Design Guidelines for Blockchain-Assisted 5G-UAV Networks

TL;DR

This paper proposes a blockchain-enabled UAV network architecture for 5G smart city applications, enhancing decentralized, secure, and reliable service delivery in dynamic IoT environments.

Contribution

It introduces a novel blockchain-based framework for UAV-supported 5G networks, enabling decentralized, secure, and flexible service provisioning for smart city scenarios.

Findings

Higher data delivery success rates compared to traditional UAV networks

Enhanced security and reliability through blockchain integration

Effective support for diverse IoT and service requests

Abstract

Fifth Generation (5G) wireless networks are designed to meet various end-user Quality of Service (QoS) requirements through high data rates (typically of Gbps order) and low latencies. Coupled with Fog and Mobile Edge Computing (MEC), 5G can achieve high data rates, enabling complex autonomous smart city services such as the large deployment of self-driving vehicles and large-scale Artificial Intelligence (AI)-enabled industrial manufacturing. However, to meet the exponentially growing number of connected IoT devices and irregular data and service requests in both low and highly dense locations, the process of enacting traditional cells supported through fixed and costly base stations requires rethought to enable on-demand mobile access points in the form of Unmanned Aerial Vehicles (UAV) for diversified smart city scenarios. This article envisions a 5G network environment that is supported by blockchain-enabled UAVs to meet dynamic user demands with network access supply. The solution enables decentralized service delivery (Drones as a Service) and routing to and from end-users in a reliable and secure manner. Both public and private blockchains are deployed within the UAVs, supported by fog and cloud computing devices and data centers to provide wide range of complex authenticated service and data availability. Particular attention is paid tocomparing data delivery success rates and message exchange in the proposed solution against traditional UAV-supported cellular networks. Challenges and future research are also discussed with highlights on emerging technologies such as Federated Learning.