A Location Privacy Framework using Edge Computing in VANET

摘要

The edge computing model are anticipated to resolve the significant flaws affecting recent trends that demands the cloud computing resources for functioning. Such novel prototypes will be useful for the users as they bridge the computational resources closer. This will enhance the bandwidth utilization and decreases the latency of network, but it will append few impressive context-awareness properties to the respective systems. In this paper, we study how the application of attractive features of edge computing can be utilized to enhance the privacy (location privacy) of the vehicular networks (VN), particularly authentication, revocation and anonymity issues. In general, we observe the existing privacy challenges in the vehicular networks and study the existing deployment models by arranging them into three categories. The outcome states that the computational overhead can be significantly reduced without compromising the privacy of vehicular nodes, if vehicular edge communication established ideally.