An Optimization of Process Scheduling Based on Heuristic GA

For the execution of the real time applications and to compute the high performance of each job, multiprocessor is the powerful tool. Such type of system highly depends on the parallel and distributed computing environment and generates a parallel and distributed network system. Consequently, several methods have been developed to optimally tackle the multiprocessor task scheduling problem which is called NP hard problem or NP complete problem. Scheduling in operating systems has a significant role in overall system performance and throughput. An efficient scheduling is vital for system performance. The concept of Parallel Processing is the speed-up of the execution of a large task by dividing the task into multiple segments that execute simultaneously. By doing the above concept each sub task has its own processor for a faster output. The effectiveness by doing so is beneficial for large number of calculations having some constraints like time constraints etc. Scheduling is the crucial step of parallel programming that deals with the assignment of a set of tasks in the parallel system environment and set the execution in such a way that the total execution time is minimized. The proposed algorithm has the efficient execution of the schedule on parallel system that takes the structure of the application and the performance characteristics. Number of appriximation and heuristics and algorithms have been proposed to fulfill the task scheduling problem. Here the study proposes a genetic based techniques to schedule parallel tasks on hetrogeneous parallel system. In this paper the scheduling problem considered includes- an optimal mapping of the task, search for an optimal configuration of the parallel system and their sequence of execution. The technique for the simultaneous optimization of al