Title :
Using a classifier system to improve dynamic load balancing
Author :
Correa, Jan M. ; Melo, Alba C.
Author_Institution :
Dept. of Comput. Sci., Brasilia Univ., Brazil
Abstract :
Dynamic load balancing is a very important problem in distributed processing. This problem aims to redistribute running processes to achieve better results according some optimization criterion. Since it is an NP-complete problem in its general formulation, it is worth using heuristics to seek better results in a reasonable time. One of the heuristics that has been successfully applied in various static scheduling problems is genetic algorithms (GAs). We propose to use a classifier system that is an adaptive system that applies a GA over a population of decision rules to achieve better decisions about when to carry out preemptive migrations in a distributed environment. The results have been impressive and the classifier system was able to surpass, without previous knowledge of the workload, the performance of a well designed analytic criterion
Keywords :
genetic algorithms; optimisation; processor scheduling; resource allocation; NP-complete problem; adaptive system; classifier system; decision rules; distributed processing; dynamic load balancing; genetic algorithms; heuristics; optimization criterion; preemptive migrations; running process redistribution; Adaptive systems; Computer science; Distributed computing; Distributed processing; Dynamic scheduling; Genetic algorithms; Load management; Performance analysis; Processor scheduling; Scheduling algorithm;
Conference_Titel :
Parallel Processing Workshops, 2001. International Conference on
Conference_Location :
Valencia
Print_ISBN :
0-7695-1260-7
DOI :
10.1109/ICPPW.2001.951980