Caricamento in corso...
Open Optical Networks
01TWOOQ, 01TWOBG, 01TWOPE, 01TWOWP, 01TWOXW
A.A. 2025/26
Course Language
Inglese
Degree programme(s)
Master of science-level of the Bologna process in Ingegneria Elettronica (Electronic Engineering) - Torino
Master of science-level of the Bologna process in Communications Engineering - Torino
Master of science-level of the Bologna process in Nanotechnologies For Icts (Nanotecnologie Per Le Ict) - Torino/Grenoble/Losanna
Master of science-level of the Bologna process in Communications Engineering - Torino
Master of science-level of the Bologna process in Ingegneria Elettronica (Electronic Engineering) - Torino
Course structure
| Teaching | Hours |
|---|---|
| Lezioni | 39 |
| Esercitazioni in laboratorio | 21 |
Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
|---|---|---|---|---|---|---|---|
| Curri Vittorio | Professore Ordinario | IINF-03/A | 36 | 0 | 6 | 0 | 7 |
Co-lectures
Context
| SSD | CFU | Activities | Area context | ING-INF/03 | 6 | D - A scelta dello studente | A scelta dello studente |
|---|
2025/26
The class of Open Optical Networks, OON in the following, aims at describing peculiarities of data networking based on the exploitation of photonic transmission on the optical fiber networks. With the specific purpose of multilayer optimization down from the IP layer, enabling full exploitation of the photonic transport layer either using the state-of-the art WDM fixed-grid, either the already standardized flex-grid. The network analysis will rely on the progressive abstraction of network elements and network subsystems to 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 network control operations, exploiting the open source library GNPy of the Telecom Infra Project. These will be the homeworks used to the student assessment. Coding will be addressed to the standard open-source procedure based on GitHub. Lectures on Python coding and use of Github will be part of the class. Seminars will be given by companies and operators of in the field. In particular, by Facebook, Cisco, SMOptics, Coriant Networks, OpenFiber and TIM. The final student assessment will be done through the discussion on the assigned homework. For OON students will be available a set of homework that may evolve into a Master thesis work, being its initial phase. The OON class will take advantage of the experience gained participating to the consortium Telecom Infra Project.
Fiber-optic networks form the backbone of the global internet, carrying the vast majority of data traffic—over 95% of terrestrial and private network traffic, and more than 99% of international data flows via undersea cables. As demand for bandwidth, ultra-low latency, and energy-efficient communication surges, open and programmable fiber-optic networks have become indispensable for building scalable, interoperable, and future-proof digital infrastructure.
The course on Open Optical Networks (OON) delves into the fundamentals and advanced strategies for basic network data transport and control over optical fiber systems. Its focus spans from the photonic layer up to the IP layer, with a view to fully leverage photonic transport using both fixed-grid WDM and flex-grid technologies.
Network analysis is taught through stepwise abstraction of network components and subsystems in a network digital twin, facilitating open and integrated network management using standard APIs and data structures.
The teaching approach is strongly application- and practice-oriented, with lectures seamlessly blended with virtual laboratory sessions:
Students progressively code Python modules to execute basic network data transport and control tasks, optionally utilizing the open-source GNPy library from the Telecom Infra Project.
These virtual labs guide students through building a “toy” digital twin optical network, enabling hands-on experimentation with control logic and network load balancing.
Coding follows standard open-source practices, including training on Python development and GitHub collaboration workflows.
The course also introduces foundational concepts of quantum communications over optical fiber.
To enrich the learning experience, seminars may possibly be organized featuring industry experts and operators—potentially including speakers from Nokia, NTT, GARR, OpenFiber, and FiberCop.
The final exam is based on assignment discussions and outcomes, with optional project tracks available that can evolve into a Master's thesis. The course draws on insights and collaborations from the Telecom Infra Project consortium and the IOWN Global Forum—notably their work on All-Photonics Networks (APN) and Digital Twin architectures, providing students with exposure to cutting-edge research and industry innovations.
NOTE: Both theoretical lectures and virtual laboratory exercises are fully compatible with remote online delivery.
• Knoweledges
o Python language
o State-of-the art transceivers for optical communications
o Foundations of optical fiber propagation and modeling its impairments
o Amplifiers and passive components
o WDM spectral use and standards
o ROADMs and node structure in general
o YANG, Netconfig, GMPLS, OTN
• Abilities
o Python development within GitHub
o Emulation of optical layer in photonic networks
o Routing spectral and wavelength assignment
o Multilayer orchestration
o In general, ability to perform physical-layer-aware network analysis, design and optimization
By the end of the Open Optical Networks (OON) course, students will have acquired the following knowledge and abilities:
Knowledge
* Python programming language fundamentals for networking applications
* State-of-the-art optical transceivers for high-speed communications
* Foundations of optical fiber propagation and modeling of physical-layer impairments
* Optical amplifiers and passive optical components
* General concepts of the Digital Twin in network design and operation
* WDM spectral utilization and related standards (fixed-grid and flex-grid)
* ROADM architectures and optical node structures
* Introduction to open networking institutions (e.g., IETF, OIF, ONF, TIP, OpenROADM, IOWN), and their role in developing open protocols and APIs
* Data modeling and network programmability with YANG, NETCONF, and RESTCONF
* Introduction to machine learning techniques for optical network control and optimization
* Fundamentals of quantum key distribution (QKD) and its integration into optical fiber networks
Abilities
* Develop and manage Python-based projects within GitHub using open-source best practices
* Emulate the optical layer in photonic networks for design and experimentation
* Perform routing, spectrum, and wavelength assignment in WDM networks
* Implement multilayer orchestration across photonic and higher layers
* Conduct physical-layer-aware network analysis, design, and optimization leveraging the network digital twin
This class will need foundation of signal analysis and digital transmission as well as general knowledge of the Internet structure.Moreover, fundamental skill in computer programming are needed. If selected students will miss some of the prerequisites, specific summary session on selected topics will be organized.
