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数据中心网络的流量控制:研究现状与趋势 被引量:22

Traffic Control for Data Center Network:State of the Art and Future Research
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摘要 作为海量数据快速存储和高效处理强有力的后盾,数据中心成为近年来学术界和工业界关注的热点.传统TCP难以在高吞吐、低时延、无损等方面同时满足当前数据中心传输需求,新的传输技术研究迫在眉睫.本文在对比传统TCP设计目标和数据中心网络中传输目标的基础上,对数据中心流量控制的研究现状展开综述.流量控制是指控制流量的发送速度以及发送规则,本文从基于端到端设计的拥塞控制和基于全局优化的流量工程两个方面对流量控制技术进行介绍,并从控制机制、扩展性、技术可行性等方面对上述技术进行了对比分析.最后本文对数据中心流量控制技术的未来研究趋势进行了总结和展望. As a strong foundation for the rapid storage and efficient processing of massive data,the data center has become a hot spot in academia and industry in recent years.Traditional TCP is difficult to meet the demand for data center transmission in high throughput,low latency and loss-free aspects.Based on the comparison between the traditional TCP design target and the transmission target in the data center network,this paper summarizes the research status of data center traffic control.Traffic control refers to the control of traffic rates and sending rules.Therefore,this paper introduces the traffic control technology based on congestion control and traffic engineering and makes a comparative analysis of the above technology from the aspects of control mechanism,expansibility and technical feasibility.Finally,this paper summarizes and looks forward to the future research trend of data center traffic control technology.According to the existing researches,we find that:(1)Considering the cost and performance,the most suitable traffic control algorithm for TCP/IP data center is DCTCP,and the most suitable traffic control algorithm for RDMA data center is DCQCN.Other researches require expensive custom hardware,which is difficult to deploy.(2)The traffic control technology is a technology of fair utilization of limited resources.Therefore,the performance of the technology can be improved by acquiring more relevant information or exchanging with other resources.E.g.ECN,RTT,traffic size,flow deadline.(3)Among the three main research points of congestion control,flow scheduling and load balancing,the mainstream algorithm system only focuses on one or two of them.(4)Smart NICs and programmable switches are widely used in the research of the data center network.The programmability of smart devices can bring new features to new technologies.In the end,the research directions are prospected.(1)A unified flow control test platform is needed.Different algorithms use different test environments,so it is difficult to evaluate them together.(2)Congestion control,flow scheduling,and load balancing studies need to be considered together.(3)Traditional distributed traffic control cannot be accurately scheduled due to insufficient information.As data centers grow in size,centralized controllers become network bottlenecks.The tradeoff between centralized and distributed control requires careful consideration.(4)High-performance programmable smart devices need to be developed and deployed.RDMA has become a hot topic in industry and academia.At the same time,programmable network devices greatly enhance the flexibility and rapid deployment of the network.(5)Traffic control design for specific application scenarios.The performance of the algorithm is improved by acquiring more relevant information or by exchanging other related resources.More resources are available in specific application scenarios.(6)With its strong self-adaptability and self-learning ability,artificial intelligence provides a set of effective decision-making tools for various research fields.The combination of artificial intelligence technology and network transmission technology is also a hot topic in the future.In summary,with the in-depth study of the data center,traffic control will become the most important basic performance tool for the data center,especially for the future high throughput,low latency requirements.
作者 杜鑫乐 徐恪 李彤 郑凯 付松涛 沈蒙 DU Xin-Le;XU Ke;LI Tong;ZHENG Kai;FU Song-Tao;SHEN Meng(Department of Computer Science and Technology,Tsinghua University,Beijing 100084;Beijing National Research Center for Information Science and Technology,Beijing 100084;Peng Cheng Laboratory,Shenzhen,Guangdong 518000;2012 Labs,Huawei Technology Co.Ltd.,Beijing 100085;School of Computer,Beijing Institute of Technology,Beijing 100081)
出处 《计算机学报》 EI CAS CSCD 北大核心 2021年第7期1287-1309,共23页 Chinese Journal of Computers
基金 国家重点研发计划课题(2018YFB1800402) 华为技术有限公司委托项目(YBN2018065021) 国家自然科学基金(61825204,61932016,61972039) 北京高校卓越青年科学家计划项目(BJJWZYJH01201910003011) 北京市自然科学基金(4192050) 鹏城实验室大湾区未来网络试验与应用环境项目(LZC0019)资助.
关键词 数据中心 流量控制 拥塞控制 流量工程 流量调度 负载均衡 data center traffic control congestion control traffic engineering flow schedule load balance
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