An Efficient Handover Trigger Scheme for Vehicular Networks Using Recurrent Neural Networks-Reference-Cited by-同舟云学术

An Efficient Handover Trigger Scheme for Vehicular Networks Using Recurrent Neural Networks

Published:2019 Issue: Volume: Page:
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Container-title:Proceedings of the 15th ACM International Symposium on QoS and Security for Wireless and Mobile Networks - Q2SWinet'19
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Author:

Aljeri Noura¹,Boukerche Azzedine¹

Affiliation:

1. University of Ottawa, Ottawa, Canada

Publisher

ACM Press

Reference29 articles.

1. Noura Aljeri and Azzedine Boukerche. 2018. Mobility and Handoff Management in Connected Vehicular Networks. In Proceedings of the 16th ACM International Symposium on Mobility Management and Wireless Access (MobiWac'18). ACM, New York, NY, USA, 82--88.

2. Yuanguo Bi, Haibo Zhou, Wenchao Xu, Xuemin Sherman Shen, and Hai Zhao. 2016. An efficient PMIPv6-based handoff scheme for urban vehicular networks. IEEE transactions on intelligent transportation systems , Vol. 17, 12 (2016), 3613--3628.

3. Azzedine Boukerche, Alexander Magnano, and Noura Aljeri. 2017. Mobile IP Handover for Vehicular Networks: Methods, Models, and Classifications. ACM Computing Surveys (CSUR) , Vol. 49, 4 (2017), 73.

4. Felipe Cunha, Leandro Villas, Azzedine Boukerche, Guilherme Maia, Aline Viana, Raquel AF Mini, and Antonio AF Loureiro. 2016. Data communication in VANETs: Protocols, applications and challenges. Ad Hoc Networks , Vol. 44 (2016), 90--103.

5. Jan G de Gooijer, Bovas Abraham, Ann Gould, and Lecily Robinson. 1985. Methods for determining the order of an autoregressive-moving average process: A survey. International Statistical Review/Revue Internationale de Statistique (1985), 301--329.

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