Safeguarding Cloud Services Sustainability by Dynamic Virtual Machine Migration with Re-allocation Oriented Algorithmic Approach

Abstract

Data centres are networking platforms which exhibit virtual machine workload execution in a dynamic manner. As the users’ requests are of enormous magnitude, it manifests as overloaded physical machines resulting in quality of service degradation and SLA violations. This challenge can be negotiated by exercising a better virtual machine allocation by dint of re-allocating a subset of active virtual machines at a suitable destined server by virtual machine migration. It is exhibited as improved resource utilization with enhanced energy efficiency along with addressing the challenge of impending server overloading resulting in downgraded services. The aforesaid twin factors of enhanced energy consumption and enhanced resource utilization can be suitably addressed by combining them together as a single objective function by utilizing cost function based best-fit decreasing heuristic. It enhances the potentials for aggressively migrating large capacity applications like image processing, speech recognition, and decision support systems. It facilitates a seamless and transparent live virtual machine migration from one physical server to another along with taking care of cloud environment resources. The identification of most appropriate migration target host is executed by applying modified version of best-fit decreasing algorithm with respect to virtual machine dynamic migration scheduling model. By executing the selection algorithm, the hotspot hosts in cloud platform are segregated. Subsequently, virtual machine-related resource loads are identified in descending order with respect to hotspots. The resource loads pertaining to non-hotspot hosts are identified in ascending order. Next, the traversing manoeuvring in non-hotspot hosts queue is exercised for identification of the most appropriate host to be reckoned as migration target host.