Adaptive Vehicular Routing Protocol Based on Ant Colony Optimization
Abstract
Vehicular Ad hoc Networks (VANETs) pose many challenges to copy with, such as large network size, rapid topology changes, and channel capacity limitations which can play a significant role in communication performance degradation and even links failure. To address these problems, we propose VACO (Vehicular routing protocol based on Ant Colony Optimization), a new adaptive multi-criteria VANET routing protocol. Based on Ant Colony Optimization (ACO) concept, VACO combines both reactive and proactive components to respectively establish and maintain best routing paths. Reactive forward and backward ants are sent between source and destination to explore and set up best routes consisting of a list of intersections. The key feature of the route selection is to rely on a periodically estimated road segment relaying quality which is expressed in terms of three combined QoS parameters (latency, bandwidth, and delivery ratio). Routing decision is then realized at each intersection to opportunistically select best next intersection based on a pheromone routing table. Packet relaying between adjacent intersections make use of simply carry and/or greedy forwarding technique. VACO also implements a proactive route maintenance using proactive ants to update, expend and improve the routing information. The derived simulation results show that VACO protocol outperforms reference protocols (GPSR and CAR) in terms of delivery ratio, throughput, overhead, and average end-to-end delay.