A Hyper-Heuristic Approach for Efficient Resource Scheduling in Grid

Efficient execution of computations in grid can require mapping of tasks to processors whose performance is both irregular and time varying because of dynamic nature. The task of mapping jobs to the available computing nodes or scheduling of the jobs on the grid is a NP complete problem. The NP-hard problem is often solved using heuristics techniques. Heuristic and metaheuristic approaches tend to be knowledge rich, requiring substantial expertise in both the problem domain and appropriate heuristics techniques. To alleviate this problem the concept of Hyperheuristic was introduced. They operate on the search space of heuristics instead of candidate solutions and can be applied to any optimization problem. This paper emphasizes the use of Hyper-heuristics built on top of hybridized Metaheuristics to efficiently and effectively schedule jobs onto available resources in a grid environment thus resulting in an optimal schedule with minimum makespan