QoE enhancement in cloud virtual machine allocation using Eagle strategy of hybrid krill herd optimization

Abstract

This paper presents a novel VM allocation policy using the Eagle Strategy of Hybrid Krill Herd (KH) Optimization technique to enhance the cloud service experience to internet users. The Cloud Service provides data centre connectivity to share the resources through Virtual Machines (VM). The performance issue in Virtual Machine (VM) allocation during eccentrics degrades data centres load and clogging degrades the Quality of Experience (QoE) with Cloud Data Centres. Proposed optimized virtual machine allocation policy eradicates eccentrics effect and clogging effect, as it provides uninterrupted access throughput for better QoE. An optimization flag is additionally added in the Service Level Agreement (SLA). During burst load time, VM expansion is done automatically using Hybrid Krill Herd (KH) re-optimization if the optimization flag is set as true. Change and Response Protocol and Agreement Protocol have been proposed to predict the optimal resources for the Virtual Machine to avoid eccentrics and clogging. The prime parameters like delay, latency, packet rate and throughput are monitored continuously to activate the re-optimization and for achieving QoE with minimized load. Experimental analysis proves the capability of Hybrid KH algorithm over Particle Swarm Optimization, Ant Colony Optimization, Genetic Algorithm and Simulated Annealing algorithms.