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http://dx.doi.org/10.3837/tiis.2016.02.003

Dynamic Scheduling Method for Cooperative Resource Sharing in Mobile Cloud Computing Environments  

Kwon, Kyunglag (Department of Computer and Information Science, Korea University)
Park, Hansaem (Department of Computer and Information Science, Korea University)
Jung, Sungwoo (Department of Computer and Information Science, Korea University)
Lee, Jeungmin (Department of Computer and Information Science, Korea University)
Chung, In-Jeong (Department of Computer and Information Science, Korea University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.10, no.2, 2016 , pp. 484-503 More about this Journal
Abstract
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.
Keywords
Mobile resource management and sharing; mobile computing; job scheduling; cooperative computing;
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