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Issue No. 01 - Jan.-March (2018 vol. 6)
ISSN: 2168-6750
pp: 72-84
Rong Yu , School of Automation, Guangdong University of Technology, Guangzhou, China
Jiefei Ding , School of Automation, Guangdong University of Technology, Guangzhou, China
Sabita Maharjan , Simula Research Laboratory, Fornebu, Norway
Stein Gjessing , Simula Research Laboratory, Fornebu, Norway
Yan Zhang , Simula Research Laboratory, Fornebu, Norway
Danny H. K. Tsang , Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong
ABSTRACT
Mobile cloud computing is a key enabling technology in the era of the Internet of Things. Geo-distributed mobile cloud computing (GMCC) is a new scenario that adds geography consideration in mobile cloud computing. In GMCC, users are able to access cloud resources that are geographically close to their mobile devices. This is expected to reduce the communication delay and the service providers’ cost compared with the traditional centralized approach. In this paper, we focus on resource sharing through the cooperation among the service providers in geo-distributed mobile cloud computing. Then, we propose two different strategies for efficient resource cooperation in geographically distributed data centers. Furthermore, we present a coalition game theoretical approach to deal with the competition and the cooperation among the service providers. Utility functions have been specifically considered to incorporate the cost related to virtual machine migration and resource utilization. Illustrative results indicate that our proposed schemes are able to efficiently utilize limited resources with quality-of-service consideration.
INDEX TERMS
Resource management, Mobile communication, Cloud computing, Mobile handsets, Bandwidth, Vehicles, Servers
CITATION

R. Yu, J. Ding, S. Maharjan, S. Gjessing, Y. Zhang and D. H. Tsang, "Decentralized and Optimal Resource Cooperation in Geo-Distributed Mobile Cloud Computing," in IEEE Transactions on Emerging Topics in Computing, vol. 6, no. 1, pp. 72-84, 2018.
doi:10.1109/TETC.2015.2479093
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