CNN: A Cluster-Based Named Data Routing for Vehicular Networks

Saeid Pourroostaei Ardakani, Chiew Foong Kwong, Pushpendu Kar, Qianyu Liu, Lincan Li

Research output: Journal PublicationArticlepeer-review

9 Citations (Scopus)


VANET routing aims to interconnect vehicular nodes via wireless links to transmit network packets. The goal of VANET routing is to reduce the communication cost, decrease the latency and increase the interoperability of the network. In this paper, a cluster-based routing protocol for VANETs called CNN is proposed. It takes advantage of the Hamming distance technique to partition a vehicular network into information-centric clusters based on the mobility of vehicular nodes. However, the proposed approach uses a named data network technique to forward network transmissions according to a hybrid communication model of Dedicated Short Range Communication and Mobile Agent. The former focuses on reactive intra-cluster link establishment, while the latter proactively forwards inter-cluster transmissions. A simulation measures the performance of the proposed approach and compares the results with two well-known VANET routing protocols: AODV and A- STAR. According to the simulation results, CNN outperforms the benchmarks in average end-to-end delay, path length, data delivery ratio, and total transmitted traffic, especially when the network is dense and the nodes are highly mobile.

Original languageEnglish
Pages (from-to)159036-159047
Number of pages12
JournalIEEE Access
Publication statusPublished - 2021


  • Computer networks
  • clustering pattern
  • data communication
  • data dissemination
  • vehicle routing

ASJC Scopus subject areas

  • Computer Science (all)
  • Materials Science (all)
  • Engineering (all)


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