Joint Coflow Optimization for Data Center Networks

被引:1
|
作者
Wu, Zhaoxi [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai 200050, Peoples R China
[2] ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
关键词
Task analysis; Bandwidth; Data centers; Scheduling; Schedules; Optimization; Data models; Data center; coflow scheduling; task placement; path choice; COMPLETION-TIME; PLACEMENT;
D O I
10.1109/ACCESS.2021.3102067
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Data parallel applications in data centers generate, process, and store huge volumes of data. Coflow Completion time (CCT) is one of the major performance metrics to capture application-level semantics. This paper is the first one to study the joint consideration of task placement, coflow bandwidth scheduling, and path choice to minimize the average CCT in intra-data center. This paper proposes a joint online scheduling framework, which first develops a 2-approximation algorithm to reduce the CCT of a single coflow, and then follows the Shortest Remaining Time First (SRTF) principle to schedule multiple coflows. Extensive simulations based on practical trace demonstrate that the proposed framework has better performance than the state-of-the-art works.
引用
收藏
页码:108402 / 108410
页数:9
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