期刊
IEEE ACCESS
卷 5, 期 -, 页码 13578-13586出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2728624
关键词
Cloud computing; fog computing; operational cost; load balancing; parallel and distributed algorithm; proximal jacobian ADMM
资金
- National Natural Science Foundation of China [61502252, 61302104, 61401223, 61522109, 61631020, 61671253]
- Natural Science Foundation of Jiangsu Province [BK20150869, BK20140887, BK20150040]
- Natural Science Research of Higher Education Institutions of Jiangsu Province [15KJA510003]
- Nanjing University of Posts and Telecommunications [NY214187]
In this paper, we intend to reduce the operational cost of cloud data centers with the help of fog devices, which can avoid the revenue loss due to wide-area network propagation delay and save network bandwidth cost by serving nearby cloud users. Since fog devices may not be owned by a cloud service provider, they should be compensated for serving the requests of cloud users. When taking economical compensation into consideration, the optimal number of requests processed locally by each fog device should be decided. As a result, existing load balancing schemes developed for cloud data centers cannot be applied directly and it is very necessary to redesign a cost-ware load balancing algorithm for the fog cloud system. To achieve the above aim, we first formulate a fog-assisted operational cost minimization problem for the cloud service provider. Then, we design a parallel and distributed load balancing algorithm with low computational complexity based on proximal Jacobian alternating direction method of multipliers. Finally, extensive simulation results show the effectiveness of the proposed algorithm.
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