Improving cluster computing performance based on job futurity prediction

Salami, Hossein; Saadatfar, Hamid; Fard, Farhad Rahmani; Shekofteh, S. Kazem; Deldari, Hossein

doi:10.1109/icacte.2010.5579820

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Because of predictor inaccuracy, there are of course a few jobs that rejected mistakenly, but in contrast, some system performance goals are achieved. The more details of these facts are shown in our pervious work [22].…”

Section: Jsm As a System Componentmentioning

confidence: 79%

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JSM: Job submission manager for large-scale distributed systems based on game theory

Saadatfar

Salami

Deldari

et al. 2010

2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)

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A bstract-Nowadays by improving the richness of prediction methods and accessing to the more information about systems behavior, the role of proactive strategies in developing more reliable and efficient systems becomes more crucial. However, the goals of prediction and the way that the results can be employed to upgrade the system are still topics which draw recent researchers' attention. In this work, we attempt to decrease Jobs wait time and failure rate by using the results of a job futurity predictor. For achieving this goal, a system component called JSM is proposed. JSM consults the predictor and employs a game theory based model in order to probably rejecting the jobs which are likely to fail. Furthermore, for avoiding from rejecting safety jobs mistakenly, JSM intelligently adopts its decisions with the systems situations. Experimental results state a significant reduction in jobs wait time and failure rate in comparison with other related work.Keywords-job submission manager; cluster computing; job futurity prediction; game theory 1.978-1-4244-6542-2/$26.00

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Section: Jsm As a System Componentmentioning

confidence: 79%

“…Output log can be used to calculate required metrics. In order to compare our proposed method with other approaches, we implement First-fit [8] and JFA [22]. First-fit selects fastest nodes which have a minimum probability of failure in duration of job execution.…”

Section: A Simulation Environmentmentioning

confidence: 99%