A Genetic Algorithm for Static Load Balancing in Parallel Heterogeneous Systems
Mehdi Effatparvar, Mohammad Sadeq Garshasbi · Procedia - Social and Behavioral Sciences · 2014
Parallel Processing refers to the concept of running tasks that can be run simultaneously on several processors. Load balancing and scheduling are very important and complex problems in multiprocessor systems. So that problems are NP-Complete problems. In this paper, we introduce a method based on genetic algorithms for scheduling and load balancing in parallel heterogeneous multi-processor systems. The results of the simulations indicate Genetic algorithm for scheduling and load balancing at in systems is better than LPT, SPT and FIFO. Simulations results indicate Genetic Algorithm reduces total response time and also it increase utilization.