Tesi etd-02102026-112152 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
TIRUYE, MULAT AYINET
URN
etd-02102026-112152
Titolo
Implementation and Integration of SRv6 NFV Chaining and Energy-Aware Optimization in the OMNeT++/INET Simulation Framework
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
COMPUTER ENGINEERING
Relatori
relatore Prof. Virdis, Antonio
relatore Prof. Mingozzi, Enzo
relatore Dott. Casu, Federico
relatore Prof. Mingozzi, Enzo
relatore Dott. Casu, Federico
Parole chiave
- INET
- NFV
- OMNeT++
- SFC
- SRv6
Data inizio appello
27/02/2026
Consultabilità
Non consultabile
Data di rilascio
27/02/2029
Riassunto (Inglese)
Riassunto (Italiano)
This thesis presents the implementation and integration of an SRv6-based Network Function Virtualization (NFV) chaining mechanism within the OMNeT++/INET simulation framework, combined with an energy‑aware optimization tool for the placement of virtual network functions.
The work includes the development of packet‑level SRv6 service chaining support inside INET, enabling the simulation of SRv6 behaviors consistent with current standards. The simulator is integrated with an existing optimization module, developed in previous work, which determines the placement of network functions on physical nodes with the goal of minimizing energy consumption.
The resulting framework has been validated and evaluated through a series of experiments aimed at assessing correctness and performance. The results demonstrate that the system accurately models SRv6‑based service chaining and effectively couples it with energy‑aware placement strategies. Overall, the framework provides a flexible and extensible environment for studying NFV chaining and resource optimization in next‑generation programmable networks.
The work includes the development of packet‑level SRv6 service chaining support inside INET, enabling the simulation of SRv6 behaviors consistent with current standards. The simulator is integrated with an existing optimization module, developed in previous work, which determines the placement of network functions on physical nodes with the goal of minimizing energy consumption.
The resulting framework has been validated and evaluated through a series of experiments aimed at assessing correctness and performance. The results demonstrate that the system accurately models SRv6‑based service chaining and effectively couples it with energy‑aware placement strategies. Overall, the framework provides a flexible and extensible environment for studying NFV chaining and resource optimization in next‑generation programmable networks.
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