Threshold-Based Workload Control for an Under-Utilized Virtual Machine in Cloud Computing

Abstract: Cloud computing empowers sharing of computing resources dynamically to a wide range of end users. The workload on the cloud resources is amassed immensely with the advancement of new applications. To increase the utilisation of the virtual machine in the cloud data center, an efficient load balancing technique is predominantly crucial. Load balancing is the heart of the data centre in cloud environment which makes all the virtual machines accomplish the same amount of workload and helps the virtual machines deliver the services with minimal time delay. To ensure optimum resource usage and fast processing time, M/G/1 is developed with vacation queuing model (VQM-LB) for adjusting the workload of the under-loaded virtual machine in a cloud environment. The proposed system uses vacation and threshold policy to efficiently control the workload level of each virtual machine in the data center , and reduces the energy consumption and cost accordingly. The result obtained in our proposed model assuredly bounces optimum solutions and apparently indicates the triumph of an efficient load balancing of tasks on minimal energy consumption and cost