The class of Open and Virtualized Networks, OVN in the following, aims at giving the fundamental skills for the novel professional operators known as Network Architects. These are requested to manage networks from the physical layer up to the network lyer. To this purpose, network elements and subsystems are virtualized, relying on physical and operational mathematical/statistical models. Virtualizations are summarized as common APIs and data structures to enabling an optimal orchestration through a network operating system. The proposed analyzes will enable an open network management based on common APIs and data structures. The teaching method will follow an application-oriented introduction of concepts. To this purpose, students will be required to develop Phyton module performing simple operations, exploiting the open source library GNPy of the Telecom Infra Project. Thus, students can operate in a license-free development environment, using their own laptop for virtual lab experiments. All the theoretical concepts will be proposed in the framework of a backbone transparent optical network supporting the deployment of different services including 5G low-latency connections and high-capacity data-center interconnections, as well as contents delivery services. After proposing an overview of the framework, the course will propose the fundamental concepts of the optical network elements (transceivers, fiber propagation, amplifiers and switches) with the purpose to enable the use of the APIs virtualizing their operational modes. Then, the concepts of network planning, management and control will be introduced, starting from application examples. Theoretical lectures will be integrated by exercises, on the following topics • Introduction to Python. A practical introduction to the basics of Python programming and the Object-Oriented paradigm. • Introduction to the GNPy. Introduction to the Python-based open source GNPy software (https://github.com/Telecominfraproject/oopt-gnpy). The students will learn how the software provides an abstraction of the single physical elements - the building blocks - of an optical network. • The Optical Network Abstraction. Using the building blocks given by GNPy the students will operate on the virtual models of the physical layer of a complete optical network as a weighted graph. • Network operations. The students will learn how to route data traffic through an optical network. • Deployment of services in the network. The student will optimize the data traffic through your optical network to support the requirements of services such as best Quality-of-Service or low-latency 5G-based services.

• Knowledges o Python language and GNPy library o Optical networking principles and challenges: telecom network overview, traffic engineering vs network engineering vs network design, Wavelength Division Multiplexing (WDM), WDM evolution to flexi-grid spectrum management. o Abstraction of network elements in a backbone networks: optical fiber, optical transceivers, optical amplifiers, switching elements o Heuristic (Optical Core) Network design methodologies o Logical topology design by heuristic approaches: greedy, local search. • Abilities o Virtualization of the data transport in a backbone network o Implementation of simple network operations on the virtualized physical layer o Modeling constraints and computing solutions to deploy different services. Perform physical-layer-aware

This class needs fundamental concepts of signal analysis, digital transmission and data networking as well as the fundamental skills in computer programming.

• Introduction to Python • Multilayer optical backbone networks • Data transport virtualization: Transceivers, WDM, fiber propagation and amplification. • Controlling, planning and managing a WDM network • Service deployment

Teaching method will be “hands-on”, so within lectures, students will be required to their own laptop so that theoretical concept will be immediately applied in simple exercises or reviewing examples. For approximately 1/3 of the available hours, the teaching assistants will support code development and in general exercise solving. The class will be organized as a series of concepts’ presentation and their application through python coding homework. Students will be required to operate on their own laptop and group working will be allowed.

Studying material will be available on “portale della didattica”. Books to deepen specific topics will be suggested as well

Slides; Esercitazioni di laboratorio; Video lezioni dell’anno corrente;

E' possibile sostenere l’esame in anticipo rispetto all’acquisizione della frequenza

Modalità di esame: Prova scritta (in aula); Prova orale obbligatoria; Elaborato progettuale individuale;

Exam: Written test; Compulsory oral exam; Individual project;

... Student assessment will be performed reviewing the Python coding and results of homework. During the oral review of the homework, theoretical questions will be asked to students.

Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.