Performance modeling and analysis for resource scheduling in data grids

Authors:
Yajuan Li;Chuang Lin;Quanlin Li;Zhiguang Shan
Affiliations:
Department of Computer Science and Technology, Tsinghua University, Beijing, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Department of Industrial Engineering, Tsinghua University, Beijing, China;Public Technical Service Department, State Information Center, Beijing, China
Venue:
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Year:
2005

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Abstract

Data Grids normally deal with large data-intensive problems on geographically distributed resources; yet, most current research on performance evaluation of resource scheduling in Data Grids is based on simulation techniques, which can only consider a limited range of scenarios. In this paper, we propose a formal framework via Stochastic Petri Nets to deal with this problem. Within this framework, we model and analyze the performance of resource scheduling in Data Grids, allowing for a wide variety of job and data scheduling algorithms. As a result of our research, we can investigate more scenarios with multiple input parameters. Moreover, we can evaluate the combined effectiveness of job and data scheduling algorithms, rather than study them separately.