Comparing Configurable Parameters of Swarm Intelligence Algorithms for Dynamic Load Balancing

Abstract

A main challenge on today's distributed systems is to cope with huge amounts of load. An important research issue is to distribute load across enterprise boundaries in highly heterogeneous environments. However, intelligent and adaptive load balancing problem is a complex problem and requires both intelligent algorithms and approaches. In this paper, we present the first findings of a novel approach towards load balancing, based on bee intelligence. The approach defines a generic architecture called SILBA (self initiative load balancing agents) which allows the exchange of different algorithms through simple plugging techniques. Six algorithms were developed, both unintelligent and intelligent ones, compared and performance benchmarks on both a cluster of virtual nodes and the Amazon EC2 cloud demonstrate promising benefits of the bee based algorithm.