Tabu-based Evolutionary Algorithm with Negative Selection for Pareto-optimization in Distributed Systems

Reliability and the load balancing are crucial factors for a quality evaluation of distributed systems. Load balancing of the Web servers can be implemented by reduction of the workload of the bottleneck computer what improves both a performance of the system and the safety of the bottleneck computers. An evolutionary algorithm based on a tabu search procedure is discussed for multi-criteria optimization of distributed systems A tabu mutation is applied for minimization the workload of the bottleneck computer. It can be obtained by task assignment as well as selection of suitable computer sorts. Moreover, a negative selection procedure is developed for improving nonadmissible solutions. Some numerical results are submitted. Key-Words: evolutionary algorithm, multi-criterion optimization, Internet bank systems