Application of Improved Ant Colony Optimization in Vehicular Ad-hoc Network Routing

This paper presents an improved ant colony optimization for vehicular ad-hoc network routing. The algorithm can quickly find the route with optimal network connectivity. Assuming that each vehicle has a digital map composed of intersections and streets, using the information contained in the data packet called ant, the vehicle can calculate the weight of each street, which is proportional to the network connection of the road section. The ant is launched by the vehicle in the intersection area. In order to find the best route between the source and destination, the source vehicle determines the best route on the street map with the minimum distance of the complete route. The performance is evaluated in the simulation environment. The simulation results show that compared with the VACO using ant algorithm, when the speed reaches 70 km/h, the transmission rate of data packets is increased by more than 10%. In addition, the routing control overhead and end-to-end delay of the proposed protocol are also reduced.