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 QoS of the network beforehand. The problem we 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. We 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 our 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.

翻译：车载自组织网络（VANETs）这一新兴领域涉及一组能够自发互联而无需任何预先存在基础设施的通信车辆。在此类网络中，在最终网络部署前对通信协议进行最优配置至关重要。通过这种方式，设计人员可以预先获得网络的最佳服务质量。本工作考虑的问题在于配置文件传输协议配置（FTC），以优化实际VANET场景中的传输时间、丢包数量以及数据传输量。我们采用五种具有代表性的前沿优化技术处理FTC问题，并比较其性能。这些算法包括：粒子群优化（PSO）、差分进化（DE）、遗传算法（GA）、进化策略（ES）和模拟退火（SA）。为进行测试，我们定义了城市和高速公路两种典型VANET环境实例。使用ns-2（一种知名的真实VANET模拟器）进行的实验表明，在两种研究的VANET实例中，PSO均优于所有对比算法。