An Optimized Roadside Units (RSU) placement for delay-sensitive applications in vehicular networks

Mehar, Sara; Senouci, Sidi‐Mohammed; Kies, Ali; Maaza, Zoulikha Mekkakia

doi:10.1109/ccnc.2015.7157957

Cited by 62 publications

(51 citation statements)

References 28 publications

(33 reference statements)

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“…Deployed RSUs have a significant impact on the reliability of VANETs and information exchange (Mehar et al, 2015). In fact, deploying more RSUs can guarantee a better connectivity, coverage and performance (Campolo et al, 2011;Patra et al, Ph.D. Thesis -Naby Nikookaran McMaster -Electrical & Computer Engineering 2014).…”

Section: Assumptions and Challengesmentioning

confidence: 99%

“…(Wu et al, 2012;Liya et al, 2013). Regarding the spatial fluctuations, RSUs are mostly proposed to be installed at locations with high vehicle density, so that more vehicles can benefit, although, if the main goal of deploying RSUs is to reduce the information dissemination delay, deploying them at less dense locations may be more beneficial (Mehar et al, 2015). To tackle the temporal fluctuations, RSUs can be deployed according to the projected traffic peak, the average traffic level, or separately, for each different time period Vageesh et al, 2014;Kim et al, 2016).…”

Section: Phd Thesis -Naby Nikookaranmentioning

confidence: 99%

“…This approach seems to be more appropriate since the network operator can estimate the deployment cost for a satisfactory level of service. In this category, also, the objective function is either the minimization of the number of deployed RSUs (e.g., see References (Abdrabou and Zhuang, 2011;Abdrabou et al, 2013;Liya et al, 2013;Liu et al, 2016;Patra et al, 2014;Wang et al, 2016) for highway scenario and References Chi et al, 2013b,a;Wang and Chang, 2011;Kumrai et al, 2014;Liu et al, 2013;Yan et al, 2014;Xiong et al, 2013;Hu et al, 2016) for urban scenario) or the minimization of the total CAPEX (e.g., see References (Lin, 2012;Liang et al, 2012;Li et al, 2015;Song et al, 2015;Mehar et al, 2015)). …”

Section: Related Workmentioning

confidence: 99%

“…Deploying RSUs is mainly considered as a way to improve the connectivity problem of V2V communications in VANET (Tonguz and Viriyasitavat, 2013;Mehar et al, 2015;Zou et al, 2011;Patil and Gokhale, 2013;Brahim et al, 2014;Tao et al, 2014), as well as a means to provide Internet access to a variety of ITS based applications and infotainment applications. The solutions that have been introduced in the literature to solve the RSU placement problem mostly focus on the former, i.e., connectivity improvement of V2V communication.…”

Section: Budget-constrained Rsu Deploymentmentioning

confidence: 99%

“…To overcome the shortcomings of VANETs, Reference (Mehar et al, 2015) proposes an RSU placement strategy to improve the network connectivity for delaysensitive applications. The goal is to select the best RSU locations so that the combination of the total RSU deployment cost and the total message delivery delay to the nearest RSU is minimized, and the message delivery delay from any road segment to the closest RSU is less than a given threshold.…”

Section: Rsu Placement and Rsu Configurationmentioning

confidence: 99%

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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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Section: Assumptions and Challengesmentioning

confidence: 99%

Section: Phd Thesis -Naby Nikookaranmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Budget-constrained Rsu Deploymentmentioning

confidence: 99%

Section: Rsu Placement and Rsu Configurationmentioning

confidence: 99%

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Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Nikookaran

Karakostas

Todd

2017

IEEE Trans. Veh. Technol.

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Toward a lightweight and efficient UAV‐aided VANET

Sedjelmaci

Messous

Senouci

et al. 2018

Trans Emerging Tel Tech

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Connectivity in a smart vehicular network is quite sensitive and highly affected by its dynamic network topology. Issues related to the intermittent nature of connectivity may arise due to the high mobility of nodes and network heterogeneity. In sparse areas, a vehicular network is basically a disruption-tolerant network suffering from frequent disconnections, long delays, and messages loss.Facing these issues, and specifically for time-sensitive applications, Unmanned Aerial Vehicle (UAV) can provide valuable assistance to Vehicular Ad Hoc Network (VANET) by assuming a relay node role between disconnected segments in the road. In such scenarios, effective communication is either between vehicles (V2V) or between vehicles and UAVs (V2U), which would form subsequently a UAV-assisted vehicular network. In the present paper, we propose a new framework for using small UAVs as mobile infrastructure nodes in order to enhance the connectivity between vehicles. The first part of this framework accurately predicts the disconnected segments such that drones can be deployed to reestablish lost links. We have implemented a theoretical game for this prediction process. Furthermore, since the battery reserves of the UAVs are limited, we have proposed a mitigation technique based on game theory to reduce the power draining effects that a broadcast storm would have on the energy consumption of the network. For the validation of the proposed UVE (UAV-aided VANET framework, with energy-conscious constraints), we conducted thorough simulation scenarios with Network Simulator 3. The obtained performances are promising in the sense that our approach achieves high packet delivery ratio, low end-to-end delay, and low overhead communication costs.Trans Emerging Tel Tech. 2019;30:e3520.wileyonlinelibrary.com/journal/ett

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Vehicular Grouping and Network Formation: Virtualization of Network Self-healing

Al-Hamid

Al-Anbuky

2018

Lecture Notes in Computer Science

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An Optimized Roadside Units (RSU) placement for delay-sensitive applications in vehicular networks

Cited by 62 publications

References 28 publications

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Toward a lightweight and efficient UAV‐aided VANET

Vehicular Grouping and Network Formation: Virtualization of Network Self-healing

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