Certain investigations on data caching in internet of vehicles using mcm and pacm models for vehicular named data networks

Abstract

The Vehicular Adhoc Networks (VANET) is an adhoc network of vehicles, formed for specific need or situation. It resembles the traditional MANET. However, VANET offers Vehicle-to-Vehicle (V2V) and Vehicleto-Roadside (V2R) wireless communication. The growth of VANET is tremendous in recent years, as specially after the invention autonomous cars. The automobile industry strives to enhance the driving experience and commuting experience by bringing all sophisticated features and emergency services in vehicles. This increases the expectation on vehicular communication, for example the Ecall facility is made mandatory in European standards. This is part for emergency service offered in the car. Likewise, there many new applications in line with infotainment and emergency services. The Named Data Networks (NDN) is a revolution in internet architecture, which seeks to improve overall performance of the interconnection. Hence the fusion of VANET and NDN as VNDN is essential for the current scenario. Today, modern automotive nodes are furnished with sophisticated sensors and on-board units to process the real time data communication. The rapid node mobility results in recurrent link failure, large variation in vehicle density, frequent fragmentation causes robust packet delivery, bandwidth management, link management, and content dissemination as a difficult task. Hence, the objective of the thesis is to enhance the performance of VANET by formulating an effective clustering technique, message dissemination techniques and traffic flow management schemesThe Position-based Adaptive Clustering Model (PACM) is presented in the first part of this thesis. The position and trajectory based adaptive clustering, coordinated content caching and popularity-based cache replacement strategies are proposed in this part. The position-based clustering model clusters the vehicle on road based on the velocity and trajectory of them. The vehicle node which is tend to move in same direction and speed are grouped together to avoid recurrent l