An Improved Job Scheduling Algorithm by Utilizing Released Resources for MapReduce

MapReduce has become one standard for big data processing in Cloud computing environment. However job scheduling in this model is always a challenge for the research fraternity and several job scheduling algorithms have already been proposed by researchers addressing various issues. All such algorithms mostly emphasize on meeting of job deadline without taking cognizance of additional released resources being available through intermediate release of resources during processing. In this paper, we propose a new job scheduling algorithm which satisfies job deadline for all scheduled jobs along with utilization of the unused resources so that more number of jobs can be scheduled and the overall system efficiency will be increased.