DocumentCode :
22555
Title :
A Note on “Orchestrating an Ensemble of MapReduce Jobs for Minimizing Their Makespan”
Author :
Wenhong Tian ; Yu Chen ; Xinyang Wang
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume :
11
Issue :
4
fYear :
2014
fDate :
July-Aug. 2014
Firstpage :
390
Lastpage :
391
Abstract :
In paper [1], a scheduling model is considered for multiple MapReduce jobs. The goal in [1] is to design an automatic job scheduler that minimizes the makespan of such a set of MapReduce jobs. In this work, we find that there is a key assumption in [1] which leads to the violation of the conditions for classical Johnson´s algorithm and a suboptimal job scheduling for minimizing total makespan. By considering a better strategy and implementation, we can still meet the conditions of classical Johnson´s algorithm. Then we can still use Johnson´s algorithm for an optimal solution. As for BalancedPools algorithm proposed in paper [1], under our proposed new strategy, it is possible to solve it exactly in linear time, but not NP-hard as suggested in [1], the proof is provided. With the new strategy, results obtained in [1] need reevaluating.
Keywords :
computational complexity; minimisation; parallel programming; scheduling; BalancedPools algorithm; Johnson algorithm; MapReduce jobs; NP-hard problem; automatic job scheduler; linear time complexity; makespan minimization; scheduling model; suboptimal job scheduling; Algorithm design and analysis; Clustering algorithms; Computational modeling; Educational institutions; Processor scheduling; Schedules; Software algorithms; Hadoop; MapReduce; batch workloads; minimized makespan; optimized schedule;
fLanguage :
English
Journal_Title :
Dependable and Secure Computing, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5971
Type :
jour
DOI :
10.1109/TDSC.2013.55
Filename :
6682908
Link To Document :
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