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Maximizing business value by optimal assignment of jobs to resources in grid computing

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  • Kumar, Subodha
  • Dutta, Kaushik
  • Mookerjee, Vijay

Abstract

An important problem that arises in the area of grid computing is one of optimally assigning jobs to resources to achieve a business objective. In the grid computing area, however, such scheduling has mostly been done from the perspective of maximizing the utilization of resources. As this form of computing proliferates, the business aspects will become crucial for the overall success of the technology. Hence, we discuss the grid scheduling problem from a business perspective. We show that this problem is not only strongly NP-hard, but it is also non-approximable. Therefore, we propose heuristics for different variants of the problem and show that these heuristics provide near-optimal solution for a wide variety of problem instances. We show that the execution times of proposed heuristics are very low, and hence, they are suitable for solving problems in real-time. We also present several managerial implications and compare the performance of two widely used models in the real-time scheduling of grid computing.

Suggested Citation

  • Kumar, Subodha & Dutta, Kaushik & Mookerjee, Vijay, 2009. "Maximizing business value by optimal assignment of jobs to resources in grid computing," European Journal of Operational Research, Elsevier, vol. 194(3), pages 856-872, May.
    • Handle: RePEc:eee:ejores:v:194:y:2009:i:3:p:856-872
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    Cited by:

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    5. Hossein Jahandideh & Julie Ward Drew & Filippo Balestrieri & Kevin McCardle, 2020. "Individualized Pricing for a Cloud Provider Hosting Interactive Applications," Service Science, INFORMS, vol. 12(4), pages 130-147, December.

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