Enhanced Context-Aware Network Coded Repetition with Privacy-Preserving Scheme and Traffic Congestion Avoidance in Vehicular Ad-Hoc Network

Abstract

In vehicular ad hoc networks, safety applications allow people to avoid dangerous situations based on the condition of the vehicles in their proximity. Such proximity awareness is realized by admitting each vehicle to collect safety messages called beacons, which are periodically and locally transmitted from its neighbouring vehicles. The reliability of beacon transmissions is a crucial factor that makes safety applications effective in practice. Due to the open medium of communication in vehicular ad hoc network it is vulnerable to many attacks. Therefore, we provide an efficient anonymous authentication scheme with low computational cost. In addition, we introduce congestion detection algorithms to detect areas of high traffic density with low speeds. Altogether we propose a new scheme called Enhanced Context-Aware Network Coded Repetition with Privacy-Preserving Scheme and Traffic Congestion Avoidance in Vehicular Ad-hoc Network to avoid malicious vehicles entering into the VANET and to avoid traffic congestion by suggesting optimal path to vehicles.