Proposta de benchmark para simulações de roteamento de dados em redes veiculares ad hoc

Abstract

In the last decades, we have witnessed an increasing sale of new cars, driven by extensive credit availability and the growth of average income. Hence, the number of vehicles on the roads has increased. Due to this high density of vehicles, the traffic jams as well as fatal accidents are increasing. In order to reduce such factors, the Intelligent Transportation Systems (ITS) aroused, offering connected services and products related to entertainment and road safety. In this system, vehicles, mobile equipments and the infrastructure in the neighborhood of the traffic ways can transfer data to each other, thus creating a network called VANET (Vehicular Ad-hoc Network). To optimize the packets routing in these dynamic networks, several Ant Colony Optmization (ACO) - based algorithms have been proposed. Such algorithms are inspired by the foraging behavior of ants, which are capable of finding the shortest paths from food sources to the nest. However, there are no performance evaluation standards in the recent literature. The algorithms are often compared to each other or with MANET’s algorithms. In this dissertation, a bench-mark of several routing instances for VANETs was created. These benchmarks can be used for testing routing algorithms. The mobility and network simulators were configured in order to create real-world VANET-like scenarios. The geographical area chosen for the scenarios was near to Curitiba downtown. Different vehicle densities were distributed in two way: purely random and biased in such a way that avenues receive higher vehicle flows. The three log-distance path loss model was applied to each scenario, sometimes combined with the Nakagami fading model. In each scenario the source and destination vehicles are fixed on opposite sides of the simulated area. For each simulation time step, the Dijkstra algorithm was run to find the shortest path data transmission between source and destination. A multiobjective ACO-based algorithm was proposed and compared with the Dijkstra algorithm. The paths found by ACO include higher number of hops than those found by the Dijkstra algorithm. A benchmark with several scenarios was created. The scenario’s simulations show the importance of several factors in the VANET connectivity, such as vehicle density, geographical location and propagation models. The results are promising and indicate the importance of choosing appropriated simulation models.