Cost-Efficient Sensory Data Transmission in Heterogeneous Software-Defined Vehicular Networks

Abstract

Sensing and networking have been regarded as key enabling technologies of future smart vehicles. Sensing allows vehicles to be context awareness, while networking empowers context sharing among ambients. Existing vehicular communication solutions mainly rely on homogeneous network, or heterogeneous network via data offloading. However, today's vehicular network implementations are highly heterogeneous. Therefore, conventional homogeneous communication and data offloading may not be able to satisfy the requirement of the emerging vehicular networking applications. In this paper, we apply the software-defined network (SDN) to the heterogeneous vehicular networks to bridge the gaps. With SDN, heterogeneous network resources can be managed with a unified abstraction. Moreover, we propose an SDN-based wireless communication solution, which can schedule different network resources to minimize communication cost. We investigate the problems in both single and multiple hop cases. We also evaluate the proposed approaches using traffic traces. The effectiveness and the efficiency are validated by the results.