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

Keywords

  • quality of service
  • roadside unit deployment
  • vehicular network

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  • Research Output

    • 1 Conference contribution

    Dimensionality reduction approach for many-objective vehicle routing problem with demand responsive transport

    Mendes, R., Wanner, E., Martins, F. & Sarubbi, J., 2017, Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. Trautmann, H., Günter, R. & et al (eds.). Cham (CH): Springer, p. 438-452 15 p. (Lecture Notes in Computer Science; vol. 10173).

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

  • 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). Springer. https://doi.org/10.1007/978-3-319-54157-0_9