Planning roadside infrastructure for information dissemination in intelligent transportation systems

Trullols, O.; Fiore, Marco; Casetti, Claudio; Chiasserini, Carla-Fabiana; Barceló-Ordinas, José M.

doi:10.1016/j.comcom.2009.11.021

Cited by 203 publications

(173 citation statements)

References 13 publications

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“…Both analytical and simulation results reveal that relay and mesh nodes, as opposed to base stations, can be more cost-effective solutions even though a much larger number of such units are required to deliver the same level of performance as offered by the base stations. An interesting paper by Trullols et al [11] uses the approach employed by the maximum coverage problem for addressing this issue. The authors identify that roadside infrastructure should be placed at intersections rather than the middle of road segment.…”

Section: B Simulation Resultsmentioning

confidence: 99%

Cars as Roadside Units: A Cooperative Solution

Viriyasitavat

Tonguz

2012

2012 IEEE Vehicular Technology Conference (VTC Fall)

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Abstract-The gradual penetration of Dedicated Short Range Communications Radio (DSRC) technology in the years to come is a formidable problem that could adversely effect the implementation of safety and non-safety applications. In this paper, we propose a solution that might mitigate the negative impact of the partial and gradual penetration problem of DSRC technology. The proposed solution is based on a self-organizing network paradigm that draws its inspiration from biological systems, such as social insect colonies [1]. By designing the local rules and a distributed algorithm needed to perform this function, it is shown that DSRC-equipped cars can indeed serve as RSUs. Results show that the message reachability and connectivity in urban vehicular networks can be increased substantially in a cost-effective manner as the proposed approach does not entail deployment of infrastructure-based RSUs.

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Section: B Simulation Resultsmentioning

confidence: 99%

Cars as Roadside Units: A Cooperative Solution

Viriyasitavat

Tonguz

2012

2012 IEEE Vehicular Technology Conference (VTC Fall)

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“…However, in general, intersections and road segments can be considered as candidate locations for RSU deployment. Since more candidate locations increase the complexity of RSU placement algorithms, some previous work (e.g., (Trullols et al, 2010;Lee and Kim, 2010;Wang and Chang, 2011;Aslam et al, 2012;Lin, 2012;Chi et al, 2013b,a (Trullols et al, 2010;Campolo et al, 2011). However, data dissemination in long road segments may suffer from long delays, which may violate the requirements of the application.…”

Section: Phd Thesis -Naby Nikookaranmentioning

confidence: 99%

“…and commercial applications (e.g., location-based advertising, etc.) (Trullols et al, 2010;Abdrabou and Zhuang, 2011;Xiong et al, 2013;Campolo et al, 2011;Patil and (Liu et al, 2013).…”

Section: Information and Entertainment (Infotainment)mentioning

confidence: 99%

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Nikookaran

Karakostas

Todd

2017

IEEE Trans. Veh. Technol.

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Vehicular ad-hoc networks will be the next step towards intelligent transportation systems. Roadside infrastructure is a key component of these systems that will eventually support various applications such as road safety, transportation services, infotainment, and in-vehicle Internet access.This thesis considers the problem of roadside unit (RSU) placement and configuration in vehicular networks. The goal is to select the RSU locations and configurations such that the sum of capital and operational expenditure costs is minimized. Historical vehicular traffic traces and a set of RSU candidate locations are used as inputs.First, the problem is formulated as an integer linear program (ILP), which provides a lower bound on the total cost, and can be found for moderate size problems. A practical algorithm called Minimum Cost Route Clustering (MCRC) is then introduced that solves a relaxed version of the ILP and uses a novel rounding procedure to obtain real RSU placements. The algorithm takes into account the energy costs incurred by transmitting vehicular requests when the latter are scheduled using a minimum energy online scheduler. Performance results are presented that show that the proposed algorithm performs well compared to the case where placements are done without considering both capital and operational expenditure costs.iii The problem of capacity augmentation is then addressed, as a way of adjusting the initial RSU network design, and serves to counterbalance its failure to take causality into account. The objective is to find an RSU radio capacity assignment that minimizes the long-term operating expenditure costs subject to meeting packet deadline constraints, subject to a given packet loss rate target. A procedure, referred to as the Capacity Augmentation (CA) Algorithm, is proposed that iterates over the RSUs, selecting candidates for capacity augmentation based on their packet loss rate sensitivities. A variety of results is presented that characterize and compare the performance of the CA Algorithm using a greedy online packet scheduler. It is shown that the CA Algorithm is an efficient way to assign RSU radio capacity that achieves the desired performance objectives.

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“…Similarly, in [7], the authors introduce the concept of wireless dead drops to accumulate and exchange data with passing vehicles. The work presented in [20] also deals with information dissemination in VANETs. The authors consider an urban scenario where infrastructure units are employed to disseminate information to vehicles, and formulate an optimization problem to find the optimal deployment of the infrastructure units in order to maximize the number of informed vehicles.…”

Section: Introductionmentioning

confidence: 99%

Infrastructure-assisted geo-routing for cooperative vehicular networks

Borsetti¹,

Gozálvez²

2010

2010 IEEE Vehicular Networking Conference

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Abstract-Cooperative vehicular systems require the design of reliable and efficient multi-hop networking protocols to achieve their foreseen benefits. Although many geo-routing protocols have been proposed in the literature, few contributions have analysed the benefits that road side infrastructure units could provide to successfully route data from source to destination. In this context, this paper proposes a novel infrastructure-assisted routing approach designed to improve the end-to-end performance, range and operation of multi-hop vehicular communications by exploiting the reliable interconnection of infrastructure units. The conducted investigation shows that the proposed infrastructureassisted routing approach achieves its objectives, and reduces the routing overhead compared to other greedy position-based geo-routing protocols. Finally, the paper shows that to obtain the maximum benefits from the proposed infrastructure-assisted routing approach, optimal infrastructure deployment strategies must be further investigated.

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Planning roadside infrastructure for information dissemination in intelligent transportation systems

Cited by 203 publications

References 13 publications

Cars as Roadside Units: A Cooperative Solution

Cars as Roadside Units: A Cooperative Solution

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Infrastructure-assisted geo-routing for cooperative vehicular networks

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