Title :
An accurate and efficient parallel genetic algorithm to schedule tasks on a cluster
Abstract :
Recent breakthroughs in the mathematical estimation of parallel genetic algorithm parameters by Cantu-Paz (2000) are applied to the NP-complete problem of scheduling multiple tasks on a cluster of computers connected by a shared bus. Experiments reveal that the parallel scheduling algorithm develops very accurate schedules when the parameter guidelines are used.
Keywords :
computational complexity; genetic algorithms; parallel algorithms; processor scheduling; workstation clusters; NP-complete problem; cluster of computers; mathematical estimation; parallel genetic algorithm; parameter guidelines; tasks scheduling; Communication channels; Concurrent computing; Genetic algorithms; Guidelines; Message passing; Microcomputers; NASA; NP-complete problem; Processor scheduling; Scheduling algorithm;
Conference_Titel :
Parallel and Distributed Processing Symposium, 2003. Proceedings. International
Print_ISBN :
0-7695-1926-1
DOI :
10.1109/IPDPS.2003.1213276
