An Optimal Heuristic Model for Greedy and Efficient Consolidation Process in Cloud Datacenters
Archana Patil, Rekha Patil · 2020
Today, cloud computing has become an integrated solution for the entrepreneurs to deploy their business applications and to obtain the immense advantages of the cloud. Virtualization increased the cloud productivity and decreased the energy consumption by mapping the physical systems into logical virtual machines. Uneven distribution of load among the hosts may generate the host over subscription and under subscription issues, which impacts negatively on QoS management and energy consumption of cloud. Server consolidation is the convenient solution for handling the host underutilization issues. Although the former researches were proposed several advancements in consolidation, it is still suffering in selection of optimal threshold values and controls the aggressive migrations. This research work has proposed an optimal heuristic model for greedy and efficient consolidation process in cloud datacenters. Experimental results proven that the proposed consolidation model defined an optimal threshold value to save the energy and the greedy consolidation policy controlled the aggressive migrations better than the former consolidation models.