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Proceedings Paper

A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements
Author(s): Xun Pu; XianLiang Lu
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Paper Abstract

Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.

Paper Details

Date Published: 1 October 2011
PDF: 8 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82855G (1 October 2011); doi: 10.1117/12.913402
Show Author Affiliations
Xun Pu, Univ. of Electronic Science and Technology of China (China)
Southwest Univ. (China)
XianLiang Lu, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)

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