| 摘要: |
| 网络拥塞控制方法是决定网络传输性能的关键因素. 近几年, 网络不断普及、网络带宽不断增长、用户对网络性能的需求不断提升, 为拥塞控制算法的设计带来挑战. 为适应不同的网络环境, 近期不少新颖的拥塞控制算法被研究者们提出来, 极大地提升网络的传输性能, 改善用户体验. 综述最新拥塞控制算法设计思想, 将其分为预约调度式、直接测量式、基于机器学习式以及迭代探测式4大类, 分别介绍相应的代表性拥塞控制算法, 并进一步对各种拥塞控制思想方法的优缺点进行对比和分析, 最后展望拥塞控制的未来发展方向, 以启发该领域的研究. |
| 关键词: 拥塞控制 网络环境 吞吐量 延时 数据中心 |
| DOI：10.13328/j.cnki.jos.007045 |
| 分类号: |
| 基金项目:国家重点研发计划(2022YFB2901404); 国家自然科学基金(61972421, 62132007); 华为创新研究计划旗舰项目; 湖南省优秀青年基金(2022JJ20078); 湖南省科技创新项目(2023RC3047) |
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| Survey on Network Congestion Control Algorithms |
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JIANG Wan-Chun1, LI Hao-Yang1, CHEN Han-Yu1, WANG Jie1, WANG Jian-Xin1, RUAN Chang2
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1.School of Computer Science and Engineering, Central South University, Changsha 410012, China;2.School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 411014, China
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| Abstract: |
| Network congestion control algorithms are the key factor indetermining network transport performance. In recent years, the spreading network, the growing network bandwidth, and the increasing user requirements for network performance have brought challenges to the design of congestion control algorithms. To adapt to different network environments, many novel design ideas of congestion control algorithms have been proposed recently, which have greatly improved the performance of networks and user experience. This study reviews innovative congestion control algorithm design ideas and classifies them into four major categories: reservation scheduling, direct measurement, machine learning-based learning, and iterative detection. It introduces the corresponding representative congestion control algorithms, and further compares and analyzes the advantages and disadvantages of various congestion control ideas and methods. Finally, the study looks forward to future development direction on congestion control to inspire research in this field. |
| Key words: congestion control network environment throughput delay data center |
