Authors : R.B. Madhumala, Harshvardhan Tiwari and C. Devarajaverma
Abstract: To meet the ever-growing demand for the online computational resources, it is mandatory to have the best resource allocation algorithm to allocate the resources to its end users. Virtual machine placement is the key technology in improving the resource utilization and thereby reduces the power consumption. In this study, particle swarm optimization algorithm is used to address VM-PM placement problem. This can be addressed by reducing the number of physical machines over the cloud datacenters. In our study, we discuss how to improve the efficiency of particle swarm Intelligence by adapting efficient mechanism to reduce the power consumption in cloud data centers by maximizing the resource utilization. The obtained results shows that proposed Particle Swarm Optimization (PSO) provide the optimized solution compared to the existing algorithms.
R.B. Madhumala, Harshvardhan Tiwari and C. Devarajaverma, 2020. Improved Particle Swarm Optimization for Virtual Machine Selection in Cloud Datacenter. Asian Journal of Information Technology, 19: 284-288.