Advertisement

Reliability Oriented Probe Deployment Strategy for Power Cellular Internet of Things

  • Lei Wei
  • Daohua ZhuEmail author
  • Wenwei Chen
  • Yukun Zhu
  • Lin Peng
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 905)

Abstract

With the power cellular Internet of Things (IoT) communication system playing a more and more important role for information transmission, exchange, and processing in the smart grid, higher requirements for the maintenance management and monitoring technologies need to be satisfied. However, at present, the monitoring capability of the power cellular IoT communication network is relatively scarce, resulting in grid data transmission has to rely on the public network. The security, reliability, and real-time performance cannot be guaranteed. Therefore, this paper focuses on the characteristics of power wireless networks, studies the technology of distributed service quality monitoring, and designs a deployment strategy for Power Cellular Internet of Things to monitor performance nodes. We first introduce the loop rate of deployment probes as the evaluation index of network reliability, and model the minimum weighted vertex coverage problem of probe deployment as the largest weighted independent set problem. Then we propose a fast heuristic algorithm to find its minimum deployment overhead with satisfying reliability requirement. The simulation results show that the proposed algorithm can improve the ability of the smart grid for locating faults quickly and effectively, as well as the comprehensive monitoring and management capability, improving network performance.

Keywords

Probe deployment Power Cellular IoT Heuristic algorithm Reliability 

Notes

Acknowledgement

This study is supported by 2017 state grid science and technology project “Research and Application for Adaption of Power Business based on LTE Wireless Private Network”.

References

  1. 1.
    Yin, H., Li, F.: Research on the development of the internet performance measurement technologies. J. Comput. Res. Dev. 53(1), 3–14 (2016)Google Scholar
  2. 2.
    Zhang, S., Lin, S., He, Z., Lee, W.J.: Ground fault location in radial distribution networks involving distributed voltage measurement. IET Gener. Transm. Distrib. 12(4), 987–996 (2018)CrossRefGoogle Scholar
  3. 3.
    Gao, J.L., Xu, Y.J., Li, X.W.: Weighted-median based distributed fault detection for wireless sensor networks. J. Softw. 5, 1208–1217 (2007)CrossRefGoogle Scholar
  4. 4.
    Pan, S., Zhang, Z., Yu, F., Hu, G.: End-to-end measurements for network tomography under multipath routing. IEEE Commun. Lett. 18(5), 881–884 (2014)CrossRefGoogle Scholar
  5. 5.
    Ge, H.W., Peng, Z.Y., Yue, H.B.: Hybrid optimization algorithm for efficient monitor-nodes selection in network traffic. Appl. Res. Comput. 4, 1480–1483 (2009). 1486Google Scholar
  6. 6.
    McGregor, T., Braun, H.W., Brown, J.: The NLANR network analysis infrastructure. IEEE Commun. Mag. 38(5), 122–128 (2000)CrossRefGoogle Scholar
  7. 7.
    Khan, U.A., Kar, S., Moura, J.M.F.: Distributed sensor localization in random environments using minimal number of anchor nodes. IEEE Trans. Signal Process. 57(5), 2000–2016 (2009)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Wu, Q., Hao, J.K.: A review on algorithms for maximum clique problems. Eur. J. Oper. Res. 242(3), 693–709 (2015)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Avis, D., Imamura, T.: A list heuristic for vertex cover. Oper. Res. Lett. 35(2), 201–204 (2007)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Battiti, R., Passerini, A.: Brain-computer evolutionary multiobjective optimization: a genetic algorithm adapting to the decision maker. IEEE Trans. Evol. Comput. 14(5), 671–687 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Lei Wei
    • 1
  • Daohua Zhu
    • 2
    Email author
  • Wenwei Chen
    • 3
  • Yukun Zhu
    • 3
  • Lin Peng
    • 4
  1. 1.State Grid Jiangsu Electric Power Company, Ltd.NanjingChina
  2. 2.Electric Power Research InstituteState Grid Jiangsu Electric Power Company, Ltd.NanjingChina
  3. 3.State Grid Information and Telecommunication Group, Ltd.BeijingChina
  4. 4.Beijing Vectinfo Technologies Company, Ltd.BeijingChina

Personalised recommendations