Adaptive Network Segmentation and Channel Allocation in Large scale V2X Communication Networks
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 17320708
- Type
- D - Journal article
- DOI
-
10.1109/TCOMM.2018.2868080
- Title of journal
- IEEE Transactions on Communications
- Article number
- -
- First page
- 405
- Volume
- 67
- Issue
- 1
- ISSN
- 0096-1965
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- 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)
-
F - Cyber Security and Network Systems (CyberNets)
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is a collaborative work between researchers from University of Surrey, University of Warwick, Northumbria Univesity and Jaguar Land Rover (Industrial Partner). The research work was supported in part by the U.K.-EPSRC ‘Towards Autonomy: Smart and Connected Control (TASCC) Programme under Grant EP/N01300X/1’. The novel MAC scheme called segmentation MAC (SMAC) proposed in this work provides significant performance gains in terms of throughput as compared to the existing schemes. The comprehensive analytical model proposed in this work is a significant contribution towards determining the multi-hop dissemination latency and provides a platform for analytical modeling in other similar networks.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
