NTR: An efficient trajectory-based routing protocol for the vehicular delay tolerant networks

Ing Chau Chang, Ming Han Hung, Ching Ru Chang, Chin En Yen

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

Traditional vehicular routing protocols cannot accurately foresee future location of each vehicle for efficient packet forwarding. Recently, the data mining approach has been applied to analyze huge vehicle trajectory data. In this paper, we propose a novel trajectory-based routing (NTR) protocol to improve the packet replication efficiency of vehicles in the Vehicular Delay Tolerant Network (VDTN). By integrating the data mining technique, NTR first establishes the trajectory tree of each vehicular node based on its trajectory data. With this kind of trajectory trees, NTR then predicts future location of each vehicle and derives its contact possibilities with all other vehicles. Hence, NTR creates the vehicle encounter trees and the packet delivery graphs to predict the optimal Store-Carry-Forward (SCF) route for spraying the optimal number of packet tokens among intermediate nodes from the packet source vehicle to the destination one. Finally, we use the Opportunistic Network Environment (ONE) simulator to perform simulations. From performance results, we conclude that NTR significantly outperforms several well-known VDTN routing protocols, in terms of the average packet delivery ratio, average end-to-end delay and average packet forwarding overhead.

原文English
主出版物標題2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面389-394
頁數6
ISBN(電子)9781538616451
DOIs
出版狀態Published - 2017 十一月 27
事件2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
持續時間: 2017 十月 52017 十月 8

出版系列

名字2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
2017-January

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
國家Canada
城市Banff
期間17-10-0517-10-08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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