Transmission control protocol congestion control switching scheme based on scenario change

doi:10.11772/j.issn.1001-9081.2021050722

Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (4): 1225-1234.DOI: 10.11772/j.issn.1001-9081.2021050722

Special Issue: CCF第36届中国计算机应用大会 (CCF NCCA 2021)

• The 36 CCF National Conference of Computer Applications (CCF NCCA 2020) • Previous Articles Next Articles

Transmission control protocol congestion control switching scheme based on scenario change

Hanguang LAI¹, Qing LI², Yong JIANG¹()

^1.Shenzhen International Graduate School，Tsinghua University，Shenzhen Guangdong 518055，China
^2.Institute of Future Networks，Southern University of Science and Technology，Shenzhen Guangdong 518055，China

Received:2021-04-22 Revised:2021-06-04 Accepted:2021-06-08 Online:2021-07-22 Published:2022-04-10
Contact: Yong JIANG
About author:LAI Hanguang， born in 1995， M. S. candidate. His research interests include end-to-end intelligent transmission control.
LI Qing， born in 1985， Ph. D.， associate professor. His research interests include future network architecture and transmission protocol， end-to-end intelligent transmission control， intelligent video transmission based on edge computing.
Supported by:
Key-Area Research and Development Program of Guangdong Province(2018B010113001)

基于场景变化的传输控制协议拥塞控制切换方案

赖涵光¹, 李清², 江勇¹()

^1.清华大学深圳国际研究生院，广东深圳 518055
^2.南方科技大学未来网络研究院，广东深圳 518055

通讯作者: 江勇
作者简介:赖涵光（1995—），男，福建泉州人，硕士研究生，主要研究方向：端到端智能传输控制
李清（1985—），男，江苏徐州人，副教授，博士，主要研究方向：未来网络体系架构与传输协议、端到端智能传输控制、基于边缘计算的智能视频传输
基金资助:
广东省重点领域研发计划项目(2018B010113001)

Abstract

Abstract:

Aiming at the problem that the performance of lightweight learning-based congestion control algorithms will fall off a cliff in some scenarios， a transmission control protocol congestion control switching scheme based on scenario change was proposed. Firstly， the real-time network environment was simulated by this scheme. Then， the scenario was identified according to the real-time environment parameters. Finally， the current congestion control algorithm was switched to the relatively optimal lightweight learning-based congestion control algorithm in this scenario. Experimental results prove that the proposed scheme is able to significantly improve network performance compared to the original schemes using a single congestion control algorithm， such as congestion control based on measuring Bottleneck Bandwidth and Round-trip propagation time （BBR） and Performance-oriented Congestion Control （PCC） with a total throughput increase of more than 5% and a total delay drop of more than 10%.

Key words: congestion control, scenario change, lightweight, learning-based, Transmission Control Protocol (TCP)

摘要：

针对轻量级基于学习的拥塞控制算法在某些场景下性能表现会出现断崖式下滑的问题，提出了一种基于场景变化的传输控制协议拥塞控制切换方案。首先，该方案模拟实时的网络环境；然后，根据实时的环境参数来识别场景；最后，将当前的拥塞控制算法切换至该场景下相对最优的轻量级基于学习的拥塞控制算法。实验结果表明，所提方案相较于原来使用单个拥塞控制算法的方案，例如测量瓶颈链路带宽和时延的拥塞控制（BBR）方案、面向性能的拥塞控制（PCC）方案等，可以使不同场景下的网络性能得到显著提升，总吞吐量增幅达到5%以上，总时延降幅达到10%以上。

关键词: 拥塞控制, 场景变化, 轻量级, 基于学习, 传输控制协议

CLC Number:

TP393.0

Hanguang LAI, Qing LI, Yong JIANG. Transmission control protocol congestion control switching scheme based on scenario change[J]. Journal of Computer Applications, 2022, 42(4): 1225-1234.

赖涵光, 李清, 江勇. 基于场景变化的传输控制协议拥塞控制切换方案[J]. 《计算机应用》唯一官方网站, 2022, 42(4): 1225-1234.

Figures/Tables 13

References 25

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拥塞控制算法	平均吞吐量/（Mb·s^-1）	平均时延/ms
BBR	4.87	132
PCC-Vivace	4.49	113
Copa	4.78	106
Cubic	4.63	141

拥塞控制算法	平均吞吐量/（Mb·s^-1）	平均时延/ms
BBR	4.87	132
PCC-Vivace	4.49	113
Copa	4.78	106
Cubic	4.63	141

链路带宽/（Mb·s^-1）	网络延迟/ms	随机丢包率/%	使用算法
1~100	1	0	Vivace
	10	0	Copa
	100	0	BBR
	500	0	BBR、Copa
5	1	0.1~1	Vivace
	10	0.1~1	Copa
	100	0.1~1	BBR
	500	0.1~1	BBR、Copa

链路带宽/（Mb·s^-1）	网络延迟/ms	随机丢包率/%	使用算法
1~100	1	0	Vivace
	10	0	Copa
	100	0	BBR
	500	0	BBR、Copa
5	1	0.1~1	Vivace
	10	0.1~1	Copa
	100	0.1~1	BBR
	500	0.1~1	BBR、Copa

链路带宽/（Mb·s^-1）	网络延迟/ms	随机丢包率/%	使用算法
1~100	100	0	Vivace
1~100	100	0.1~1	Copa

Transmission control protocol congestion control switching scheme based on scenario change

基于场景变化的传输控制协议拥塞控制切换方案

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Figures/Tables 13

References 25

Related Articles 15

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Metrics

链路带宽/（Mb·s^-1）	网络延迟/ms	随机丢包率/%	使用算法
1~20	1	0	Copa
1	10	0	Copa
5	10	0	Copa、Vivace
20	10	0	Vivace
1	100	0	Vivace
1	100	0	Copa
5~20	500	0	Vivace
5~20	500	0	Copa
1	10	0.1	Copa
5	10	0.1	Vivace
20	10	0.1	Vivace
1	10	0.5~1	Copa
5	10	0.5~1	Vivace
20	10	0.5~1	Copa

链路带宽/（Mb·s^-1）	网络延迟/ms	随机丢包率/%	使用算法
1	1	0~1	Copa
5	1	0~0.5	Vivace
5	1	1	BBR
20	1	0~1	BBR
100	1	0~0.1	BBR
100	1	0.5~1	Vivace

组别	时刻	变化时刻/s	带宽/（Mb·s^-1）	延迟/ms
1	t₁	8	193	5
	t₂	243	45	17
	t₃	364	7	91
	t₄	445	5	40
2	t₁	48	19	22
	t₂	178	2	16
	t₃	285	275	1
	t₄	438	2	7
3	t₁	50	1	18
	t₂	139	172	47
	t₃	368	2	13
	t₄	447	82	2

时刻	第1组		第2组		第3组
时刻	吞吐量	时延	吞吐量	时延	吞吐量	时延
t₁	Copa	PCC-Vivace	BBR	PCC-Vivace	Copa	Copa
t₂	BBR	Copa	BBR	Copa	BBR	Copa
t₃	BBR	Copa	PCC-Vivace	Copa	Copa	Copa
t₄	BBR	Copa	Copa	Copa	PCC-Vivace	Copa

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