MPBRP- Mobility Prediction Based Routing Protocol in VANETs

Abstract

Vehicular Ad-hoc Networks (VANETs) technology has been emerged as an important research topic in recent years. This is because the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications are becoming more popular in the field of Intelligent Transportation System (ITS) so as to further enhance traffic efficiency, safety, emissions reduction and infotainment applications. Over the last few years, a number of routing protocols in VANETs have been developed. In particular, position-based routing protocols have attracted the most interest in VANETs as they are suitable for a frequently changeable network topology and highly dynamic nature of vehicular nodes. This paper develops a new Mobility Prediction Based Routing Protocol (MPBRP) for neighborhood detection, packet transmission and path recovery in VANETs by using driver's intention collected from the positioning systems. Several major contributions are made in the paper: (1) Combining both predictive forwarding strategy and recovery strategy to detect neighbors and transfer packets. (2) Utilizing the predicted position and angles in a pre-defined time with considering driver's intention to select the neighboring nodes and discover the transmission path. (3) Validating the effectiveness and feasibility of the proposed protocol by creating a unified simulation platform (Veins) and implementing it in real world scenarios. (4) Enhancing the overall performance as the proposed routing protocol achieved competitive improvement over existing protocols in terms of packet delivery ratio, end-to-end delay and average hops about 26.22%, 21.89% and 20.79% by average in grid-based scenario, and about 26.04%,23.14% and 18.51% by average in urban scenario respectively.