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

Authors
Kwon, KyunglagPark, HansaemJung, SungwooLee, JeungminChung, In-Jeong
Issue Date
29-2월-2016
Publisher
KSII-KOR SOC INTERNET INFORMATION
Keywords
Mobile resource management and sharing; mobile computing; job scheduling; cooperative computing
Citation
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.10, no.2, pp.484 - 503
Indexed
SCIE
SCOPUS
KCI
Journal Title
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Volume
10
Number
2
Start Page
484
End Page
503
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/89464
DOI
10.3837/tiis.2016.02.003
ISSN
1976-7277
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.
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