Utilizing road-side infrastructure for location-based services in vehicular ad-hoc networks

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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“…As in (Maia et al, 2013;Dai et al, 2013), we assume that TTL is 40 time slots for each request. The maximum request drop rate is set to 5%.…”

Section: Performance Resultsmentioning

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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“…Some mobile LBS frameworks and architectures have been proposed. Chengcheng Dai proposes a LBS framework using vehicular ad-hoc networks [4]. R. Gobi proposes a communication framework for data management in LBS [5].…”

Section: ) Analyzing Test Results and Coveragesmentioning

confidence: 99%

Test Model and Coverage Analysis for Location-based Mobile Services

Zhang¹,

Gao²,

Aktouf³

et al. 2015

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Location-based services (LBS) are very important mobile app services, which provide diverse mobility services for mobile users anywhere and anytime. This brings new demands, issues, and challenges in mobile application testing. Today, mobile applications provide location-based service functions based on dynamic location contexts, mobile users and their travel patterns to deliver location-based mobile data, and service actions. Current software testing methods do not consider location-based validation coverage. Hence, there is a lack of research results addressing location-based mobile application testing. This paper focuses on mobile LBS testing. A novel test object model is proposed for quality validation of location-based mobile information services. In addition, the related test coverage metrics are also presented. These metrics can be useful for test engineers in designing test cases. A case study based on student testers is reported to demonstrate the potential application of the proposed model.

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“…In recent years, considerable attention has been focused on RSU placement [12, 15–20]. The authors have examined the RSU placement issue for the highway and urban environments.…”

Section: Review Of the Related Workmentioning

confidence: 99%

Optimal road side units placement model based on binary integer programming for efficient traffic information advertisement and discovery in vehicular environment

Balouchzahi

Fathy

Akbari

2015

IET Intelligent Transport Systems

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Utilizing road-side infrastructure for location-based services in vehicular ad-hoc networks

Cited by 5 publications

References 32 publications

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Test Model and Coverage Analysis for Location-based Mobile Services

Optimal road side units placement model based on binary integer programming for efficient traffic information advertisement and discovery in vehicular environment

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