An efficient IoT cloud energy consumption based on genetic algorithm

Abstract

Cloud computing is a promising technology which enables processing a great amount of data. In a large scale IoT infrastructure, optimum allocation of virtual machines to the physical hosts leads to reduce energy consumption of data centers. Moreover, it may prevent pollution of the environment and improve the efficiency. The comprehensive study of this research shows that employing the various methods of virtualization, proper combination of these methods and applying evolutionary strategies is promising to develop new algorithms. The developed novel algorithms could improve the energy efficiency of cloud computing. In this study, an effort is made to provide an optimum virtual machines allocation to physical hosts with employing imperialistic competitive (IC) and genetic algorithms (GA). Toward that end, the crossover operation from GA is mixed with IC. Cloudsim software is used for simulation and Netbean software for implementation. Considerable improvement on energy consumption is achieved through the proposed method.