A genetic-fuzzy logic based load balancing algorithm in heterogeneous distributed systems

Distributed processing is recognized as a practical way to achieve high performance in various computational applications. Many dynamic loadbalancing algorithms have been proposed for parallel and discrete simulations. But the actual performances of these algorithms have been far from ideal, especially in the heterogeneous environment. In this paper, a hybrid approach using fuzzy supervised learning and generic algorithm is presented. The fuzzy membership function is dynamically adjusted by the genetic coding. Moreover, the proposed load-balancing algorithm has learning capability. The experimental results show that our proposed algorithm has better performance comparing with other classical load balancing algorithms. Keyword:Load-balancing, genetic algorithm, fuzzy logic, heterogeneous