Title :
KASIA approach vs. Differential Evolution in Fuzzy Rule-Based meta-schedulers for Grid computing
Author :
Prado, R.P. ; García-Galán, S. ; Expósito, J. E Muñoz
Author_Institution :
Telecommun. Eng. Dept., Univ. of Jaen, Linares, Spain
Abstract :
Many efforts have been made in the last few years to solve the high-level scheduling problem in Grid computing, i.e., the efficient resources utilization and allocation of workload within resources domains. Nowadays, some trends are based on the consideration of Fuzzy Rule-Based Systems, whose performance is critically conditioned to theirs knowledge bases quality. In this sense, Genetic Algorithms have been extensively used to obtain such knowledge bases, mainly founded on Pittsburgh approach. However, new strategies are recently emerging showing improvement over genetic-based learning methods. In this work, comparative results of two non-genetic learning strategies derived from bio-inspired algorithms, Differential Evolution and Particle Swarm Optimization, are presented for the evolution of fuzzy rule-based meta-schedulers in Grid computing.
Keywords :
evolutionary computation; fuzzy set theory; grid computing; knowledge based systems; learning (artificial intelligence); particle swarm optimisation; resource allocation; scheduling; KASIA approach; Pittsburgh approach; bioinspired algorithm; differential evolution; fuzzy rule-based metaschedulers; fuzzy rule-based system; genetic algorithm; grid computing; high-level scheduling problem; knowledge base quality; nongenetic learning strategy; particle swarm optimization; resource allocation; resource utilization; Encoding; Grid computing; Knowledge acquisition; Knowledge based systems; Particle swarm optimization; Processor scheduling; Scheduling; Differential Evolution; Fuzzy Rule-Based Systems; Grid Computing; Particle Swarm Optimization; Scheduling;
Conference_Titel :
Genetic and Evolutionary Fuzzy Systems (GEFS), 2011 IEEE 5th International Workshop on
Conference_Location :
Paris
Print_ISBN :
978-1-61284-049-9
DOI :
10.1109/GEFS.2011.5949488