Balancing Risk and Price: An Opportunity-Cost Approach for Job Scheduling in the Grid Market

  • Authors:

  • Kai Shen;Shoubao Yang;Wei Chen;Xiaoqian Liu;Bin Wu

  • Affiliations:

  • University of Science and Technology of China;University of Science and Technology of China;University of Science and Technology of China;University of Science and Technology of China;University of Science and Technology of China

  • Venue:
  • GCC '07 Proceedings of the Sixth International Conference on Grid and Cooperative Computing
  • Year:
  • 2007

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Abstract

The previous deadline and budget constrained (DBC) algorithms were proposed to optimize the user's cost in market-based job assignment. However those algorithms are not suitable for unreliable grid environment. An opportunity-cost guided algorithm is proposed for job scheduling to bridge this gap. By employing trust mechanism into the grid market, this approach takes both of resource's explicit cost and the successful opportunity into considerations. Von Neumann-Morgenstern utility function (VNM-UF) from the traditional economy theory is applied to characterize the user's risk bias. A quantitative method is given. Simulations show our approach is more suitable for unreliable environment than many other existing approaches. The job failure rate is reduced to 30% and the total cost saves by 8%~10% averagely.