基于NDN架构的车联网内容检索协议

In the existing content retrieval protocols of vehicular named data networking (VNDN), the content retrieval for location-independent applications is usually to obtain the location of the content provider based on flooding. This method not only costs much, but also is unable to adapt to the highly dynamic changes of the location of content providers. In this paper, a content retrieval protocol, CPCoR, was proposed based on clustering and prediction mechanism for VNDN. The CPCoR was arranged to establish a dynamic network content index table through the collaborative interaction between vehicles and roadside units. In the intra-street forwarding mechanism, the index was designed to forward according to the cluster head with stable link connection. In the inter-street forwarding mechanism, the index was designed to select the best forwarding street according to the routing performance of streets. Experimental results show that, compared with existing protocols, Navigo and CCVN, CPCoR protocol can not only improve the success rate of content acquisition by 21.5% and 51.3%, but also can effectively reduce the cost of content acquisition by 22.6% and 28.4%.