Abstract
The real-time camera-equipped mobile devices have been widely researched recently. And cloud computing has been used to support those applications. However, the high communication latency and unstable connections between cloud and users influence the Quality of Service (QoS). To address the problem, we integrate fog computing and Software Defined Network (SDN) to the current architecture. Fog computing pushes the computation and storage resources to the network edge, which can efficiently reduce the latency and enable mobility support. While SDN offers flexible centralized control and global knowledge to the network. For applying the software defined cloud-fog network (SDC-FN) architecture in the real-time mobile face recognition scenario effectively, we propose leveraging the SDN centralized control and fireworks algorithm (FWA) to solve the load balancing problem in the SDC-FN. The simulation results demonstrate that the SDN-based FWA could decrease the latency remarkably and improve the QoS in the SDC-FN architecture.
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Acknowledgments
This work was supported in part by National Natural Science Foundation of China (No. 61401331, No. 61401328), 111 Project in Xidian University of China (B08038), Hong Kong, Macao and Taiwan Science and Technology Cooperation Special Project (2014DFT10320, 2015DFT10160), The National Science and Technology Major Project of the Ministry of Science and Technology of China (2015zx03002006-003) and Fundamental Research Funds for the Central Universities (20101155739).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Shi, C., Ren, Z., He, X. (2018). Research on Load Balancing for Software Defined Cloud-Fog Network in Real-Time Mobile Face Recognition. In: Chen, Q., Meng, W., Zhao, L. (eds) Communications and Networking. ChinaCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 210. Springer, Cham. https://doi.org/10.1007/978-3-319-66628-0_12
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DOI: https://doi.org/10.1007/978-3-319-66628-0_12
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