A bio-inspired adaptive junction-based routing protocol for VANETs

The Junction-based routing (JBR) manages the data packet forwarding between vehicles in urban Vehicular Ad-hoc Networks (VANETs) where radio obstacles force routing decisions on junctions. JBR has been developed through different types such as the dynamic selection of junctions. The latter has been introduced to solve the shortages of static junction selection in transferring data within city scenarios. Meanwhile, the lack of up-to-date traffic density information induces the selection of unstable route segments for data packet relay so that many data packets are dropped. That is due to Time-To-Live (TTL) expiration or local sparse streets maxima. Our study addresses the optimal adapted number of selected junctions on each forwarding junction in order to reduce the data loss rates of the existing dynamic junction selection approaches. For this purpose, a bio-inspired evaluation mechanism of route segments’ continuous connectivity using the Firefly Algorithm (FA) is implemented in this paper. FA tracks the routing quality of route segments on the basis of their connectivity history and predefined real-time traffic parameters. This approach provides progressive route connectivity information that allows the application of an adaptive dynamic junction selection. The latter combines the single and multiple junction selection in order to cope with unanticipated traffic density changes of route segments, especially for the remote and unfrequented streets. The comparison of the proposed bio-inspired JBR protocol to a few classic JBR schemes has proven considerable PDR improvement from 6% to 19% in large cities and 6% to 11% in small cities.