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Evolutionary modeling and robustness analysis of multi-domain cooperative communication network under the environment of Internet of things

Author

Listed:
  • Jianrong Wang
  • Pan Zhang
  • Wei Bai
  • Guoyuan Yang
  • Yunyun Yang

Abstract

In the future, the Internet of things will reduce the cell radius and increase the number of low-power nodes to support thousands of times of traffic growth under 5G. As a virtual multiple input multiple output technology, cooperative communication technology can solve these problems effectively. According to the evolution characteristics of cooperative communication networks, a multi-domain cooperative communication network evolution model with preferential attachment and random attachment is constructed in this article. And then, the network properties and robustness are analyzed using the mean-field method and different attacks. Aiming at the resource constraints and resource allocation problems of communication nodes, a relay selection strategy based on the combination of maximum degree and minimum clustering coefficient is proposed. The simulation results show that the relay node selection strategy based on the combination of maximum degree and minimum clustering coefficient has significant advantages in selection steps and selection time, which greatly enhanced the performance of relay selection in multi-domain cooperative communication networks. Through real-time monitoring and updating of the performance and security indicators of the multi-domain cooperative communication networks, it provides a strong guarantee for the node deployment and security management of the Internet of things cooperative communication system.

Suggested Citation

  • Jianrong Wang & Pan Zhang & Wei Bai & Guoyuan Yang & Yunyun Yang, 2022. "Evolutionary modeling and robustness analysis of multi-domain cooperative communication network under the environment of Internet of things," International Journal of Distributed Sensor Networks, , vol. 18(11), pages 15501329221, November.
  • Handle: RePEc:sae:intdis:v:18:y:2022:i:11:p:15501329221135160
    DOI: 10.1177/15501329221135160
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