VANET aided D2D Discovery: Delay Analysis and Performance
- Submitting institution
-
Edinburgh Napier University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1109769
- Type
- D - Journal article
- DOI
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10.1109/TVT.2017.2690238
- Title of journal
- IEEE Transactions on Vehicular Technology
- Article number
- -
- First page
- 8059
- Volume
- 66
- Issue
- 9
- ISSN
- 0018-9545
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 16
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- It is the first in vehicular communications that implements device to device (D2D) discovery using vehicular networks for offloading purposes. It established a new avenue for offloading in multi-lane networks for the first time. A short version of this paper was presented in the IEEE flagship conference, WCNC 2016. Led to Al-Dubai being invited to give a Plenary Speech at ACM MISC 2018 https://misc2018.misc-lab.org/speakers.html. It formed the basis for a continuing international collaboration with the co-authors in the American University of Beirut and resulted in joint three follow-up papers: 10.1109/TGCN.2018.2813060, 10.1109/ACCESS.2018.2879436, 10.1109/COMST.2018.2874356; and two joint PhD supervisions.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -