Towards a High Efficiency of Native NDN over Wi-Fi 6 for the Internet of Vehicles

TL;DR

This paper proposes a unicast-based variant of Native NDN over Wi-Fi 6 for vehicular networks, significantly improving throughput and request satisfaction compared to standard Native NDN.

Contribution

It introduces a novel unicast transmission approach for Native NDN over Wi-Fi 6, addressing throughput and efficiency issues in vehicular environments.

Findings

Our proposal achieves up to 89% of satisfied requests.

It delivers over 200% more data received than standard NDN.

Performance improvements are demonstrated in Wi-Fi 6 vehicular scenarios.

Abstract

Named Data Networking (NDN) is a top-notched architecture to deal with content distribution over the Internet. With the explosion of video streaming transmission and future massive Internet of Things and Vehicles (IoT/IoV) traffic, evolving Wi-Fi networks will play an essential role in such ecosystems. However, Native NDN deployment over wireless networks may not perform well. Wi-Fi broadcasts/multicasts result in reduced throughput due to the usage of basic service mode. Despite recent initial works addressing that issue, further studies and proposals are required to boost the adoption of Native NDN. We advocate that an initial step towards designing a feasible Native NDN over wireless networks should be understanding the challenges in emerging scenarios and providing a uniform baseline to compare and advance proposals. To this end, first, we highlight some challenges and directions to improve throughput and energy efficiency, reduce processing overhead, and security issues. Next, we propose a variant of NDN that minimizes the problems identified by performing transmission via unicast to avoid storms in wireless networks. Finally, we conducted a performance evaluation to compare Standard Native NDN with our proposal on Wi-Fi 6 vehicular networks. The results show that our proposal outperforms the Standard NDN in the evaluated scenarios, reaching values close to 89% of satisfied requests, achieving more than 200% of data received than Standard NDN.