• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Hu Zhiyao, Li Dongsheng, Li Ziyang. Recent Advances in Datacenter Flow Scheduling[J]. Journal of Computer Research and Development, 2018, 55(9): 1920-1930. DOI: 10.7544/issn1000-1239.2018.20180156
Citation: Hu Zhiyao, Li Dongsheng, Li Ziyang. Recent Advances in Datacenter Flow Scheduling[J]. Journal of Computer Research and Development, 2018, 55(9): 1920-1930. DOI: 10.7544/issn1000-1239.2018.20180156

Recent Advances in Datacenter Flow Scheduling

More Information
  • Published Date: August 31, 2018
  • Flow scheduling techniques impose an important impact on the performance of the data center. Flow scheduling techniques aim at optimizing the user experience by controlling and scheduling the transmission link, priority and transmission rate of data flows. Flow scheduling techniques can achieve various optimization objects such as reducing the average or weighted flow completion time, decreasing the delay of long-tail flows, optimizing the transmission of flows with deadline constraints, improving the utilization of the network link. In this paper, we mainly review the recent research involving flow scheduling techniques. First, we briefly introduce data center and flow scheduling problem and challenges. These challenges mainly lie in the means to implement flow scheduling on network devices or terminal hosts, and how to design low-overhead highly-efficient scheduling algorithms. Especially, the coflow scheduling problem is proved NP-Hard to solve. Then, we review the latest progress of flow scheduling techniques from two aspects, i.e., single-flow scheduling and coflow scheduling. The divergence between single-flow scheduling techniques and coflow scheduling techniques is the flow relationship under different applications like Web search and big data analytics. In the end of the paper, we outlook the future development direction and point out some unsolved problems involving flow scheduling.
  • Cited by

    Periodical cited type(15)

    1. 叶进,谢紫琪,肖庆宇,宋玲,李晓欢. 数据中心网络中基于ELM的流簇大小推理机制. 计算机科学与探索. 2021(02): 261-269 .
    2. 林霄,姬硕,岳胜男,孙卫强,胡卫生. 面向跨数据中心网络的节点约束存储转发调度方法. 计算机研究与发展. 2021(02): 319-337 . 本站查看
    3. 王金焱. 异构无线网络多路径流量调度算法研究. 常熟理工学院学报. 2021(02): 70-75 .
    4. 董金良,刘小伟,李海江. 基于蚁群优化的通信网络负荷信息分散协调调度. 水电与抽水蓄能. 2021(03): 68-71 .
    5. 韩茂玲. 复杂网络大规模数据流均衡调度方法. 成都工业学院学报. 2021(03): 38-42 .
    6. 武自强,周建涛,赵大明,柳林. 数据中心基于服务满足度的网络流避让方法. 计算机工程与应用. 2021(19): 116-122 .
    7. 时洋 ,文梅 ,费佳伟 ,张春元 . 一种基于DAG的网络流量调度器. 计算机研究与发展. 2021(12): 2798-2810 . 本站查看
    8. 李文信,齐恒,徐仁海,周晓波,李克秋. 数据中心网络流量调度的研究进展与趋势. 计算机学报. 2020(04): 600-617 .
    9. 陈珂,刘亚志,王思晗. 基于流量特征的流调度策略研究综述. 计算机应用研究. 2020(10): 2889-2894 .
    10. 郑莹,段庆洋,林利祥,游新宇,徐跃东,王新. 深度强化学习在典型网络系统中的应用综述. 无线电通信技术. 2020(06): 603-623 .
    11. 柯文龙,王勇,叶苗,陈俊奇. Ceph云存储网络中一种业务优先级区分的多播流调度方法. 通信学报. 2020(11): 40-51 .
    12. 李维虎,张顶山,崔慧明,周龙,朱志挺,谢挺. 数据中心网络coflow调度机制结构构建及仿真. 电子测量技术. 2019(10): 78-81 .
    13. 康瑾,李革. 面向医院手术排程的智能规划算法研究. 信息技术. 2019(11): 37-41+45 .
    14. 孙超. 基于模糊反馈的共享网络远程数据控制仿真. 计算机仿真. 2019(10): 409-412+438 .
    15. 王远. 数据中心网络拥塞控制研究综述. 信息工程大学学报. 2019(06): 714-719 .

    Other cited types(13)

Catalog

    Article views (1855) PDF downloads (823) Cited by(28)
    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return