NDLI: User Demand Prediction-Based Resource Management Model in Grid Computing Environment

Content Provider	IEEE Xplore Digital Library
Author	Kyu Cheol Cho Tae Young Kim Jong Sik Lee
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Inha Univ., Incheon (Kyu Cheol Cho; Tae Young Kim; Jong Sik Lee)
Abstract	As demand and supply of Grid resources in Grid computing environments increases rapidly, many Grid researchers have taken particular interest in efficient management of Grid resources. In this paper, a user demand prediction-based resource management model (UDPRMM), which uses the user demand trend of Grid resources as a critical management factor, is proposed. This paper introduces a user demand prediction approach with historical user demands and aims for effective Grid resource management through transaction management between resource users and resource suppliers. For performance evaluation with accuracy and reliability, the UDPRMM is compared with the user demand fixed-based resources management model (UDFRMM) and the user demand random-based resources management model (UDRRMM). The UDPRMM demonstrates improvement greater than 70% with regard Grid resource transactions and greater than 16% with regard to Grid resource transaction quantities in comparison with the UDFRMM and the UDRRMM. In evaluation, the UDPRMM reduces delay time by 21%, over that of the UDFRMM, and 19% over that of the UDRRMM. The empirical results demonstrate the usefulness of the UDPRMM with effective economics-based resource management.
Starting Page	627
Ending Page	632
File Size	286089
Page Count	6
File Format	PDF
ISBN	9780769533285
DOI	10.1109/ICHIT.2008.196
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-28
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics DEVS User demand prediction Biological system modeling Computational modeling Predictive models Grid computing Resource management Mathematical model Equations
Content Type	Text
Resource Type	Article

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