DocumentCode
3229539
Title
A Resource Allocation Model with Cost-Performance Ratio in Data Grid
Author
Zhao, Xiangang ; Xu, Liutong ; Wang, Bai
Author_Institution
Beijing Univ. of Posts & Telecommun., Beijing
Volume
3
fYear
2007
fDate
July 30 2007-Aug. 1 2007
Firstpage
371
Lastpage
376
Abstract
Resource allocation for data transfer is a fundamental issue for achieving high performance in data grid environments. In this paper, we survey the existing researches on allocation problems in grid environment and propose a resource allocation model based on the cost-performance ratio for commerce environments. This ratio takes both price and quality of data resource into consideration at the same time. According to the optimization objective we define two types of ratios: Price-aware ratio and quality-aware ratio. They are suitable for the environments where allocations put more emphasis on quality or price of resource respectively. Based on the maximal cost-efficiency, we formulize the allocation optimization problem and present two theorems and a deduction about its solutions. The corresponding proofs are also given in the paper. Finally, we present two algorithms to allocate and re-allocate data resources. The analysis shows that the algorithms can satisfy our requirements.
Keywords
data analysis; grid computing; resource allocation; software cost estimation; software quality; commerce environments; cost-performance ratio; data grid; data transfer; price-aware ratio; quality-aware ratio; resource allocation model; Algorithm design and analysis; Artificial intelligence; Bandwidth; Constraint optimization; Cost function; Environmental economics; Grid computing; Resource management; Software engineering; Time factors;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-2909-7
Type
conf
DOI
10.1109/SNPD.2007.341
Filename
4287880
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