Soft Computing

, Volume 21, Issue 8, pp 1949–1961 | Cite as

Parallel multi-objective metaheuristics for smart communications in vehicular networks

Methodologies and Application

Abstract

This article analyzes the use of two parallel multi-objective soft computing algorithms to automatically search for high-quality settings of the Ad hoc On Demand Vector routing protocol for vehicular networks. These methods are based on an evolutionary algorithm and on a swarm intelligence approach. The experimental analysis demonstrates that the configurations computed by our optimization algorithms outperform other state-of-the-art optimized ones. In turn, the computational efficiency achieved by all the parallel versions is greater than 87 %. Therefore, the line of work presented in this article represents an efficient framework to improve vehicular communications.

Keywords

Parallelism Multi-objective optimization Vehicular networks Routing 

Notes

Acknowledgments

J. Toutouh is supported by Grant AP2010-3108 of the Spanish Ministry of Education. This research has been partially funded by project UMA/FEDER FC14-TIC36, and the Spanish MINECO project TIN2014-57341-R (http://moveon.lcc.uma.es). University of Malaga, International Campus of Excellence Andalucía Tech.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Dept. of Lenguajes y Ciencias de la ComputaciónUniversity of MalagaMálagaSpain

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