(untitled) (International Journal of Engineering and Computer Science, 2017)
Grid computing is effective and purely dispersed body that gives a highly assessed computing platform that resolve the high level of difficulties through allocation and distribution of computational ability. Yet Ant Colony algorithm for Optimization has the ability to give an optimized result in grid computing background then other algorithms but it does not give the assurance to give proper results when it executed for many time. Ant Colony algorithm provides improbability in merging time to the deviation in the size of the problem and has opposing results onto the program effectiveness. This algorithm lacks organized initial values because of the unsystematic initialization. This assumption defines about poorly chosen values will lead to bad solutions. In the proposed algorithm scheduling of autonomous jobs are selected. In this procedure at one time only one job is selected and proceeds for execution on the main server. If this main server is failed while executing then server is rejected. We have calculated the performance of these algorithms such as FCFS/FF, SJF/FF, LJF/FF and metaheuristic algorithm Ant Colony Optimization for job scheduling and draw comparison between proposed technique