* Foundations of signal analysis and digital transmission are required.
* General knowledge of the Internet structure is welcome but not mandatory.
* Fundamental skills in computer programming are needed.
* To support students with different backgrounds, recap lectures on the fundamentals of optical communications and data networks will be provided. These will enable all students to follow the subsequent lectures profitably, regardless of their initial background.
• Introduction to Python and Github
• Introduction of optical communications and networking
• Abstraction of disaggregated optical networks
• Abstraction of data transport: fiber propagation and amplification
• Optimization
• Controlling
* Class introduction
* Introduction to Python
* Recap lectures on fundamentals of optical communications and data networks
* The concept of Digital Twin
* Optical Transport Networks
* Transponders
* Fiber propagation
* Optical amplification
* ROADMs
* Quality of transmission
* Open network abstraction as a weighted graph (digital twin)
* Open network control protocols and data structures
* Network operations
* Open network control and management with open network operating systems, open protocols, and open APIs
* Machine learning in network control
* Introduction to quantum communications and networking
NOTE:
1. All lectures are based on PowerPoint presentations and are fully compatible with remote lecturing.
2. All topics will be applied in hands-on virtual laboratories that students will be required to develop on their own laptops using open-source software (PyCharm or similar) and GitHub repositories. Virtual laboratories are seamlessly compatible with remote teaching.
The exam opens to the students the possibility to prosecute in master's thesis works perfomed within the Telecom Infraproject in collaborations with vendors and operators, as for instance in developing open API abtracting physical layer functionalities with an open network opearating systems (e.g, ONOS) and testing them in the open harware availlable in th eoptical communications lab of PoliTo.
The exam also opens the possibility for students to continue their work in the form of a Master’s thesis in collaboration with the Telecom Infra Project (TIP) and the IOWN Global Forum, together with vendors and network operators. Thesis activities may include, for example, developing open APIs to abstract physical-layer functionalities within open network operating systems (e.g., ONOS or OpenDaylight), and testing these solutions on the open hardware platforms available in the PoliTo-Links Open PLANET Lab . The lab features a three-node optical network testbed with links up to 2000 km, directly interconnected with the GARR production network and the TOP-IX regional internet exchange point, enabling realistic experimentation that combines advanced optical transmission with real operational environments. Research directions also include using the optical network as a distributed sensor (e.g., for vibration or environmental event detection), and the application of artificial intelligence for both network control and sensing, extending the role of fiber infrastructure beyond pure data transport.
Teaching method will be “hands-on”, so within every lecture, 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 main teacher will be helped by assistants supporting 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
Teaching method will be “hands-on”, so within every lecture, 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 main teacher will be helped by assistants supporting 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 (virtual laboratories). In virtual laboratories the students will be required to code on their own laptopt exploiting opensource software (Pycharm or similar) and GitHub repository. Virtual laboraties are saemless compatible with remote teaching. All theoretical lectures will be based on powerpoint slides provided in advance to the students, enabling a teaching method fully compatible with remote learning. Theoretical class will also possibly use the online graphic interface of GNPy (https://gnpy-ui.azurewebsites.net/). All lectures will be recorded and availble on the portal.
Studying material will be available on “portale della didattica”. Books to deepen specific topics will be suggested as well.
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; Video lezioni tratte da anni precedenti; Materiale multimediale ; Strumenti di simulazione;
Lecture slides; Lab exercises; Video lectures (current year); Video lectures (previous years); Multimedia materials; Simulation tools;
Modalità di esame: Prova orale obbligatoria; Prova pratica di laboratorio;
Exam: Compulsory oral exam; Practical lab skills test;
...
Student assessment will be performed reviewing the Python coding homework, including the proper use of github and reports. This work can be a group work. This process will deliver a maximum of 25 points. The remaining 5 points – and possible laude – will be assigned during the individual final oral discussion.
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.
Exam: Compulsory oral exam; Practical lab skills test;
The exam is an oral interview structured as follows:
* 5–10 minutes: Students present their assignments directly on their laptop, showing code and results.
* 20 minutes: Students give a PowerPoint (or equivalent) presentation summarizing results from the assignments and theoretical implications. The ability to organize material and effectively use figures, tables, and diagrams will be evaluated.
* 10–15 minutes: Theoretical questions related to the assignments and their comments, aimed at assessing theoretical understanding.
To pass the exam it is mandatory to complete all assignments.
Evaluation criteria:
* 70% of the grade is based on the presentation of code and assignments, including meaningful theoretical comments.
* 30% of the grade is based on the related theoretical questions.
* Up to 3 bonus points can be earned by continuously developing the assignments through GitHub Classroom.
In case of special needs, the exam is fully compatible with an online procedure.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.