计算机工程 ›› 2019, Vol. 45 ›› Issue (10): 19-25,32.doi: 10.19678/j.issn.1000-3428.0054041

所属专题: 云计算专题

• 云计算专题 • 上一篇    下一篇

一种近似最小有效瓶颈优先的Coflow调度机制

李文信1, 周晓波2, 徐仁海2, 齐恒1, 李克秋2   

  1. 1. 大连理工大学 计算机科学与技术学院, 辽宁 大连 116024;
    2. 天津大学 智能与计算学部, 天津 300350
  • 收稿日期:2019-03-01 修回日期:2019-05-03 出版日期:2019-10-15 发布日期:2019-05-31
  • 作者简介:李文信(1991-),男,博士,主研方向为云计算、大数据技术;周晓波,副教授;徐仁海,博士研究生;齐恒,副教授;李克秋,教授、博士生导师。
  • 基金项目:
    国家重点研发计划(2016YFB1000205);国家自然科学基金重点项目(61432002)。

An Approximate Smallest-Effective-Bottleneck-First Coflow Scheduling Mechanism

LI Wenxin1, ZHOU Xiaobo2, XU Renhai2, QI Heng1, LI Keqiu2   

  1. 1. School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China;
    2. College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
  • Received:2019-03-01 Revised:2019-05-03 Online:2019-10-15 Published:2019-05-31

摘要: 针对先验知识未知场景下的Coflow调度问题,提出一种近似最小有效瓶颈优先的Coflow调度方法。通过结合Coflow当前大小和宽度决定Coflow的调度顺序,并区分出流大小以及短与长等特征的Coflow,从而加大调度优化的空间。实验结果表明,与先验知识未知场景下的Aalo方法相比,该方法可使Coflow的平均完成时间降低33.2%,相较于先验知识已知场景下的SEBF方法,Coflow平均完成时间与其仅有7.3%的性能差距。

关键词: 数据中心, 并行计算, Coflow调度, 流量调度, 近似最小有效瓶颈优先

Abstract: Aiming at the Coflow scheduling problem in the prior knowledge unknown scene,an Approximate Smallest-Effective-Bottleneck-First(A-SEBF) Coflow scheduling method is proposed.Coflow's scheduling order is determined by combining the current size and width of Coflow,and the Coflow is characterized by large and small flows,as well as features such as fat,short and thin,so as to increase the space for scheduling optimization.Experimental results show that compared with the Aalo method in the prior knowledge unknown scene,the method can reduce the average completion time of Coflow by 33.2%.Compared with the SEBF method in the prior knowledge known scene,the average completion time of Coflow lags only 7.3% in performance.

Key words: data center, parallel computing, Coflow scheduling, flow scheduling, Approximate Smallest-Effective-Bottleneck-First(A-SEBF)

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