A Heuristic Algorithm for Task Scheduling Based on Mean Load

Efficient task scheduling is critical to achieving high performance on grid computing environment. A heuristic task scheduling algorithm satisfied resources load balancing on grid environment is presented in this paper. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfied condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The performance of the proposed algorithm is evaluated via extensive simulation experiments. Experiment results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.