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Scheduling with uncertainties on new computing platforms

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Abstract

New distributed computing platforms (grids) are based on interconnections of a large number of processing elements. A most important issue for their effective utilization is the optimal use of resources through proper task scheduling. It consists of allocating the tasks of a parallel program to processors on the platform and to determine at what time the tasks will start their execution. As data may be subject to uncertainties or disturbances, it is practically impossible to precisely predict the input parameters of the task scheduling problem.

We briefly survey existing approaches for dealing with data uncertainties and discuss their relevance in the context of grid computing. We describe the stabilization process and analyze a scheduling algorithm that is intrinsically stable (i.e., it mitigates the effects of disturbances in input data at runtime). This algorithm is based on a decomposition of the application graph into convex sets of vertices. Finally, it is compared experimentally to pure on-line and well-known off-line algorithms.

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Authors and Affiliations

  1. UTIC, Higher School of Sciences and Techniques of Tunis, 5 Av. Taha Hussein, Tunis, Tunisia

    Amine Mahjoub

  2. LIG, Grenoble University, 51 Av. Jean Kuntzman, Montbonnot Saint Martin, 38330, France

    Johnatan E. Pecero Sánchez & Denis Trystram

Authors
  1. Amine Mahjoub
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  2. Johnatan E. Pecero Sánchez
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  3. Denis Trystram
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Corresponding author

Correspondence to Johnatan E. Pecero Sánchez.

Additional information

This work has been partially realized within INRIA-DGRSRT bilateral franco-tunisian project. It has been done when A. Mahjoub was visiting the LIMOS in France.

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Mahjoub, A., Pecero Sánchez, J.E. & Trystram, D. Scheduling with uncertainties on new computing platforms. Comput Optim Appl 48, 369–398 (2011). https://doi.org/10.1007/s10589-009-9311-0

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  • DOI: https://doi.org/10.1007/s10589-009-9311-0

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