A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service

Flávio Vinícius Cruzeiro Martins*, João F.M. Sarubbi, Elizabeth F. Wanner

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we propose the Delta-MGA, a specific multiobjective algorithm for solving the allocation of Roadside Units (RSUs) in a Vehicular Network (VANETs). We propose two multiobjective models to solve two different problems. The first one, our objectives are to find the minimum set of RSUs and to maximize the number of covered vehicles. The second one, our objectives are to find the minimum set of RSUs and to maximize the percentage of time that each vehicle remains connected. Our metric is based on Delta Network metric proposed in literature. As far as we concerned, Delta-MGA is the first multiobjective approach to present a deployment strategy for VANETs. We compare our approach with two mono-objective algorithms: (i) Delta-r; (ii) Delta-GA. Our results demonstrate that our approach gets better results when compared with Delta-r algorithm and competitive results when compared with Delta-GA algorithm. Furthermore, the main advantage of Delta-MGA algorithm is that with it is possible to find several different solutions given to the planning authorities diverse alternatives to deploy the RSUs.

Original languageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization
Subtitle of host publication9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings
EditorsHeike Trautmann, Rudolph Günter, et al
Place of PublicationCham (CH)
PublisherSpringer
Pages120-134
Number of pages15
ISBN (Electronic)978-3-319-54157-0
ISBN (Print)978-3-319-54156-3
DOIs
Publication statusPublished - 2017
Event9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 - Munster, Germany
Duration: 19 Mar 201722 Mar 2017

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10173
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017
CountryGermany
CityMunster
Period19/03/1722/03/17

Fingerprint

Vehicular Networks
Roadsides
Unit
Maximise
Metric
Percentage
Planning
Strategy
Alternatives
Demonstrate

Keywords

  • quality of service
  • roadside unit deployment
  • vehicular network

Cite this

Martins, F. V. C., Sarubbi, J. F. M., & Wanner, E. F. (2017). A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service. In H. Trautmann, R. Günter, & et al (Eds.), Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 120-134). (Lecture Notes in Computer Science; Vol. 10173). Cham (CH): Springer. https://doi.org/10.1007/978-3-319-54157-0_9
Martins, Flávio Vinícius Cruzeiro ; Sarubbi, João F.M. ; Wanner, Elizabeth F. / A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service. Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. editor / Heike Trautmann ; Rudolph Günter ; et al. Cham (CH) : Springer, 2017. pp. 120-134 (Lecture Notes in Computer Science).
@inproceedings{7dc16420cb1d40999d99c4a6e7bf7ca4,
title = "A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service",
abstract = "In this work, we propose the Delta-MGA, a specific multiobjective algorithm for solving the allocation of Roadside Units (RSUs) in a Vehicular Network (VANETs). We propose two multiobjective models to solve two different problems. The first one, our objectives are to find the minimum set of RSUs and to maximize the number of covered vehicles. The second one, our objectives are to find the minimum set of RSUs and to maximize the percentage of time that each vehicle remains connected. Our metric is based on Delta Network metric proposed in literature. As far as we concerned, Delta-MGA is the first multiobjective approach to present a deployment strategy for VANETs. We compare our approach with two mono-objective algorithms: (i) Delta-r; (ii) Delta-GA. Our results demonstrate that our approach gets better results when compared with Delta-r algorithm and competitive results when compared with Delta-GA algorithm. Furthermore, the main advantage of Delta-MGA algorithm is that with it is possible to find several different solutions given to the planning authorities diverse alternatives to deploy the RSUs.",
keywords = "quality of service, roadside unit deployment, vehicular network",
author = "Martins, {Fl{\'a}vio Vin{\'i}cius Cruzeiro} and Sarubbi, {Jo{\~a}o F.M.} and Wanner, {Elizabeth F.}",
year = "2017",
doi = "10.1007/978-3-319-54157-0_9",
language = "English",
isbn = "978-3-319-54156-3",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "120--134",
editor = "Heike Trautmann and Rudolph G{\"u}nter and {et al}",
booktitle = "Evolutionary Multi-Criterion Optimization",
address = "Germany",

}

Martins, FVC, Sarubbi, JFM & Wanner, EF 2017, A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service. in H Trautmann, R Günter & et al (eds), Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. Lecture Notes in Computer Science, vol. 10173, Springer, Cham (CH), pp. 120-134, 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017, Munster, Germany, 19/03/17. https://doi.org/10.1007/978-3-319-54157-0_9

A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service. / Martins, Flávio Vinícius Cruzeiro; Sarubbi, João F.M.; Wanner, Elizabeth F.

Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. ed. / Heike Trautmann; Rudolph Günter; et al. Cham (CH) : Springer, 2017. p. 120-134 (Lecture Notes in Computer Science; Vol. 10173).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service

AU - Martins, Flávio Vinícius Cruzeiro

AU - Sarubbi, João F.M.

AU - Wanner, Elizabeth F.

PY - 2017

Y1 - 2017

N2 - In this work, we propose the Delta-MGA, a specific multiobjective algorithm for solving the allocation of Roadside Units (RSUs) in a Vehicular Network (VANETs). We propose two multiobjective models to solve two different problems. The first one, our objectives are to find the minimum set of RSUs and to maximize the number of covered vehicles. The second one, our objectives are to find the minimum set of RSUs and to maximize the percentage of time that each vehicle remains connected. Our metric is based on Delta Network metric proposed in literature. As far as we concerned, Delta-MGA is the first multiobjective approach to present a deployment strategy for VANETs. We compare our approach with two mono-objective algorithms: (i) Delta-r; (ii) Delta-GA. Our results demonstrate that our approach gets better results when compared with Delta-r algorithm and competitive results when compared with Delta-GA algorithm. Furthermore, the main advantage of Delta-MGA algorithm is that with it is possible to find several different solutions given to the planning authorities diverse alternatives to deploy the RSUs.

AB - In this work, we propose the Delta-MGA, a specific multiobjective algorithm for solving the allocation of Roadside Units (RSUs) in a Vehicular Network (VANETs). We propose two multiobjective models to solve two different problems. The first one, our objectives are to find the minimum set of RSUs and to maximize the number of covered vehicles. The second one, our objectives are to find the minimum set of RSUs and to maximize the percentage of time that each vehicle remains connected. Our metric is based on Delta Network metric proposed in literature. As far as we concerned, Delta-MGA is the first multiobjective approach to present a deployment strategy for VANETs. We compare our approach with two mono-objective algorithms: (i) Delta-r; (ii) Delta-GA. Our results demonstrate that our approach gets better results when compared with Delta-r algorithm and competitive results when compared with Delta-GA algorithm. Furthermore, the main advantage of Delta-MGA algorithm is that with it is possible to find several different solutions given to the planning authorities diverse alternatives to deploy the RSUs.

KW - quality of service

KW - roadside unit deployment

KW - vehicular network

UR - http://link.springer.com/chapter/10.1007%2F978-3-319-54157-0_9

UR - http://www.scopus.com/inward/record.url?scp=85014241817&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-54157-0_9

DO - 10.1007/978-3-319-54157-0_9

M3 - Conference contribution

AN - SCOPUS:85014241817

SN - 978-3-319-54156-3

T3 - Lecture Notes in Computer Science

SP - 120

EP - 134

BT - Evolutionary Multi-Criterion Optimization

A2 - Trautmann, Heike

A2 - Günter, Rudolph

A2 - et al,

PB - Springer

CY - Cham (CH)

ER -

Martins FVC, Sarubbi JFM, Wanner EF. A multiobjective strategy to allocate roadside units in a vehicular network with guaranteed levels of service. In Trautmann H, Günter R, et al, editors, Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. Cham (CH): Springer. 2017. p. 120-134. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-54157-0_9