A Content Sharing and Discovery Framework Based on Semantic and Geographic Partitioning for Vehicular Networks

摘要

Recently P2P networks and theirs applications have become increasingly popular. On the other hand, considering ever increasing industrial and scholarly popularity of Vehicular Ad hoc Networks (VANETs), implementation P2P network over VANET has attracted attentions recently. One of the most important applications in P2P networks is content discovery. Regarding the difficulties of structured and unstructured protocols over VANET, this paper presents a new framework for sharing and content discovery which formed a structured overlay to overcome problems likes broadcasting storm which is the main problem of unstructured methods. On the other hand, this paper tries to solve the instability of structured overlay networks as the main problem of them, by applying geographical and semantic partitioning. Simulation results clarified higher performance of proposed framework in comparison to previous protocols. Furthermore, applying G-Network queue network, we have modeled the behavior of proposed framework and then, optimize it by gradient descent optimization method.