Design, Implementation, and Empirical Validation of a Framework for Remote Car Driving Using a Commercial Mobile Network

Despite the fact that autonomous driving systems are progressing in terms of their automation levels, the achievement of fully self-driving cars is still far from realization. Currently, most new cars accord with the Society of Automotive Engineers (SAE) Level 2 of automation, which requires the driver to be able to take control of the car when needed: for this reason, it is believed that between now and the achievement of fully automated self-driving car systems, there will be a transition, in which remote driving cars will be a reality. In addition, there are tele-operation-use cases that require remote driving for health or safety reasons. However, there is a lack of detailed design and implementation available in the public domain for remote driving cars: therefore, in this work we propose a functional framework for remote driving vehicles. We implemented a prototype, using a commercial car. The prototype was connected to a commercial 4G/5G mobile network, and empirical experiments were conducted, to validate the prototype’s functions, and to evaluate its performance in real-world driving conditions. The design, implementation, and empirical evaluation provided detailed technical insights into this important research and innovation area.This research was funded in part by the EU Horizon 2020 5G-PPP 5G-INDUCE project (“Open cooperative 5G experimentation platforms for the industrial sector NetApps”) under grant number H2020-ICT-2020-2/101016941, by the EU Horizon Europe INCODE project (“Programming platform for intelligent collaborative deployments over heterogeneous edge-IoT environments”) under grant number HORIZON-CL4-2022-DATA-01-03/101093069, and by the EU Horizon Europe project INCODE: programming platform for intelligent collaborative deployments over heterogeneous edge-IoT environments (HORIZON-CL4-2022-DATA-01-03/101093069)

SliceNet: end-to-end cognitive network slicing and slice management framework in virtualised multi-domain, multi-tenant 5G networks

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Network slicing has emerged as a major new networking paradigm for meeting the diverse requirements of various vertical businesses in virtualised and softwarised 5G networks. SliceNet is a project of the EU 5G Infrastructure Public Private Partnership (5G PPP) and focuses on network slicing as a cornerstone technology in 5G networks, and addresses the associated challenges in managing, controlling and orchestrating the new services for users especially vertical sectors, thereby maximising the potential of 5G infrastructures and their services by leveraging advanced software networking and cognitive network management. This paper presents the vision of the SliceNet project, highlighting the gaps in existing work and challenges, the proposed overall architecture, proposed technical approaches, and use cases.Peer ReviewedPostprint (author's final draft

Water IoT monitoring system for aquaponics health and fishery applications

Aquaponic health is a very important in the food industry field, as currently there is a huge amount of fishing farms, and the demands are growing in the whole world. This work examines the process of developing an innovative aquaponics health monitoring system that incorporates high-tech back-end innovation sensors to examine fish and crop health and a data analytics framework with a low-tech front-end approach to feedback actions to farmers. The developed system improves the state-of-the-art in terms of aquaponics life cycle monitoring metrics and communication technologies, and the energy consumption has been reduced to make a sustainable system

P4-NetFPGA-based network slicing solution for 5G MEC architectures

Network Slicing is one of the fundamental capabilities of the new Fifth-generation (5G)networks. It is defined as several logical networks that are created to fulfil specific Quality of Service (QoS)and Quality of Experience (QoE)requirements and are available over the same physical infrastructure. This paper proposes a novel extension to P4-NetFPGA framework to achieve network slicing between different 5G users in the edge-to-core network segment. This solution provides hardware-isolation of the performance in terms of bandwidth, latency and packet loss of 5G network traffic. The work proposed has been validated in a real 5G infrastructure