Job Scheduling in Grid Computing using User Deadline

Grid computing could be a style of distributed computing that co-ordinates and provides the ability of resource sharing over varied geographical locations. Resource planning in Grid computing is an advanced task owing to the heterogeneous and dynamic nature of the resources. Bacterial foraging has recently emerged as a world optimization algorithmic program for distributed optimization and management. This paper proposes the job of the bacterial foraging optimization technique for Grid resource planning. A completely unique bacterial foraging based mostly hyperheuristic resource planning algorithmic program has been designed to effectively schedule the roles on the market resources during a Grid environment. The performance of the planned algorithmic program has been evaluated with the present common Meta heuristics based scheduling algorithms through the GridSim toolkit. The experimental results show that the planned algorithmic program outperforms the present algorithms by minimizing price and makespan of user applications submitted to the Grid. Although this algorithm performs well there are fewer disadvantages that gives less results and that can be improved by using deadline based hyper heuristic method which gives much better results than the Bacterial Foraging Optimization (BFO). Keywords-Grid computing, Job scheduling, Meta heuristic, Hyper heuristic, User deadline.