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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages389-394
Number of pages6
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Publication series

Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period17-10-0517-10-08

Fingerprint

Delay tolerant networks
Delay Tolerant Networks
Vehicular Networks
Routing Protocol
Routing protocols
Routing
Trajectories
Trajectory
Data mining
Data Mining
Predict
Network routing
End-to-end Delay
Network Protocols
Spraying
Vertex of a graph
Replication
Simulator
Simulators
Contact

All Science Journal Classification (ASJC) codes

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

Cite this

Chang, I-C., Hung, M. H., Chang, C. R., & Yen, C. E. (2017). NTR: An efficient trajectory-based routing protocol for the vehicular delay tolerant networks. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (pp. 389-394). (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8122635
Chang, Ing-Chau ; Hung, Ming Han ; Chang, Ching Ru ; Yen, Chin En. / NTR : An efficient trajectory-based routing protocol for the vehicular delay tolerant networks. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 389-394 (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017).
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abstract = "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.",
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Chang, I-C, Hung, MH, Chang, CR & Yen, CE 2017, NTR: An efficient trajectory-based routing protocol for the vehicular delay tolerant networks. in 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 389-394, 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, Banff, Canada, 17-10-05. https://doi.org/10.1109/SMC.2017.8122635

NTR : An efficient trajectory-based routing protocol for the vehicular delay tolerant networks. / Chang, Ing-Chau; Hung, Ming Han; Chang, Ching Ru; Yen, Chin En.

2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 389-394 (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - 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.

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Chang I-C, Hung MH, Chang CR, Yen CE. NTR: An efficient trajectory-based routing protocol for the vehicular delay tolerant networks. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 389-394. (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017). https://doi.org/10.1109/SMC.2017.8122635