Cooperative Volunteer Protocol to Detect Non-Line of Sight Nodes in Vehicular Ad hoc Networks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. CTIA vehicular Ad hoc Network (VANET) is a special type of Mobile Ad hoc Network (MANET) application that impacts wireless communications and Intelligent Transport Systems (ITSs). VANETs are employed to develop safety applications for vehicles to create a safer and less cluttered environment on the road. The many remaining challenges relating to VANETs have encouraged researchers to conduct further investigation in this field to meet these challenges. For example, issues pertaining to routing protocols, such as the delivery of warning messages to vehicles facing Non-Line of Sight (NLOS) situations without causing a broadcasting storm and channel contention are regarded as a serious dilemma, especially in congested environments. This prompted the design of an efficient mechanism for a routing protocol capable of broadcasting warning messages from emergency vehicles to vehicles under NLOS conditions to reduce the overhead and increase the packet delivery ratio with reduced time delay and channel utilisation. This work used the cooperative approach to develop the routing protocol named the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle experiencing an NLOS situation. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other to collect data and make decisions based on the sensed circumstances. The simulation results showed that the proposed protocol outperformed the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead, and latency. The results also showed that the proposed CVP could successfully detect NLOS situations and solve them effectively and efficiently for both the intersection scenario in urban areas and the highway scenario