Grey Wolf Optimizer based Resource Allocation and Optimization Algorithm in Cloud Computing Environment

Abstract

Abstract The Internet of Things (IoT) is a scattered structure where every item links with internet for communication. The IoT structure is composed by several resources and gateways or cluster heads. So in this environment, IoT resource allocation and scheduling task is a crucial challenge. The resource allocation and resource scheduling process are responsible to perform mapping between IoT resources and gateways and also deals with optimized resource allocation at gateways. In the real scenario, each gateway may face heavy traffics and that may create the overhead so allocatingand scheduling resources manually is not a feasible solution. Therefore, in this research work we introduce a hybrid approach to optimize the resources so that we can achieve the minimum transmission cost. The proposed approach is based on Grey Wolf Optimizer (GWO) algorithm. The GWO has been designed by motivation from the civic activity specially searching and hunting prey of grey wolves. The introduced hybrid GWO has been tested on the several benchmark functions and got the satisfied result.