Review of existing variants of Grey Wolf Optimization algorithm handling Load Balancing in Clouds

Abstract

Cloud computing has earned lot of awarenes in the Information Technology and now appeared as the next level in the evolution of Internet. But now it has been observed that the Load balancing (LB) is one among various challenges in cloud computing that needs to be resolved to perform the accurate operations on cloud and also to obtain the rapid development in the the sphere of cloud computing. The demand of various customers all over the world for the services used to increase the load rapidly. Therefore load balancing required to equally distribute the workload over each and every virtual machine in the cloud system hence as a result the throughput increases and the response time minimizes. The aim of load balancing is to build the client satisfaction, resource utilization maximisation and improvement in the cloud system performance leads to reduction in energy consumption and heat dissipation. In the present paper, the standard Grey Wolf Optimisation algorithm for load balancing is demonstrated for the cloud environment. Also the other versions of Grey wolf optimisation has been studied to know the issues related to them and additional functionality required by them to achieve the higher system performance. Furthermore, according to the surveyed research papers it has been seen that now the performance of the proposed hybrid Grey Wolf Optimisation algorithms is simulated by using Cloudsim simulator on the basis of different parameters such as throughput and response time etc.