Leveraging ICN with network sensing for intelligent transportation systems: a dynamic naming approach

Chen Wang, Jun Wu, Xi Zheng, Bei Pei, Xuyun Zhang, Dongjin Yu, Junhua Tang

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The network sensing and tracking over the huge transportation network composed of a large number of vehicles and facilities are the basic functions of the Intelligent Transportation Systems, which is an important component of the Smart City. In the transportation network supported by the Information-Centric Network, the traditional static naming is adopted, and the track function is completed at the application layer. At the same time, a large amount of network status information that is continuously sensed consumes routing space. This paper proposes a Dynamic Naming approach to sense the Intelligent Transportation Systems network. It uses dynamic naming to describe the status of the changeable objects in the Intelligent Transportation Systems network sensed by the system, and adopts a block centralized storage structure to organize the routing table, which reduces redundant information and makes full use of routing space and historical routing information for network sensing. The Dynamic Naming approach shortens the query time, improves the efficiency of network sensing, and provides a new solution at the routing level to sense and track the status of dynamic objects in Intelligent Transportation Systems.
Original languageEnglish
Pages (from-to)15875-15884
Number of pages10
JournalIEEE Sensors Journal
Volume21
Issue number14
Early online date25 Jun 2020
DOIs
Publication statusPublished - 15 Jul 2021

Keywords

  • intelligent transportation systems
  • Dynamic naming
  • information-centric network
  • network sensing

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