Effective Prediction of V2I Link Lifetime and Vehicle's Next Cell for Software Defined Vehicular Networks: A Machine Learning Approach-Reference-Cited by-同舟云学术

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Effective Prediction of V2I Link Lifetime and Vehicle's Next Cell for Software Defined Vehicular Networks: A Machine Learning Approach

Published:2019-12 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE Vehicular Networking Conference (VNC)
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Author:

Toufga Soufian,Abdellatif Slim,Owezarski Philippe,Villemur Thierry,Relizani Doria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9047648/9062769/09062803.pdf?arnumber=9062803

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A UAV-Assisted Handover Scheme for Coverage Maximization against 5G Coverage Holes;2023 14th International Conference on Information and Communication Technology Convergence (ICTC);2023-10-11

2. A Review of Blockchain Technology in Knowledge-Defined Networking, Its Application, Benefits, and Challenges;Network;2023-08-30

3. A Comprehensive Survey on Knowledge-Defined Networking;Telecom;2023-08-02

4. Handover Predictions as an Enabler for Anticipatory Service Adaptations in Next-Generation Cellular Networks;Proceedings of the 20th ACM International Symposium on Mobility Management and Wireless Access on 20th ACM International Symposium on Mobility Management and Wireless Access;2022-10-24

5. A Deep Learning-Based Model for Link Quality Estimation in Vehicular Networks;IETE Journal of Research;2021-09-23

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