PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



Open Optical Networks

01TWOOQ, 01TWOBG, 01TWOOV, 01TWOPE

A.A. 2022/23

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 And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni) - Torino
Master of science-level of the Bologna process in Ingegneria Informatica (Computer Engineering) - Torino
Master of science-level of the Bologna process in Nanotechnologies For Icts (Nanotecnologie Per Le Ict) - Torino/Grenoble/Losanna

Course structure
Teaching Hours
Lezioni 20
Esercitazioni in laboratorio 40
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Curri Vittorio Professore Ordinario IINF-03/A 20 0 20 0 6
Co-lectures
Espandi

Context
SSD CFU Activities Area context
ING-INF/03 6 D - A scelta dello studente A scelta dello studente
2022/23
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.
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 below fthe 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. Theoretical lectures will be integrated by exercises perfomed as virtual laboratories, as described in the following. NOTE: both theoretical lectures and practical sw exercise are fully compatible with remote online teaching.
• 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
• 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
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.
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. To support students with different background, recap letures on fundamental of optical communication and data networks will be provided to enable all the students to profitably follow the following lectures.
• 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 fundamental of optical communications and data networks - Optical Transport networks Tranponder Fiber propagation optical amplification ROADAMS Quality of transmission - Network abstraction as a weigthed graph - Network control protocols and data structures - Network operations - Open network control and management by open network operating system - Machine learning in network control NOTE: 1) All lectures are based on powerpoint presntation and fully compatible with remote lecturing 2) all topics will be applied in hands-on virtual laboratories that the students will be required to develop on their own laptopt exploiting opensource software (Pycharm or similar) and GitHub repository. Virtual laboratiores are seamless 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 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.
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 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.
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 focused on discussing the homework implemenation. Students will be required to show on their own laptop the solutions of the assigments. Then, to to the students will be required to summarize these results and theoretical implications in a ppt (or equivalent) presentation. The capabilty to properly organize the presentation and to effectively summarize results (figures, tables, etc...) will be part of the evaluation. Finally, theoretical questions will be asked related to the assigments' comments to evaluate the therotical part. To pass the exam it is manadatory to finalize the assignments. In the overall evaluation, 80% of the mark (24/30) is based on the presentation of code and assignments and 20% (6/30) on the related theoretical questions. The exam structure does not foresee any difference between online and onsite exam: online, the interview and homework check are carried on in the virtual classroom by sharing the laptop monitor, while onsite the same exam structure is carried on live in a room.
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.
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