A New Comprehensive RSU Installation Strategy for Cost-Efficient VANET Deployment

Recently, studies on vehicular ad hoc networks (VANETs) are booming due to their huge potential. The road side unit (RSU) is a key component of the VANET infrastructure connecting mobile vehicles to the rest of the infrastructure. To maximize the availability of RSUs, RSUs should be densely deployed...

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Vydané v:IEEE transactions on vehicular technology Ročník 66; číslo 5; s. 4200 - 4211
Hlavní autori: Donghyun Kim, Velasco, Yesenia, Wei Wang, Uma, R. N., Hussain, Rasheed, Sejin Lee
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.05.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9545, 1939-9359
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Shrnutí:Recently, studies on vehicular ad hoc networks (VANETs) are booming due to their huge potential. The road side unit (RSU) is a key component of the VANET infrastructure connecting mobile vehicles to the rest of the infrastructure. To maximize the availability of RSUs, RSUs should be densely deployed. Otherwise, blind spots may exist in which vehicles lose the connection to the infrastructure. Unfortunately, the massive deployment of RSUs to seamlessly cover the whole area of interest, which could be a vast metropolitan, can be very expensive. As the effectiveness and the benefits of the VANET have yet to be fully proven, such large scale deployment can hardly be a currently viable option. Motivated by this observation, this paper investigates a new strategy of how to best deploy RSUs so that their spatiotemporal coverage is maximized under a limited budget. In detail, for the first time in the literature, we consider an innovative RSU deployment framework, which is a well-balanced combination of three different approaches: deploying RSUs on static locations, public mobile transportation, and fully controllable vehicles owned by the local government. We first introduce a new strategy to abstract a map of city area into a grid graph. Then, we formulate the problem as a new optimization problem and show its NP-hardness. To solve this problem, we transform this problem into another optimization problem. Then, we propose a new polynomial running time approximation algorithm for the problem and show that the performance ratio (the ratio between the quality of an output of the proposed algorithm and the quality of the best possible solution) is at least half of the best possible ratio. We also conduct simulations under various settings to study the effectiveness of the proposed approach.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2016.2598253