Renewable Energy-Aware IoT Data Aggregation for Fog Computing
This paper considers the problem of renewable energy and spectrum allocation for a fog-based IoT network where the fog node can request energy from multiple renewable power suppliers (RPSs) to serve the end devices. We consider that RPSs of different relay nodes can form coalitions. RPSs in the same coalition can better coordinate their price strategy. Then, we analyze an independent RPS’s incentive to join a coalition or stay independent, and a nonindependent RPS’s incentive to deviate to join other coalitions or stay in present coalition. Then, in this paper, we achieve the Nash stable coalition structure, and the corresponding energy pricing for the structure. Finally, we give simulation results, and results show that RPSs, the fog node, and spectrum owner can benefit from coalitions.
KeywordsFog computing M2M communication Internet of things (IoT) Renewable energy Energy allocation Coalitions formation
This work was supported in part by the NSF of Jiangsu Province under Grant BK20161518 and Grant BK20171444, in part by the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, under Grant 2018D05, in part by the National Natural Science Foundation of China under Grant 61772287, Grant 61771252, and in part by the Open Research Fund of Jiangsu Engineering Research Center of Communication and Network Technology, NJUPT.
- 1.Mebrek, A., Merghem-Boulahia, L., Esseghir, M.: Efficient green solution for a balanced energy consumption and delay in the IoT-fog-cloud computing. In: 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA), pp. 1–4 (2017)Google Scholar
- 2.Yan, S., Peng, M., Wang, W.: User access mode selection in fog computing based radio access networks. In: 2016 IEEE International Conference on Communications (ICC), pp. 1–6 (2016)Google Scholar
- 3.Shen, S., Huang, L., Zhou, H., Yu, S.: Multistage signaling game-based optimal detection strategies for suppressing malware diffusion in fog-cloud-based IoT networks. IEEE Internet Things J. (2018)Google Scholar
- 4.Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing toward balanced delay and power consumptionGoogle Scholar
- 5.He, J., Wei, J., Chen, K., Tang, Z., Zhou, Y., Zhang, Y.: Multi-tier fog computing with large-scale IoT data analytics for smart cities. IEEE Internet Things J. 99 (2017)Google Scholar