GA-based job scheduling strategies for fault tolerant grid systems

Chao Chin Wu; Kuan Chou Lai; Ren Yi Sun

doi:10.1109/APSCC.2008.165

GA-based job scheduling strategies for fault tolerant grid systems

Chao Chin Wu, Kuan Chou Lai, Ren Yi Sun

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

Abstract

This work mainly aims at the designs of the genetic algorithm based scheduling strategies by considering four different fault tolerance techniques in the Grid environment, including Retry, Migration, Checkpoint, Replication. We also take into account the risk relationship between jobs and nodes to improve the system reliability in the scheduling algorithm. According to the simulation results, we can find out that the performance of fault tolerant algorithms is better than risky algorithm whether in makespan, average turnaround time, or the job failure rate. Checkpoint algorithm has the best performance in all algorithms. On the other hand, retry algorithm is recommended for the system where the job sizes are usually smaller because of its simplicity. Finally, replicated algorithm is not suitable for the Grid since it imposes too much overhead.

Original language	English
Title of host publication	Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008
Publisher	IEEE Computer Society
Pages	27-32
Number of pages	6
ISBN (Print)	9780769534732
DOIs	https://doi.org/10.1109/APSCC.2008.165
Publication status	Published - 2008 Jan 1
Event	3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008 - Yilan, Taiwan Duration: 2008 Dec 9 → 2008 Dec 12

Publication series

Name	Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008

Other

Other	3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008
Country	Taiwan
City	Yilan
Period	08-12-09 → 08-12-12

All Science Journal Classification (ASJC) codes

Computer Science Applications
Software
Electrical and Electronic Engineering

Access to Document

10.1109/APSCC.2008.165

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Wu, C. C., Lai, K. C., & Sun, R. Y. (2008). GA-based job scheduling strategies for fault tolerant grid systems. In Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008 (pp. 27-32). [4780647] (Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008). IEEE Computer Society. https://doi.org/10.1109/APSCC.2008.165

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abstract = "This work mainly aims at the designs of the genetic algorithm based scheduling strategies by considering four different fault tolerance techniques in the Grid environment, including Retry, Migration, Checkpoint, Replication. We also take into account the risk relationship between jobs and nodes to improve the system reliability in the scheduling algorithm. According to the simulation results, we can find out that the performance of fault tolerant algorithms is better than risky algorithm whether in makespan, average turnaround time, or the job failure rate. Checkpoint algorithm has the best performance in all algorithms. On the other hand, retry algorithm is recommended for the system where the job sizes are usually smaller because of its simplicity. Finally, replicated algorithm is not suitable for the Grid since it imposes too much overhead.",

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Wu, CC, Lai, KC & Sun, RY 2008, GA-based job scheduling strategies for fault tolerant grid systems. in Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008., 4780647, Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008, IEEE Computer Society, pp. 27-32, 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008, Yilan, Taiwan, 08-12-09. https://doi.org/10.1109/APSCC.2008.165

GA-based job scheduling strategies for fault tolerant grid systems. / Wu, Chao Chin; Lai, Kuan Chou; Sun, Ren Yi.

Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008. IEEE Computer Society, 2008. p. 27-32 4780647 (Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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