A Fuzzy Rule Base Technique for Process Grain Scheduling of Parallel Jobs

In this paper, we introduce a fuzzy based engine for the scheduling problem. In real world scheduling problems, due to the synchronization granularity of processes, the scheduling of parallel jobs becomes ineffective. A good way of characterizing a parallel system is to consider the synchronization granularity or frequency of synchronization between processes in a system. The scientific applications of the parallel system consist of multiple processes running on different processors that communicate frequently. The performance evaluation of such systems mainly depends on how the processes are co scheduled. If the processes are not co scheduled properly, then the system will lead to severe performance penalties. The various co scheduling techniques available are First Come First Served, Gang Scheduling and Flexible Co Scheduling and nimble algorithm. The paper focuses on an attempt to develop fuzzy systems based on the scheduling criteria which decides the best scheduling algorithm for parallel jobs.