SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR)

Chung-Ming Huang, Meng Shu Chiang, Wei Long Su, Duy Tuan Dao

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

1 Citation (Scopus)

Abstract

This paper proposed a control scheme for offloading vehicular communication traffic from the cellular network to V2V paths that can exist in Vehicular Ad Hoc Networks (VANETs). The Software Defined Network (SDN) architecture is adopted to tackle the complicated issues of VANET V2V offloading. The performance analysis for the proposed SDN-based offloading control scheme shows that it has better throughput in both the 4G link and the V2V paths when vehicle's density is in the middle.

Original languageEnglish
Title of host publication32nd International Conference on Information Networking, ICOIN 2018
PublisherIEEE Computer Society
Pages274-279
Number of pages6
ISBN (Electronic)9781538622896
DOIs
Publication statusPublished - 2018 Apr 19
Event32nd International Conference on Information Networking, ICOIN 2018 - Chiang Mai, Thailand
Duration: 2018 Jan 102018 Jan 12

Publication series

NameInternational Conference on Information Networking
Volume2018-January
ISSN (Print)1976-7684

Other

Other32nd International Conference on Information Networking, ICOIN 2018
CountryThailand
CityChiang Mai
Period18-01-1018-01-12

Fingerprint

Vehicular ad hoc networks
Network architecture
Telecommunication traffic
Throughput

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Huang, C-M., Chiang, M. S., Su, W. L., & Dao, D. T. (2018). SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR). In 32nd International Conference on Information Networking, ICOIN 2018 (pp. 274-279). (International Conference on Information Networking; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/ICOIN.2018.8343124
Huang, Chung-Ming ; Chiang, Meng Shu ; Su, Wei Long ; Dao, Duy Tuan. / SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR). 32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society, 2018. pp. 274-279 (International Conference on Information Networking).
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abstract = "This paper proposed a control scheme for offloading vehicular communication traffic from the cellular network to V2V paths that can exist in Vehicular Ad Hoc Networks (VANETs). The Software Defined Network (SDN) architecture is adopted to tackle the complicated issues of VANET V2V offloading. The performance analysis for the proposed SDN-based offloading control scheme shows that it has better throughput in both the 4G link and the V2V paths when vehicle's density is in the middle.",
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Huang, C-M, Chiang, MS, Su, WL & Dao, DT 2018, SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR). in 32nd International Conference on Information Networking, ICOIN 2018. International Conference on Information Networking, vol. 2018-January, IEEE Computer Society, pp. 274-279, 32nd International Conference on Information Networking, ICOIN 2018, Chiang Mai, Thailand, 18-01-10. https://doi.org/10.1109/ICOIN.2018.8343124

SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR). / Huang, Chung-Ming; Chiang, Meng Shu; Su, Wei Long; Dao, Duy Tuan.

32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society, 2018. p. 274-279 (International Conference on Information Networking; Vol. 2018-January).

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

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Huang C-M, Chiang MS, Su WL, Dao DT. SDN-based V2V offloading for cellular network using the LifeTime-based network state routing (LT-NSR). In 32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society. 2018. p. 274-279. (International Conference on Information Networking). https://doi.org/10.1109/ICOIN.2018.8343124