Abstract
This paper presents a new approach to solve the problem of job scheduling for parallel processing in heterogeneous systems. The optimization goals are: (i) minimum total execution time including communication costs and (ii) shortest response time for all jobs. We introduce a classification for the given scheduling problem by the heterogeneity of the systems, from the view of the schedulers' eyes. Then, according to this analysis, a new scheduling strategy for so-called “Strictly-Heterogeneous” systems is proposed. The key idea of the new approach is the use of the Hungarian method, which provides a quick and objective-oriented search for the best schedule by the given optimization criteria. In addition, by modifying this method into so-called Objective-Oriented Algorithm (OOA), the time complexity for scheduling is decreased to O(n(E+nlogn)). The simulation results show us that OOA provides better solution quality while scheduling time is less than the existing methods.
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Hanh, P.H., Simonenko, V. (1997). Objective-oriented algorithm for job scheduling in parallel heterogeneous systems. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1997. Lecture Notes in Computer Science, vol 1291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63574-2_22
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DOI: https://doi.org/10.1007/3-540-63574-2_22
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