NDLI: On Evaluating JARS: Job history-based Adaptive grid resource selection

Content Provider	IEEE Xplore Digital Library
Author	Cinyoung Hur Yoonhee Kim
Copyright Year	2010
Description	Author affiliation: Department of Computer Science, Sookmyung Women's University, Seoul, Korea (Cinyoung Hur; Yoonhee Kim)
Abstract	Grids have ensured to solve a large-scale complex scientific problem with utilizing many heterogeneous resources that are geographically separated. However, as grid resources and scientific applications become diverse, the difficulty of their execution management and control has been increased. In this paper, we propose JARS (Job history-based Adaptive grid Resource Selection) system and evaluate with different scenarios. Specifically, statistical technique, Plackett-Burman design with fold-over, is applied on analyzing grid environments and job history. Through JARS system, accumulated knowledge of applications' execution can be utilized in practical resource selection. As a proof-of-concept, we analyzed job history from an aerospace research grid system and obtained characteristics of grid resources and applications. The simulations present that resources with acceptable performance and reliability are selected under heavy resource failures.
Starting Page	817
Ending Page	820
File Size	331145
Page Count	4
File Format	PDF
ISBN	9781424453665
ISSN	15421201
e-ISBN	9781424453672
DOI	10.1109/NOMS.2010.5488368
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-19
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	History Computational modeling Computational fluid dynamics Large-scale systems Application software Resource management Job design Computer science Adaptive systems Grid computing Resource selection Adaptive system Job history
Content Type	Text
Resource Type	Article

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