Two Heuristic Approaches for Mapping Parallel Applications on Distributed Computing Systems | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 1, Volume 18, Issue 2, December 2008, Page 85-98 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2008.65226 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Marwa Shouman1; Gamal M. Attiya2; Ibrahim Z. Morsi3 | ||||
| 1Dept. of Computer Science and Eng., Faculty of Elect., Eng., Minufiya University | ||||
| 2* Dept. of Computer Science and Eng., Faculty of Elect., Eng., Minufiya University | ||||
| 3Dept. of Electrical Engineering, Faculty of Engineering, Minufiya University | ||||
| Abstract | ||||
| The performance of a parallel application running on a Distributed Computing System (DCS) is basically affected by the distribution of workload over the various processors in the system. This problem is known to be NP-hard in most cases and complicates farther with increasing number of tasks and/or computers. This paper presents two heuristic algorithms; Simulated Annealing (SA) and Genetic Algorithm (GA), to solve the mentioned problem. The qualities of the resulting distribution are compared with that obtained by applying the Branch–and-Bound (BB) technique | ||||
| References | ||||
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