Peer-Reviewed Journal Details
Mandatory Fields
Page, AJ;Keane, TM;Naughton, TJ
2010
July
Journal of Parallel and Distributed Computing
Multi-heuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed system
Published
53 ()
Optional Fields
PARALLEL PROCESSOR SYSTEMS INDEPENDENT TASKS SCHEDULING ALGORITHMS COMPUTING SYSTEMS RECONSTRUCTION
70
758
766
We present a multi-heuristic evolutionary task allocation algorithm to dynamically map tasks to processors in a heterogeneous distributed system. It utilizes a genetic algorithm, combined with eight common heuristics, in an effort to minimize the total execution time. It operates on batches of unmapped tasks and can preemptively remap tasks to processors. The algorithm has been implemented on a Java distributed system and evaluated with a set of six problems from the areas of bioinformatics, biomedical engineering, computer science and cryptography. Experiments using up to 150 heterogeneous processors show that the algorithm achieves better efficiency than other state-of-the-art heuristic algorithms. (C) 2010 Elsevier Inc. All rights reserved.
SAN DIEGO
0743-7315
10.1016/j.jpdc.2010.03.011
Grant Details