A load balancing method based on genetic clonal annealing strategy in grid environments

Load balancing is a very important and complex problem in grid computing. Grid computing differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. This paper combined with the advantages of genetic algorithm, clonal selection algorithm and simulated annealing, brings forward a genetic clonal annealing algorithm and applied to solve grid computing task scheduling problem. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.