Tesi etd-02052024-160715 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
GHADIR, SETAYESH
URN
etd-02052024-160715
Titolo
Deep Q-Learning for Enhanced SD-WAN Performance and Reliability in Rural Areas
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA E NETWORKING
Relatori
relatore Adami, Davide
relatore Borgianni, Luca
relatore Borgianni, Luca
Parole chiave
- Deep Q-Network (DQN) algorithm
- reinforcement learning
- reliability
- rural networks
- software-defined wide area network
Data inizio appello
23/02/2024
Consultabilità
Non consultabile
Data di rilascio
23/02/2027
Riassunto
This thesis explores the deployment of software-defined wide area network (SD-WAN) in rural networks, enhancing reliability through reinforcement learning using the deep Q-networks algorithm. Implemented through Python and Mininet simulation, DQN should optimizes link selection based on criteria such as bandwidth, traffic type, and link status, aiming to improve overall network performance in challenging rural environments.
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