Tesi etd-09302025-222058
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Tipo di tesi
Corso di Dottorato (D.M.226/2021)
Autore
RADOVIC, MARGITA
URN
etd-09302025-222058
Titolo
SDN Control and Modeling for Efficient Next-Generation Optical Networks
Settore scientifico disciplinare
ING-INF/03
Corso di studi
Istituto di Tecnologie della Comunicazione, dell'Informazione e della Percezione - Ph.D. in Emerging Digital Technologies
Relatori
relatore Prof. SAMBO, NICOLA
Tutor Dott. SGAMBELLURI, ANDREA
Tutor Dott. SGAMBELLURI, ANDREA
Parole chiave
- Nessuna parola chiave trovata
Data inizio appello
05/12/2025;
Disponibilità
completa
Riassunto analitico
The rapid growth of global data traffic continues to challenge the scalability and effi-
ciency of optical transport networks. Traditional optical systems, characterized by static
configurations and high design margins, are increasingly inefficient for meeting future
demands on spectrum efficiency, energy consumption, and operational flexibility. To
support evolving services and traffic dynamics, optical networks require programmable
and adaptive control mechanisms that can optimize the use of existing resources while
maintaining interoperability across heterogeneous systems.
This thesis investigates software-defined networking (SDN)–enabled approaches for
enhancing the performance and flexibility of optical networks. It first examines super-
channel transmission as a means to increase spectral efficiency through automated op-
timization of subcarrier spacing and filter bandwidth, enabling low-margin operation
without compromising the quality of transmission (QoT). The impact of margin reduction
on power consumption is also investigated, revealing a trade-off between spectral and
energy efficiency and highlighting the potential for power-aware super-channel opera-
tion. Next, multiband (MB) transmission is explored as a strategy for capacity expansion,
where thulium-doped fiber amplifiers (TDFAs) operating in the S-band are modeled and
controlled via SDN using machine learning techniques to achieve dynamic and accu-
rate configuration. Finally, the thesis investigates point-to-multipoint (P2MP) coherent
transceivers and digital subcarrier multiplexing (DSCM) for dynamic optical access and
aggregation, employing OpenConfig extensions to enable automated, vendor-neutral con-
trol of network resources. In addition, fully dynamic multipoint-to-multipoint (MP2MP)
operation is demonstrated using emulated DSCM transceivers.
The results demonstrate the potential of SDN-based control to improve spectrum
utilization, operational efficiency, and adaptability in next-generation optical networks.
These studies contribute to optical network operation that is in line with the evolving re-
quirements for next-generation networks, supporting more efficient, flexible, and adaptive
use of network resources.
ciency of optical transport networks. Traditional optical systems, characterized by static
configurations and high design margins, are increasingly inefficient for meeting future
demands on spectrum efficiency, energy consumption, and operational flexibility. To
support evolving services and traffic dynamics, optical networks require programmable
and adaptive control mechanisms that can optimize the use of existing resources while
maintaining interoperability across heterogeneous systems.
This thesis investigates software-defined networking (SDN)–enabled approaches for
enhancing the performance and flexibility of optical networks. It first examines super-
channel transmission as a means to increase spectral efficiency through automated op-
timization of subcarrier spacing and filter bandwidth, enabling low-margin operation
without compromising the quality of transmission (QoT). The impact of margin reduction
on power consumption is also investigated, revealing a trade-off between spectral and
energy efficiency and highlighting the potential for power-aware super-channel opera-
tion. Next, multiband (MB) transmission is explored as a strategy for capacity expansion,
where thulium-doped fiber amplifiers (TDFAs) operating in the S-band are modeled and
controlled via SDN using machine learning techniques to achieve dynamic and accu-
rate configuration. Finally, the thesis investigates point-to-multipoint (P2MP) coherent
transceivers and digital subcarrier multiplexing (DSCM) for dynamic optical access and
aggregation, employing OpenConfig extensions to enable automated, vendor-neutral con-
trol of network resources. In addition, fully dynamic multipoint-to-multipoint (MP2MP)
operation is demonstrated using emulated DSCM transceivers.
The results demonstrate the potential of SDN-based control to improve spectrum
utilization, operational efficiency, and adaptability in next-generation optical networks.
These studies contribute to optical network operation that is in line with the evolving re-
quirements for next-generation networks, supporting more efficient, flexible, and adaptive
use of network resources.
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