Efficient Workflow Management Algorithms for Optimization the Scheduling in Grid Computing

Grid computing is a high performance computing environment to solve larger scale computational demands. Grid computing contains resource management, scheduling, security problems, information management and so on. Scheduling is the use to achieve high performance in grid environments. This paper explains one of the large growing optimization algorithms, the ant colony algorithm and genetic algorithm in Grid computing. It uses different heterogeneous systems for sharing large-scale resources to solve very large scientific problems. In this paper, two optimization algorithms are used for scheduling techniques in grid computing. It aims to find a suitable allocation of resources for each job with the comparison of hybrid ACO and GA. We compared our proposed hybrid results with previous results in terms of execution time & execution cost which proves that our new hybrid approach has better results.