High-efficient energy saving processing of big data of communication under mobile cloud computing

Abstract

From 21st century, it is hard for traditional storage and algorithm to provide service with high quality because of big data of communication which grows rapidly. Thus, cloud computing technology with relatively low cost of hardware facilities is created. However, to guarantee the quality of service in the situation of the rapid growth of data volume, the energy consumption cost of cloud computing begins to exceed the hardware cost. In order to solve the problems mentioned above, this study briefly introduced the virtual machine and its energy consumption model in the mobile cloud environment, introduced the basic principle of the virtual machine migration strategy based on the artificial bee colony algorithm and then simulated the performance of processing strategy to big data of communication based on artificial bee colony algorithm in mobile cloud computing environment by CloudSim3.0 software, which was compared with the performance of two algorithms, resource management (RM) and genetic algorithm (GA). The results showed that the power consumption of the migration strategy based on the artificial bee colony algorithm was lower than the other two strategies, and there were fewer failed virtual machines under the same number of requests, which meant that the service quality was higher.