Adaptive Segmented Subscription for Efficient Data Dissemination in Vehicular Named Data Networks

Vehicular Named Data Networking (VNDN) is a promising information-centric network architecture to achieve efficient data delivery among vehicles. With a subscription-based communication paradigm, it can disseminate event-triggered data like traffic updates or road accident notifications in a timely way. However, due to vehicle mobility and network dynamics, the data subscription path is normally fragile and consequently the data dissemination efficiency would be diminished. To address this problem, we propose SegSub, an adaptive segmented subscription mechanism which can maintain robust subscription path for efficient data dissemination in mobile scenarios. SegSub divides the whole subscription path into several segments and different strategies are employed to maintain subscription status for each segment path. The frequency of subscription update on each segment is calculated based on the prediction of vehicle mobility and network status to reach a trade-off between subscription updating overhead and expected data dissemination delay. Furthermore, a subscription migration mechanism is proposed to alleviate the data loss and redundant pending overhead caused by subscription failure when vehicles move. Evaluation results demonstrate that SegSub can decrease dissemination delay by 91.9% and 58.7% compared to native VNDN and the state-of-the-art subscription method.