On Geocasting over Urban Bus-Based Networks by Mining Trajectories

Fusang Zhang, Beihong Jin*, Zhaoyang Wang, Hai Liu, Jiafeng Hu, Lifeng Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

51 Citations (Scopus)

Abstract

Bus networks in cities have distinctive features such as wide coverage and fixed bus routes so that they show the potential of forming the communication backbone in vehicular ad hoc networks (VANETs). This paper focuses on the geocast in bus-based VANETs and presents a geocast routing mechanism named Vela. Specifically, Vela analyzes and mines historical bus trajectories and characterizes spatial–temporal patterns (i.e., bus travel-time patterns and bus spatial encounter patterns) in a moderate granularity of road segments, which makes the mined patterns both accurate and steady. Furthermore, Vela exploits these acquired patterns to build a probabilistic spatial–temporal graph model and provides the available routing paths with the best possible quality-of-service levels for data delivery requests. Moreover, Vela also employs a two-hop aware strategy that utilizes the real-time spatial–temporal relationships between buses to increase the chances of forwarding the data. The results of the experiments on the real and synthetic trajectories show that Vela performs much better in terms of delivery ratio and delay and has stronger scalability than the other solutions.

Original languageEnglish
Pages (from-to)1734-1747
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Volume17
Issue number6
Early online date29 Feb 2016
DOIs
Publication statusPublished - Jun 2016

Scopus Subject Areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

User-Defined Keywords

  • bus-based routing
  • time series analysis
  • trajectory mining
  • Vehicular ad hoc networks

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