The emerging field of vehicular ad hoc networks (VANETs) deals with a set of communicating vehicles which are able to spontaneously interconnect without any pre-existing infrastructure. In such kind of networks, it is crucial to make an optimal configuration of the communication protocols previously to the final network deployment. This way, a human designer can obtain an optimal Quality-of-Service (QoS) of the network beforehand. The problem the authors consider in this work lies in configuring the File Transfer protocol Configuration (FTC) with the aim of optimizing the transmission time, the number of lost packets, and the amount of data transferred in realistic VANET scenarios. The authors face the FTC with five representative state-of-the-art optimization techniques and compare their performance. These algorithms are: Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Evolutionary Strategy (ES), and Simulated Annealing (SA). For their tests, two typical environment instances of VANETs for Urban and Highway scenarios have been defined. The experiments using ns-2 (a well-known realistic VANET simulator) reveal that PSO outperforms all the compared algorithms for both studied VANET instances. This paper is organized as follows. In the next section the authors briefly describe the most relevant related works found in the current literature. In Section 3 they introduce the Optimal File Transfer Configuration problem. Section 4 provides preliminary descriptions of the compared algorithms. In Section 5, the optimization strategy and fitness function are described. Experimental results and comparisons are presented in Section 6, including performance, scalability, and technical analyses of the resulted VANET configurations. Conclusions and future work are drawn in Section 7.


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    Title :

    Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics


    Contributors:
    Garcia-Nieto, J. (author) / Toutouh, J. (author) / Alba, E. (author)


    Publication date :

    2010


    Size :

    11 Seiten, 8 Bilder, 9 Tabellen, 25 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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