A Genetic Algorithm Based Dynamic Load Balancing Scheme for Heterogeneous Distributed Systems

Abstract

Load balancing is a crucial issue in parallel and distributed systems to ensure fast processing and optimum utilization of computing resources. Load balancing strategies try to ensure that every processor in the system does almost the same amount of work at any point of time. This paper investigates dynamic load-balancing algorithm for heterogeneous distributed systems where half of the processors have double the speed of the others. Two job classes are considered for the study, the jobs of first class are dedicated to fast processors. While second job classes are generic in the sense they can be allocated to any processor. The performance of the scheduler has been verified under scalability. Some simulation results are presented to show the effectiveness of genetic algorithms for dynamic load balancing.