Experimental Analysis of Algorithms for Coflow Scheduling
| Autor: | Cliff Stein, Yuan Zhong, Zhen Qiu |
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| Rok vydání: | 2016 |
| Předmět: |
Theoretical computer science
Computer science Approximation algorithm 020206 networking & telecommunications 02 engineering and technology Parallel computing Scheduling (computing) 03 medical and health sciences 0302 clinical medicine Parallel communication 030220 oncology & carcinogenesis 0202 electrical engineering electronic engineering information engineering Online algorithm Completion time Heuristics SIMPLE algorithm Analysis of algorithms |
| Zdroj: | Experimental Algorithms ISBN: 9783319388502 SEA |
| Popis: | Modern data centers face new scheduling challenges in optimizing job-level performance objectives, where a significant challenge is the scheduling of highly parallel data flows with a common performance goal e.g., the shuffle operations in MapReduce applications. Chowdhury and Stoica [6] introduced the coflow abstraction to capture these parallel communication patterns, and Chowdhury et al. [8] proposed effective heuristics to schedule coflows efficiently. In our previous paper [18], we considered the strongly NP-hard problem of minimizing the total weighted completion time of coflows with release dates, and developed the first polynomial-time scheduling algorithms with O1-approximation ratios. In this paper, we carry out a comprehensive experimental analysis on a Facebook trace and extensive simulated instances to evaluate the practical performance of several algorithms for coflow scheduling, including our approximation algorithms developed in [18]. Our experiments suggest that simple algorithms provide effective approximations of the optimal, and that the performance of the approximation algorithm of [18] is relatively robust, near optimal, and always among the best compared with the other algorithms, in both the offline and online settings. |
| Databáze: | OpenAIRE |
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