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ADJSA: an adaptable dynamic job scheduling approach based on historical information

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ACM International Conference Proceeding Series; Vol. 304 archive
Proceedings of the 2nd international conference on Scalable information systems table of contents

Suzhou, China

SESSION: WIP 1 -- work-in-progress I table of contents

Article No. 31

Year of Publication: 2007

ISBN:978-1-59593-757-5

Authors

Lan Xu	Soochow University, Suzhou, China and Key Lab of Computer Information Processing Technology of Jiangsu Province, Suzhou, China
Qiao-ming Zhu	Soochow University, Suzhou, China and Key Lab of Computer Information Processing Technology of Jiangsu Province, Suzhou, China
Zhengxian Gong	Soochow University, Suzhou, China and Key Lab of Computer Information Processing Technology of Jiangsu Province, Suzhou, China
Pei-feng Li	Soochow University, Suzhou, China and Key Lab of Computer Information Processing Technology of Jiangsu Province, Suzhou, China

Sponsors

SIGARCH: ACM Special Interest Group on Computer Architecture
SIGIR: ACM Special Interest Group on Information Retrieval
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia

Publisher

ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) ICST, Brussels, Belgium, Belgium

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Downloads (6 Weeks): 3, Downloads (12 Months): 10, Citation Count: 0

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ABSTRACT

Currently, there are many researches focusing on grid scheduling and more and more scheduling algorithms were proposed. However, those algorithms are not satisfied with the requirement of the grid for ignoring its characteristics of dynamics, autonomy, distributing, etc. Therefore, this paper proposes an adaptable dynamic job scheduling approach based on historical information (ADJSA). This approach adjusts the predicting model automatically by using the recent jobs execution historical information and then selects the appropriate resource to execute the job considering dynamic and real-time factors of the Grid.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Maheswaran M, Ali S, Siegel HJ, Hensgen D, Freund RF. A comparison of dynamic strategies for mapping a class of independent jobs onto heterogeneous computing systems. Technical Report, School of ECE, Purdue University, 1999
	2	Yang Y, Cai ZX, Fu Y, Liu MQ. An adaptive grid job scheduling method based on genetic algorithm{J}. Computer Engineering And Applications, 2005.1
	3	William K. Cheung , Jiming Liu , Kevin H. Tsang , Raymond K. Wong, Dynamic Resource Selection For Service Composition in The Grid, Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, p.412-418, September 20-24, 2004 [doi>10.1109/WI.2004.58]

INDEX TERMS

Keywords:
adaptation, grid computing, historical information, job scheduling

Collaborative Colleagues:

Lan Xu: colleagues

Qiao-ming Zhu: colleagues

Zhengxian Gong: colleagues

Pei-feng Li: colleagues

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