Traffic Offloading for Online Video Service in Vehicular Networks: A Cooperative Approach

Online video service becomes prevalent nowadays, as people are accustomed to getting information in the form of videos. While home users can easily retrieve all kinds of contents onto their laptops or smartphones, vehicular users are constrained by intermittent connectivity to roadside units (RSUs). Besides, as the load of cellular infrastructure increases dramatically, it is envisioned that the cellular network can be offloaded by utilizing RSUs and vehicular relays. In this paper, we propose a cooperative downloading mechanism in heterogeneous vehicular networks that comprises vehicular ad hoc network and cellular network. In this mechanism, RSUs act as traffic managers to fetch proper data from the Internet and then distribute to vehicles in an approximately optimal manner. Specifically, based on vehicular mobility prediction and internode throughput estimation, a storage time aggregated graph is constructed for planning transmission scheme; then, an iterative greedy-driven algorithm is designed for a suboptimal solution, which has polynomial computational time complexity. Compared with max-throughput and min-delay cooperative downloading (MMCD), simulation results show that our approach outperforms MMCD by $5\%\text{$-$}25\%$ with respect to offload fraction.