Future Generation Computer Systems
Modeling user submission strategies on production grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
Two experiments with application-level quality of service on the EGEE grid
Proceedings of the 2nd workshop on Grids meets autonomic computing
Modelling pilot-job applications on production grids
Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing
Algorithms and mechanisms for procuring services with uncertain durations using redundancy
Artificial Intelligence
A survey of task mapping on production grids
ACM Computing Surveys (CSUR)
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This paper presents a method to optimize the timeout value of computing jobs. It relies on a model of the job execution time that considers the job management system latency through a random variable. It also takes into account a proportion of outliers to model either reliable clusters or production grids characterized by faults causing jobs loss. Job management systems are first studied considering classical distributions. Different behaviors are exhibited, depending on the weight of the tail of the distribution and on the amount of outliers. Experimental results are then shown based on the latency distribution and outlier ratios measured on the EGEE grid infrastructure1. Those results show that using the optimal timeout value provided by our method reduces the impact of outliers and leads to a 1.36 speed-up even for reliable systems without outliers.