the other hand, BBR is applied to different network domains to achieve a better performance [ 18 , 19 , 20 , 21 ]. Google is also constantly optimizing BBR algorithm and updating BBR v2 version [ 22 ] to improve coexistence with other algorithms and reduce the attack.…”

Section: Introductionmentioning

confidence: 99%

Improvement of RTT Fairness Problem in BBR Congestion Control Algorithm by Gamma Correction

Pan

Tan

et al. 2021

Sensors

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Google proposed the bottleneck bandwidth and round-trip propagation time (BBR), which is a new congestion control algorithm. BBR creates a network path model by measuring the available bottleneck bandwidth and the minimum round-trip time (RTT) to maximize delivery rate and minimize latency. However, some studies have shown that there are serious RTT fairness problems in the BBR algorithm. The flow with longer RTT will consume more bandwidth and the flows with shorter RTT will be severely squeezed or even starved to death. Moreover, these studies pointed out that even small RTT differences will lead to the throughput of BBR flows being unfair. In order to solve the problem of RTT fairness, an improved algorithm BBR-gamma correction (BBR-GC) is proposed. BBR-GC algorithm takes RTT as feedback information, and then uses the gamma correction function to fit the adaptive pacing gain. This approach can make different RTT flows compete for bandwidth more fairly, thus alleviating the RTT fairness issue. The simulation results of Network Simulator 3 (NS3) show that that BBR-GC algorithm cannot only ensure the channel utilization, but also alleviate the RTT fairness problem of BBR flow in different periods. Through the BBR-GC algorithm, RTT fairness is improved by 50% and the retransmission rate is reduced by more than 26%, compared with that of the original BBR in different buffer sizes.

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MFBBR: An Optimized Fairness-aware TCP-BBR Algorithm in Wired-cum-wireless Network

Cited by 8 publications

References 7 publications

A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC

A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC

Improvement of BBRv2 Congestion Control Algorithm Based on Flow-aware ECN

Improvement of RTT Fairness Problem in BBR Congestion Control Algorithm by Gamma Correction

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