Named Data Networking-Based Macrovehicular Cloud Framework

Named data networking (NDN) is a new data-centric paradigm where a consumer may communicate with multiple providers; therefore, it might be an ideal solution for constructing a macrovehicular cloud (aVC). Based on this observation, we are motivated to exploit the advantages of NDN to achieve aVC. However, NDN has a different architecture from vehicular networking, which might lead to considerable aVC-based data retrieval costs and frequent reverse-path disruptions. To overcome the problems, we propose an NDN-based aVC framework (NVCF) to achieve aVC, and aim to reduce aVC-based data retrieval costs and improve aVC-based data acquisition success rates. NVCF exploits NDN to achieve aVC so that vehicles can acquire aVC-based data via one data retrieval process. Moreover, NVCF stabilizes reverse paths by electing a small number of forwarders so that vehicles can employ unicast and stable reverse paths to retrieve data from the nearest provider or forwarder involved in reverse paths. Furthermore, NVCF can effectively fix broken reverse paths to guarantee successful receipt of aVC-based data. NVCF is analyzed and evaluated, and the experimental results demonstrate that NVCF effectively reduces data retrieval costs and improves success rates.