Towards scalable, fair and robust data dissemination via cooperative vehicular communications

Recent advances in infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communications are envisioned to enable a variety of emerging applications in vehicular networks, where it is imperative to provide efficient data services via cooperative vehicular communications. In this work, we present the data dissemination system via cooperative I2V and V2V communications. We formulate the problem by investigating both the communication constraint and the application requirement on data dissemination. The goal is to maximize the system performance by exploiting the joint effects of I2V and V2V communications. On this basis, we propose an on-line scheduling algorithm to enable scalable, fair and robust data dissemination. The algorithm makes scheduling decisions by transforming the data dissemination problem to the maximum weighted independent set (MWIS) problem and approximately solving MWIS using a greedy method. We build the simulation model based on realistic traffic and communication characteristics. A comprehensive simulation study demonstrates that the proposed solution is able to effectively strike a balance between I2V and V2V data services and maximize system performance in terms of scalability, fairness and robustness.