Load Balancing in Grids using Ant Colony Optimization Algorithm

Grid computing is the combination of computer resources from multiple administrative domains for a common goal. Grid computing is characterized by large-scale sharing and cooperation of dynamically distributed resources, such as CPU cycles, communication bandwidth, and data, to constitute a computational environment. Load balancing is one of the critical issues that must be considered in managing a grid computing environment. The load balancing mechanism aims to equally spread the load on each computing node, maximizing their utilization and minimizing the total task execution time. It is complicated due to the distributed and heterogeneous nature of the resources. An ant colony optimization algorithm for load balancing in grid computing is proposed which will determine the best resource to be allocated to the jobs, based on resource capacity and at the same time balance the load of entire resources on grid. The algorithm will consider various resource parameters (MIPS, communication bandwidth, No. of processors and memory) for calculating the resource capability for executing various jobs thus allocating the best resource for the job and also balances the load of all the resource