Roulette Wheel Selection Model based on Virtual Machine Weight for Load Balancing in Cloud Computing

Abstract

The increasing use of cloud computing resources have placed a large workload on the data centers. Solving the load balancing problem among all virtual machines (VMs) increases performance, throughput and decreases the request delay. In this paper, Roulette Wheel Selection algorithm is applied on all VMs for balancing the load in the cloud computing environment based on virtual machine weight. In our experiments, measures such as response time, data center request servicing time and processing cost are used. Simulation results show that Roulette Wheel Selection algorithm reduces data transfer cost when compared to three other load balancing algorithms.