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On-line predicting behaviors of jobs in dynamic load balancing

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Abstract

A key issue of dynamic load balancing in a loosely coupled distributed system is selecting appropriate jobs to transfer. In this paper, a job selection policy based on on-line predicting behaviors of jobs is proposed. Tracing is used at the beginning of execution of a job to predict the approximate execution time and resource requirements of the job so as to make a correct decision about whether transferring the job is worthwhile. A dynamic load balancer using the job selection policy has been implemented. Experimental measurement results show that the policy proposed is able to improve mean response time of jobs and resource utilization of systems substantially.

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Authors and Affiliations

  1. Department of Computer Science, Jilin University, 130023, Changchun

    Ju Jiubin, Xu Gaochao & Yang Kun

Authors
  1. Ju Jiubin
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  2. Xu Gaochao
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  3. Yang Kun
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Additional information

This work was supported by the National High-Tech R/D Programme and the National Natural Science Foundation of China.

Ju Jiubin is a Professor in the Department of Computer Science, Jilin University. His research interests include parallel processing, computer networks, computer architecture, and distributed systems.

Xu Gaochao is a Teacher in the Department of Computer Science, Jilin University. He received his B.S., M.S. and Ph.D. degrees in computer science from Jilin University in 1988, 1991, and 1995, respectively. His research interests include parallel processing, computer networks, and distributed systems.

Yang Kun received his M.S. degree in computer science from Jilin University in 1994. His research interests include parallel processing, computer networks, and distributed systems.

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Ju, J., Xu, G. & Yang, K. On-line predicting behaviors of jobs in dynamic load balancing. J. of Compt. Sci. & Technol. 11, 39–48 (1996). https://doi.org/10.1007/BF02943520

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  • DOI: https://doi.org/10.1007/BF02943520

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