Scalability Analysis of Context-Aware Multi-RAT Car-to-Cloud Communication

In 2020 IEEE 92th Vehicular Technology Conference (VTC-Fall), Victoria, B.C., Canada, October 2020

Abstract:

Nowadays always-connected vehicles create opportunities for novel services like vehicles serving as highly mobile sensor platforms in the Internet of Things context. Hereby, cars upload and transfer their sensor data readings via a mobile communication network into the cloud. Data is shared in the cloud via vehicle big data marketplaces. As wireless resources are limited and shared by all users, data transfers need to be conducted efficiently. The ongoing growth of  generated data inside vehicles and thereby the increasing data upload demand becomes more and more challenging to Mobile Network Operators. Within the scope of the work, an opportunistic Multi-Radio-Access-Technology (Multi-RAT) uploading approach is proposed in order to conduct those data uploads faster and more efficiently. This approach leverages multiple network interfaces and combines them to one unified communication link. Data uploads can be delayed to exploit good channel conditions and avoid uploads when the channel quality is insufficient. The simulative results and evaluations highlight that the proposed method is well-suited for vehicular data uploads. Even though a trade-off in the age of information is created, the throughput is increased. Besides, better performance in spectral efficiency is achieved in comparison to traditional single-link transmissions.