A novel load balancing method based on genetic algorithm in grid computing system

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. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of load balancing scenarios. This paper studies Min-min chromosome genetic algorithm (MCGA) to gauge their suitability for solving grid load balancing problems. The effectiveness of MCGA algorithm is shown for a number of test problems. Performance comparisons with Min-min, and genetic algorithm also discussed.