Design and analysis of a load balancing strategy in data grids

  • Authors:
  • Xiao Qin

  • Affiliations:
  • Department of Computer Science, New Mexico Institute of Mining and Technology, Socorro, NM

  • Venue:
  • Future Generation Computer Systems - Special section: Data mining in grid computing environments
  • Year:
  • 2007

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Abstract

Developing Data Grids has increasingly become a major concern to make Grids attractive for a wide range of data-intensive applications. Storage subsystems are most likely to be a performance bottleneck in Data Grids and, therefore, the focus of this paper is to design and evaluate a data-aware load-balancing strategy to improve the global usage of storage resources in Data Grids. We build a model to estimate the response time of job running at a local site or remote site. In light of this model, we can calculate slowdowns imposed on jobs in a Data Grid environment. Next, we propose a load-balancing strategy that aims to balance load of a Data Grid in such a judicious way that computation and storage resources in each site are simultaneously well utilized. We conduct experiments using a simulated Data Grid to analyze the performance of the proposed strategy. Experimental results confirm that our load-balancing strategy can achieve high performance for data-intensive jobs in Data Grid environments.