Social Attributes-Based Content Delivery for Sparse Vehicular Content-Centric Network
Xiaonan Wang, Xilan Chen
Abstract
In the sparse vehicular content-centric network, discontinuous connections lead to stale forwarding information and broken reverse paths, ultimately resulting in content delivery failures. Social interactions among vehicles are considered to contribute to enhancing the efficiency of vehicular content delivery because social relationships among vehicles are generally long-term and vehicles sharing more social attributes have a higher chance of meeting each other. Therefore, we are motivated to exploit the social attributes of vehicles to address the issue of content delivery failures in the sparse vehicular content-centric network. Based on the idea, we propose a social attributes based content delivery framework for the sparse vehicular content-centric network, and aim to improve content delivery success rates and alleviate costs. The framework leverages the social metrics of vehicles to deliver contents and to perform in-network caching. The experimental results demonstrate the superiority of the proposed framework in terms of content delivery success rates and costs.