Imperial College London
Alternate

ProfessorKinLeung

Faculty of Engineering, Department of Electrical and Electronic Engineering

Tanaka Chair in Internet Technology
 
 
 
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Contact

 

+44 (0)20 7594 6238kin.leung Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

810aElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Rossi:2017:10.1109/WCNC.2017.7925786,
author = {Rossi, G and Fan, Z and Chin, WH and leung, KK},
doi = {10.1109/WCNC.2017.7925786},
title = {Stable clustering for Ad-Hoc vehicle networking},
url = {http://dx.doi.org/10.1109/WCNC.2017.7925786},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Vehicular ad-hoc networks (VANETs) that enable communication among vehicles and between vehicles and un- manned aerial vehicles (UAVs) and cellular base stations have re- cently attracted significant interest from the research community, due to the wide range of practical applications they can facilitate (e.g. road safety, traffic management, pollution monitoring and rescue missions). Despite this increased research activity, the high vehicle mobility in a VANET raises concerns regarding the robustness and adaptiveness of such networks to support system applications. Instead of allowing direct communications between every vehicle to UAVs or base stations, clustering methods will potentially be efficient to overcome bandwidth, power consump- tion and other resource issues. Using the clustering technique, neighbouring vehicles are grouped into clusters with a particular vehicle elected as the Custer Head (CH) in each cluster. Each vehicle communicates with UAVs or base stations through the CH of the associated cluster. Despite the potential advantages, a major challenge for clustering techniques is to maintain cluster stability in light of vehicle mobility and radio fluctuation. In this paper, we propose a Stable Clustering Algorithm for vehicular ad hoc networks (SCalE). Two novel features are incorporated into the algorithm: knowledge of the vehicles behaviour for efficient selection of CHs, and the employment of a backup CH to maintain the stability of cluster structures. By simulation methods, these are shown to increase stability and improve performance when compared to existing clustering algorithms.
AU  - Rossi,G
AU  - Fan,Z
AU  - Chin,WH
AU  - leung,KK
DO  - 10.1109/WCNC.2017.7925786
PY  - 2017///
SN  - 1558-2612
TI  - Stable clustering for Ad-Hoc vehicle networking
UR  - http://dx.doi.org/10.1109/WCNC.2017.7925786
UR  - http://hdl.handle.net/10044/1/47917
ER  -
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