New ICT Infrastructure & Reference Architecture to Support Operations in Future PI Logistics Networks

Technical Approach

The technology approach of the ICONET project will be to produce a Cloud-based PI Control and Management Platform that will serve as an experimental platform that will support the research and development required to further the Physical Internet concept over the course of the project.

The requirements gathering work stream of the project will feed into the PI reference architecture blueprint, which will be used as the basis for initial and subsequent design iterations of the proof of concept (PoC) Cloud-based PI Control and Management Platform. This PoC platform will enable the detailed study of deployed and simulated Physical Internet use cases driven by the requirements of the Living Labs. It will allow for detailed research on all Physical Internet concepts to further the state of the art for the PI digital prototype over the course of ICONET.

By conducting detailed research into the areas of PI node & PI inter-node connectivity, PI nodes intelligent optimisation, network abstractions and encapsulation protocols, routing logic and algorithms, IoT topologies and IoT integration mechanisms, security and privacy, data analytics for real-time PI network optimisation and PI network simulation, it is hoped to make significant inroads in the following areas:

• Deliver the digital backbone for PI. A cloud based connectivity platform on which PI networks can be created based on federated PI nodes
• Support PI connectivity platform as a service on a multitude of cloud infrastructures
• Facilitate inter-cloud inter-networking to create federations of PI nodes/hubs
• Form a digital PI connectivity framework – Bridging and federating previously unconnected logistics networks to allow realisation of the PI concept

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© 2018 ICONET

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This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains
EU-flag-(high-resolution)

This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains