An Improved Scheduling Approach for Efficient Resource Utilization and Its Application in Bioinformatics Grid

Grid computing are utilized by numerous research ventures for storing of high dimensional data and complex computation. Scheduling is a critical issue in the present Grid computing for achieving efficiency of the resource utilization. In this work, an improved scheduling approach for efficient resource utilization in a bioinformatics grid is proposed. The microarray gene data is disseminated among the resources for parallel calculation utilizing the ensemble classifier. The proposed technique, Cluster Heterogeneous Min-Min Artificial Bee Colony (CHMM-ABC), uses Min min scheduling and ABC metaheuristic for efficient scheduling. For analysis, two synthetic microarray gene data with a large feature set is investigated. Simulations shown the proposed optimization scheduling algorithm improves Makespan and speedup.