Green Cloud Computing-Oriented Algorithmic Approach-Based Virtual Machine Consolidation

Abstract

AbstractData centres are the hubs for global connectivity through networking. Cloud computing has become an indispensable need to fulfil the insatiable ever-expanding networking demand. More and more data centres are raised to fulfil this objective, consequently resulting in enhanced environmental pollution. Hence, server-related energy conservation is an indispensable need for minimizing carbon emissions. Factors like grid-related energy consumption and associated carbon emissions enhance electricity cost and carbon tax which results into total operating costs of data centres. The aim focuses on maximization of green energy usage with minimization of operating cost and carbon emission through process of virtual machine placement decision. Dynamic virtual machine consolidation emerges as a convincing solution for minimized energy consumption with optimized resource utilization in data centres. Virtual machine consolidation problems being truly NP-hard demand several heuristic algorithms for addressing the problem. Since most of the existing works are focussed for reducing number of hosts and their present resource utilization unmindful of future resource requirements, it results into unnecessary virtual machine migrations along with enhanced service-level agreement (SLA) violations. This problem can be duly addressed by considering current and future resource utilization by negotiating it as a bin-packing problem. The prediction of future resource utilization can be secured by using a k-nearest neighbour regression-based model.KeywordsVirtual machine placementEnergy efficiencyBin packingSLA