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, we 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, we show that the proposed algorithm performs better.