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Stochastic scheduling for multiclass applications with availability requirements in heterogeneous clusters

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Abstract

High availability plays an important role in heterogeneous clusters, where processors operate at different speeds and are not continuously available for processing. Existing scheduling algorithms designed for heterogeneous clusters do not factor in availability. We address in this paper the stochastic scheduling problem for heterogeneous clusters with availability constraints. Each node in a heterogeneous cluster is modeled by its speed and availability, and different classes of tasks submitted to the cluster are characterized by their execution times and availability requirements. To incorporate availability and heterogeneity into stochastic scheduling, we introduce metrics to quantify availability and heterogeneity in the context of multiclass tasks. A stochastic scheduling algorithm SSAC (stochastic scheduling with availability constraints) is then proposed to improve availability of heterogeneous clusters while reducing average response time of tasks. Experimental results show that our algorithm achieves a good trade-off between availability and responsiveness.

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Authors and Affiliations

  1. Department of Computer Science, San Diego State University, San Diego, CA, 92182, USA

    Tao Xie

  2. Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, 36849, USA

    Xiao Qin

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  1. Tao Xie
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  2. Xiao Qin
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Correspondence to Tao Xie.

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Xie, T., Qin, X. Stochastic scheduling for multiclass applications with availability requirements in heterogeneous clusters. Cluster Comput 11, 33–43 (2008). https://doi.org/10.1007/s10586-007-0049-0

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  • DOI: https://doi.org/10.1007/s10586-007-0049-0

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