In this paper we proposal a new scheduling system based on multi-clusters environments. The work we present is Adaptive Job Allocation Strategy (AJAS) in which the scheduler dispatches jobs that with self-scheduling scheme into appropriate resources across multi-clusters. The strategy focuses on how to increase resource utility, jobs via self-scheduling and dispatching jobs to nodes with similar performance capacities, thus equalizing execution times among all the nodes the jobs require. Experimental results show that the proposed approach performs better than previous schemes.
['Chao-Tung Yang', 'Keng-Yi Chou']
An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters