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Renewable Energy Powered IoT Data Traffic Aggregation for Edge Computing

  • Cunchao Peng
  • Dapeng LiEmail author
  • Feng Tian
  • Yongan Guo
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 517)

Abstract

With the development of the Internet of Things (IoT) industry and the arrival of the 5G era, edge computing is considered to be the more suitable computing technology for the IoT. In this paper, we propose an edge-computing-based M2M data aggregation wireless transmission system powered by efficient renewable energy allocation servicing for the edge devices. The pricing scheme problem is formulated as a Stackelberg game between the operator and multi-RPSs. Simulation results show how the previous pricing scheme and bandwidth of each node affect the renewable energy storage levels of each RPS and his own profit. The results also show the operator’s optimal service price scheme and the equilibrium renewable energy storage level of each RPS.

Keywords

Edge computing M2M communication IoT Renewable Energy Supplier (RPS) Pricing scheme Simultaneous decisions Sequential decisions 

Notes

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.

References

  1. 1.
    Cisco White Paper: Global Mobile Data Traffic Forecast Update, 2016–2021, Cisco Visual Networking Index, pp. 1–5, Feb 2017Google Scholar
  2. 2.
    Dastjerdi, A., Buyya, R.: Fog Computing: Helping the Internet of Things Realize its Potential. IEEE Computer Society, pp. 112–116 (2016)CrossRefGoogle Scholar
  3. 3.
    Chen, X., Shi, Q., Yang, L., Xu, J.: Thriftyedge: resource-efcient edge computing for intelligent IoT applications. IEEE Netw. 61–64, Jan 2018CrossRefGoogle Scholar
  4. 4.
    Chang, Y., Chen, S., Wang, T., Lee, Y.: Fog computing node system software architecture and potential applications for NB-IoT industry. In: IEEE International Computer Symposium, pp. 727–730 (2016)Google Scholar
  5. 5.
    Mao, Y., Zhang, J., Song, S.H., et al.: Power-delay tradeoff in multi-user mobile-edge computing systems. In: IEEE Global Communications Conference, pp. 1–6, Dec 2016Google Scholar
  6. 6.
    Kiani, A., Ansari, N.: Edge computing aware NOMA for 5G networks. IEEE Internet Things J. 1–7 (2017)Google Scholar
  7. 7.
    Fawal, A., Mansour, A., Roy, F., Jeune, D., Hamie, A.: RACH overload congestion mechanism for M2M communication in LTE-a: issues and approaches. In: International Symposium on Networks, pp. 1–6, May 2017Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Cunchao Peng
    • 1
  • Dapeng Li
    • 1
    • 2
    Email author
  • Feng Tian
    • 1
  • Yongan Guo
    • 1
  1. 1.Jangsu Engineering Research Center of Communication and Network TechnologyNanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.National Mobile Communications Research LaboratorySoutheast UniversityNanjingChina

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