An Adaptive Load Balancing Approach in Distributed Computing Using Genetic Theory

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. Meanwhile, in the receiver-initiated load balancing algorithms, the receiver continues to send an unnecessary request message for load acquisition until a sender is found while the system load is low. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic based approach for improved sender-initiated and receiver-initiated load balancing in distributed systems.