TY  - JOUR
T1  - Improved Particle Swarm Optimization for Virtual Machine Selection in Cloud Datacenter
AU - Madhumala, R.B. AU - Tiwari, Harshvardhan AU - Devarajaverma, C. 
JO  - Asian Journal of Information Technology
VL  - 19
IS  - 12
SP  - 284
EP  - 288
PY  - 2020
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2020.284.288
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2020.284.288
KW  - particle swarm optimization
KW  -virtual machine optimization
KW  -Cloud computing
KW  -energy efficiency
KW  -resource allocation
KW  -nature inspired algorithms
AB  - 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.
ER  -