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The Computer Journal
Article . 2019 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Traffic-Centric Mesoscopic Analysis of Connectivity in VANETs

Authors: Mani Zarei;

Traffic-Centric Mesoscopic Analysis of Connectivity in VANETs

Abstract

Abstract Vehicular ad hoc networks (VANETs) have emerged as an appropriate class of information propagation technology promising to link us even while moving at high speeds. In VANETs, a piece of information propagates through consecutive connections. In the most previous vehicular connectivity analysis, the provided probability density function of intervehicle distance throughout the wide variety of steady-state traffic flow conditions is surprisingly invariant. But, using a constant assumption, generates approximate communication results, prevents us from improving the performance of the current solutions and impedes designing the new applications on VANETs. Hence, in this paper, a mesoscopic vehicular mobility model in a multilane highway with a steady-state traffic flow condition is adopted. To model a traffic-centric distribution for the spatial per-hop progress and the expected spatial per-hop progress, different intervehicle distance distributions are utilized. Moreover, the expected number of hops, distribution of the number of successful multihop forwarding, the expected time delay and the expected connectivity distance are mathematically investigated. Finally, to model the distribution of the connectivity distances, a set of simplistic closed-form traffic-centric equations is proposed. The accuracy of the proposed model is confirmed using an event-based network simulator as well as a road traffic simulator.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
hybrid