In the field of optical communications, the data traffic undergoes a continuos growth related both to technological innovation and to the adoption and contamination of methodologies originating from a variety of disciplines.

The goal of our team is to provide reliable solutions and implementations able to face up the technical challenges in order to achieve higher performance and to meet the increasing market demand.

Machine Learning Aided Networking

In collaboration with LINKS Foundation and vendor companies, the PLANET team  develops procedures and methods using the artificial intelligence in order to optimize the control of optical line systems. Furthermore, relying on the knowledge on the physical layer abstraction, there is a careful investigation on the use of the machine learning techniques in managing optical networks focusing on planning and failure recovery.

Multi-band Optical Networks

Wideband Optical Network (WON) is a doctoral-level training network funded by the European Commission under Horizon2020 Marie Sklodowska-Curie ITN Action. The programme trains 14 early-stage researchers (ESRs) in the area of multiband optical networks through the collaboration of academic and industrial highly qualified institutions. Solutions identified within WON will enable to overcome a possible traffic-crunch by achieving a 10-fold increase in the usable optical bandwidth of single-mode fibres. Prof. Curri represents PoliTo within the H2020-MSCA-ETN WON. Some of the PhD students are currently trained at PoliTo as part of the PLANET team, investigating on the extension of data transport beyond the C-band with several invited talks at conferences and on major journals.

Multi-Layer Network Simulation

The PLANET team operates in developing simulation algorithms and research investigations based on the Synopsys software tools. Prof. Curri is the scientific responsible of the MSA with Synopsys for the activities supporting the development of the RSoft optical solution suite.

Multi-Service Optical Networks

The cohexistence of heterogeneous features such as modern high capacity transmission, backward compatibility with legacy equipment and distribution of reference unit of the standard time for metrologic purposes in the same optical network enables the reuse of the same infrastructure but it also leads to the coexistence of strongly heterogeneous signals. In collaboration with LINKS Foundation, INRIM and vendor companies, the PLANET team investigates such non-trivial scenario to properly address the management, planning and optimization procedures. In particular, the PLANET team is part of the TIFOON (EMPIR Call 2018 – SRT-s21) project funded by the EU, being the only telecom group of the project that targats the use of telecom technologies to deliver time and frequency within optical data network infrastructures.

Open Optical Networks

Politecnico di Torino is an active member of the consortium Telecom Infra Project (TIP) promoted by Facebook that aims at the development of HW and SW for open and disaggregated wireless and optical networks. Prof. Curri represents PoliTo within the consortium and he is the scientific responsible of the PoliTo-TIP MSA. He leads the PLANET team activities within the OOPT working group of the TIP. The PLANET team collaborates with operators and vendors, such as Facebook, Microsoft, Orange, Telefonica, Telia, Cisco, Juniper Network, Infinera and many others, to develop mathematical modelling for the abstraction of the physical layer and to implement the outcomes within an open source python library named GNPy. Prof. Curri holds the role of GNpy Scientific Chair within the PSE-OOPT working group of the TIP. The GNpy library aims at estimating and predicting the physical layer quality of transmission (QoT) with the purpose of promoting the implementation of open common API’s for management and control of networks including the physical layer awareness. The developed source code is available in the TIP GitHub repositories OOPT-GNpy.

Physical Layer Aware Network Assessment

Thanks to the physical layer abstraction enabled by the data transport models, the PLANET team has introduced the Statistical Network Assessment Process (SNAP) framework for a Monte Carlo in-line analyses on the impact of the physical layer options on networking metrics. Within such a framework, the PLANET team has also developed the Offline Physical Layer Assessment (OPLA) tools with the aim of the off-line evaluation of the impact of the physical layer merit on the network layer performances. These activities are funded by vendor companies.

Power Electronics Innovation Center

The Power Electronics Innovation Center (PEIC) objective is to provide power conversion solutions for electric vehicles powertrains and chargers, more electric aircrafts, energy production and harvesting from renewables, smart transformers for electrical grids, more efficient variable speed drives. Prof. Curri is part of the interdepartmental PoliTo center PEIC led by Prof. Radu Bojoi of DENERG. The PLANET team contributes to the PEIC by implementing an optical bus to remotize controlling in power electronic grids and to operate on power electronic as a cloud implementing the Internet of Power paradigm. In collaboration with the LINKS Foundation, the PLANET team has developed a prototype for the optical bus.