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Renewable Energy-Aware IoT Data Aggregation for Fog Computing

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Book cover Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 517))

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Abstract

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.

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References

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Acknowledgments

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.

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Correspondence to Dapeng Li .

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Fu, Y., Li, D., Tian, F., Guo, Y. (2020). Renewable Energy-Aware IoT Data Aggregation for Fog Computing. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_104

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  • DOI: https://doi.org/10.1007/978-981-13-6508-9_104

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6507-2

  • Online ISBN: 978-981-13-6508-9

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