Adaptive and Optimised Vehicular Ad Hoc Network with Cognitive Medium Access Control Layer

Vehicular Ad Hoc Network (VANET) technology is emerging as an ideal solution to enhance road driving experience through information sharing. The main purpose of VANET is to ensure road safety through efficient communication network between vehicles. However, VANET suffers from its inherent high mobility, ever changing nature of environment and communication interference which degrade the performance of the communication network and prevents successful data transmission. The current VANET employs mostly static parameters to improve data transmission. Despite the current efforts so far, VANET with static parameters are not adapted to the ever changing VANET environment, which makes VANET less adaptable and not optimized. Therefore the goal of this thesis is to propose solutions and techniques to optimize and adapt the VANET MAC to better suit VANET applications in the ever changing environment. All the proposed schemes presented in this thesis namely HaFL, MarPVS and MACVS, have been simulated in an urban area with the use of Omnet-4.2.2, Vehicles Network Simulation (Veins), Simulation of Urban Mobility (SUMO) and open google map application. Results show that the proposed schemes result in improvement in terms of latency, throughput and packet success rate, as compared to the default IEEE802.11p scheme and the current scheme in the literature. In summary, the thesis contribution includes derivation of new theorem, proofs and formula with the development of new techniques, algorithm and framework for VANET MAC. This research contributes to the improvement of VANET MAC performance through better adaptability and optimization