An Altruistic Prediction-Based Congestion Control for Strict Beaconing Requirements in Urban VANETs
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2341
- Type
- D - Journal article
- DOI
-
10.1109/TSMC.2017.2759341
- Title of journal
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Article number
- -
- First page
- 2582
- Volume
- 49
- Issue
- 12
- ISSN
- 2168-2216
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2018
- URL
-
https://e-space.mmu.ac.uk/619213/
- 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
-
2
- Research group(s)
-
D - Smart Infrastructure
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper introduces a proactive approach for the resolution of beacon congestion problems in vehicular networks. Solving this issue is critical for safety, efficiency and environmental impacts. We are invited to present this work at IEEE ISC2 2020 and it enabled the successful award of a JSPS fellowship in Japan (fellowship ID S21005). The paper underpinned a Marie Skłodowska-Curie Actions Individual Fellowship on Vehicular Edge Computing (Id: SEP-210688532, awaiting outcome) in collaboration with University of La Rochelle, The University of Electro Communications and the University of Hawaii at Manoa supported by Transport for Greater Manchester (Sam Li Sam.Li@tfgm.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -