Genetic Algorithm for Parallel Process Scheduling

The hindrance of process scheduling in parallel and distributed system is challenging job in the field of computer science as research. Scheduling in parallel computing system plays an important role in overall for the enhancement of the performance of system in distributing the jobs. Scheduling in such type of system has a NP complete or NP hard problem. Process scheduling in parallel and distributed system allocate the processes to processor. By doing so make-span or execution time can be minimized. Further the processors utilization in the parallel computing system can be maximized. One more advantage of this one is to maximize the load balancing of jobs in the parallel processing. To tackle such type of problem a heuristic approach can be utilized that is known as Genetic algorithm. Genetic algorithm optimizes the problem in minimum time with maximum workload and is based on natural selection and natural genetics. Here with the help of GA, the problem can be made more simple and fast by considering load balancing efficiently and with the help of simulation results, the performance and efficiency of the proposed genetic algorithm can be evaluated.