A Dynamic Evolution Mechanism for IoV Community in an Urban Scene

Jiujun Cheng, Chunrong Cao, Mengchu Zhou, Cong Liu, Shangce Gao, Changjun Jiang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Existing work on the Internet-of-Vehicles (IoV) community mainly focuses on the detection of IoV community using static network detection and evolution methods of complex networks. These methods are prone to over-centralization, high computational complexity, and poor stability during the evolution of a community. In this work, we present an IoV community model and its evolution mechanism in an urban scene. More specifically, we first propose an IoV community detection model based on node similarity merging. Then, we use a network increment-based strategy to analyze node increment, edge increment, and weight increment. Finally, we give a dynamic evolution mechanism of an IoV community. Simulation-based experimental evaluation results show that the proposed mechanism achieves better real-time performance and accuracy than existing methods.

Original languageEnglish (US)
Article number9266057
Pages (from-to)7521-7530
Number of pages10
JournalIEEE Internet of Things Journal
Issue number9
StatePublished - May 1 2021

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


  • Community model
  • Internet of Vehicles (IoV)
  • dynamic evolution
  • network incremental-based
  • urban scene


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