Heterogeneous Roadside Unit Placement in Eco-Sustainable Communication Networks for Intelligent Transportation

Yingge, Song; Lin, Bin; Tian, Ye; Ding, Ning; He, Rongxi; Zhao, Tiange

doi:10.1109/fcst.2015.64

Cited by 6 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other works also consider additional issues such as reducing the energy consumption of RSUs [3,15,16], improving vehicles' content downloading capabilities [9], selecting the most suitable configurations for RSUs deployed [17] or estimating the maximum deployment distance between two neighboring RSUs [18]. Moreover, those works rely on different techniques such as clustering [3], cumulative weight [8], time continuous homogeneous Markov chains [9], game theoretic tools [19] and Integer Linear Programming (ILP) [15].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms

et al. 2018

View full text Add to dashboard Cite

Vehicular networks make use of the Roadside Units (RSUs) to enhance the communication capabilities of the vehicles in order to forward control messages and/or to provide Internet access to vehicles, drivers and passengers. Unfortunately, within vehicular networks, the wireless signal propagation is mostly affected by buildings and other obstacles (e.g., urban fixtures), in particular when considering the IEEE 802.11p standard. Therefore, a crowded RSU deployment may be required to ensure vehicular communications within urban environments. Furthermore, some applications, notably those applications related to safety, require a fast and reliable warning data transmission to the emergency services and traffic authorities. However, communication is not always possible in vehicular environments due to the lack of connectivity even employing multiple hops. To overcome the signal propagation problem and delayed warning notification time issues, an effective, smart, cost-effective and all-purpose RSU deployment policy should be put into place. In this paper, we propose the genetic algorithm for roadside unit deployment (GARSUD) system, which uses a genetic algorithm that is capable of automatically providing an RSU deployment suitable for any given road map layout. Our simulation results show that GARSUD is able to reduce the warning notification time (the time required to inform emergency authorities in traffic danger situations) and to improve vehicular communication capabilities within different density scenarios and complexity layouts.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Moreover, those works rely on different techniques such as clustering [3], cumulative weight [8], time continuous homogeneous Markov chains [9], game theoretic tools [19] and Integer Linear Programming (ILP) [15].…”

Section: Related Workmentioning

confidence: 99%

Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms

et al. 2018

View full text Add to dashboard Cite

show abstract

“…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%

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Nikookaran

Karakostas

Todd

2017

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

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.

show abstract

Infrastructure deployment and optimization of fog network based on MicroDC and LRPON integration

Zhang

Lin

Yin

et al. 2016

Peer-to-Peer Netw. Appl.

View full text Add to dashboard Cite

Heterogeneous Roadside Unit Placement in Eco-Sustainable Communication Networks for Intelligent Transportation

Cited by 6 publications

References 12 publications

Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms

Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms

Combining Capital and Operating Expenditure Costs in Vehicular Roadside Unit Placement

Infrastructure deployment and optimization of fog network based on MicroDC and LRPON integration

Contact Info

Product

Resources

About