DTMR: An adaptive Distributed Tree-based Multicast Routing protocol for vehicular networks

Abstract

The modern driver-assistance and autonomous technologies in vehicles increase the ease of driving vehicles. The increased vehicle usage increases the requirement of efficient group communication between the vehicles to support the safety as well as the non-safety applications in Vehicular Ad-hoc NETworks (VANET). In VANET, multicast communication is mostly preferred for the effective utilization of computational resources and the attainment of the Quality of Service (QoS). To implement an efficient multicast communication, we need to build and retain a multicast tree. Due to the high mobility and rapid topology changes, the formation and maintenance of a multicast tree are challenging in VANET. Existing multicast communication techniques are either centralized or location-based flooding and suffer from tree reconfiguration overhead. In this paper, a novel Distributed Tree-based Multicast Routing (DTMR) algorithm is proposed. During the link failure, the connection is switched to a predetermined and highly stable guardian node. Further, the tree fragmentation and the rejoining delay is reduced in VANET using the proposed algorithm, DTMR. From the simulation results, it is evident that the DTMR achieves a significant performance improvement against the existing multicast techniques such as Distributed Time-limited Reliable Broadcast Incremental Power Strategy (DTRBIP) and Energy Efficient Multicast routing protocol based on Software Defined Networks and Fog computing for Vehicular networks (EEMSFV) in terms of delay, packet loss ratio, scalability, and reliability. In terms of end-to-end delay, packet loss rate, and reliability, the DTMR outperforms the existing DTRBIP and EEMSFV protocols. DTMR achieves 94--96% reliability in highway scenarios and 96--99% reliability in urban environments. Further, as a proof of concept, the proposed, DTMR is implemented and analyzed in real-time. It is found that the real-time experimental results are on par with the simulation results. Hence, the proposed DTMR achieves network stability and reliability in real-time.