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Abstract

Grid computing paved way for efficient utilization of resources and this is one of the important aspects in the recent research trends. In this paper, an Intelligent Water Drops (IWD) algorithm is proposed for task workflow scheduling with hyper-heuristic search for achieving better performance optimization for workflow distribution in computational grid environment. The challenge is to find the best matching resource among the available free resources for which a grid broker is used. A hyper heuristic search is performed which undergoes multiple rounds of searches for finding the best matching resource by imparting a specific point in time rule. Load balancing is achieved by computing the average computational power of all the resources and grouping the resources. This helps the system to assign various types of jobs to the resources, thus improving the computational efficiency. The performance parameters such as makespan, cost, deadline of jobs and number of searches for finding best optimal resource are considered for performance enhancement. The simulation results of Intelligent Water Drops based Hyper-heuristic algorithm is compared with few of the latest existing works and the proposed algorithm outperforms thus achieving performance optimization.