A dynamic load balancing approach using genetic algorithm in distributed systems

In sender-initiated load balancing algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput. To solve these problems, the authors propose a genetic algorithm method for improved sender-initiated load balancing in distributed systems, and define a suitable fitness function. This algorithm decreases unnecessary request messages and increases acceptance rate. Compared with the conventional sender-initiated algorithms, they show that the proposed algorithm performs better.