An Efficient Cache Strategy in Information Centric Networking Vehicle-to-Vehicle Scenario

Information centric networking (ICN) has been recently proposed as a prominent solution for content delivery in vehicular ad hoc networks. By caching the data packets in vehicular unused storage space, vehicles can obtain the replicate of contents from other vehicles instead of original content provider, which reduces the access pressure of content provider and increases the response speed of content request. In this paper, we propose a community similarity and population-based cache policy in an ICN vehicle-to-vehicle scenario. First, a dynamic probability caching scheme is designed by evaluating the community similarity and privacy rating of vehicles. Then, a caching vehicle selection method with hop numbers based on content popularity is proposed to reduce the cache redundancy. Moreover, to lower the cache replacement overhead, we put forward a popularity prediction-based cooperative cache replacement mechanism, which predicts and ranks popular content during a period of time. Simulation results show that the performance of our proposed mechanisms is greatly outstanding in reducing the average time delay and increasing the cache hit ratio and the cache hit distance.