An Adaptive Virtual Machine Location Selection Mechanism in Distributed Cloud
Kyunglag Kwon, Han-Saem Park, Jung Sung-Woo, Jeungmin Lee, In-Jeong Chung · KSII Transactions on Internet and Information Systems · 2016
Mobile cloud computing has recently become a new paradigm for the utilization of a variety of shared mobile resources via wireless network environments.However, due to the inherent characteristics of mobile devices, a limited battery life, and a network access requirement, it is necessary for mobile servers to provide a dynamic approach for managing mobile resources efficiently in mobile cloud computing environments.Since on-demand job requests occur frequently and the number of mobile devices is drastically increased in mobile cloud computing environments, a different mobile resource management method is required to maximize the computational power.In this paper, we therefore propose a cooperative, mobile resource sharing method that considers both the inherent properties and the number of mobile devices in mobile cloud environments.The proposed method is composed of four main components: mobile resource monitor, job handler, resource handler, and results consolidator.In contrast with conventional mobile cloud computing, each mobile device under the proposed method can be either a service consumer or a service provider in the cloud.Even though each device is resource-poor when a job is processed independently, the computational power is dramatically increased under the proposed method, as the devices cooperate simultaneously for a job.Therefore, the mobile computing power throughput is dynamically increased, while the computation time for a given job is reduced.We conduct case-based experiments to validate the proposed method, whereby the feasibility of the method for the purpose of cooperative computation is shown.