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An Adaptive Grid Resource Selection Method Using Statistical Analysis of Job History  

Hur, Cin-Young (숙명여자대학교 컴퓨터과학과)
Kim, Yoon-Hee (숙명여자대학교 컴퓨터과학과)
Publication Information
Journal of KIISE:Computer Systems and Theory / v.37, no.3, 2010 , pp. 127-137 More about this Journal
Abstract
As large-scale computational applications in various scientific domains have been utilized over many integrated sets of grid computing resources, the difficulty of their execution management and control has been increased. It is beneficial to refer job history generated from many application executions, in order to identify application‘s characteristics and to decide selection policies of grid resource meaningfully. In this paper, we apply a statistical technique, Plackett-Burman design with fold-over (PBDF), for analyzing grid environments and execution history of applications. PBDF design identifies main factors in grid environments and applications, ranks based on how much they affect to their execution time. The effective factors are used for selecting reference job profiles and then preferable resource based on the reference profiles is chosen. An application is performed on the selected resource and its execution result is added to job history. Factor's credit is adjusted according to the actual execution time. For a proof-of-concept, we analyzed job history from an aerospace research grid system to get characteristics of grid resource and applications. We built JARS algorithm and simulated the algorithm with the analyzed job history. The simulation result shows good reliability and considerable performance in grid environment with frequently crashed resources.
Keywords
Adaptive Resource selection; Job history; Grid computing; e-Science; Plackett-Burman;
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