DocumentCode :
1361550
Title :
Measuring Disruption in Vehicular Communications
Author :
Hasan, Syed Faraz ; Ding, Xuemei ; Siddique, Nazmul H. ; Chakraborty, Shyam
Author_Institution :
Intell. Syst. Res. Center, Univ. of Ulster-Magee, Londonderry, UK
Volume :
60
Issue :
1
fYear :
2011
Firstpage :
148
Lastpage :
159
Abstract :
Recent studies have shown that roadside wireless local area network (WLAN) access points (APs) can provide network access from vehicles. However, the unplanned deployment of WLAN APs is the main hurdle in the provision of continuous network services. Because of this unplanned deployment, a mobile node moving at vehicular speed experiences periods of connectivity and disruption as it exploits roadside WLAN APs. Although several works have studied the performance of WLAN APs in providing network services at vehicular speed, very little has been reported on their mathematical interpretation. This paper proposes a hidden Markov model (HMM) to represent a typical roadside-to-vehicle communication. The proposed model is based on the experimental findings and is used to quantify the probabilistic measure of disruption. To the best of the authors´ knowledge, this is the first effort that quantifies the aggregate amount of disruption in 802.11-based roadside-to-vehicle communications.
Keywords :
hidden Markov models; mobile radio; wireless LAN; 802.11-based roadside-to-vehicle communications; HMM; WLAN; access points; continuous network services; hidden Markov model; mathematical interpretation; mobile node; roadside wireless local area network; Cities and towns; Hidden Markov models; Intelligent systems; Mathematical model; Mobile communication; Vehicles; Wireless LAN; Disruption; forward algorithm; hidden Markov model (HMM); mathematical modeling; vehicular communications; wireless local area networks (WLANs);
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2010.2087780
Filename :
5610741
Link To Document :
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