Marini, Riccardo
(2019)
Software Defined Networking Architectures for LoRaWAN.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Telecommunications engineering [LM-DM270], Documento full-text non disponibile
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Abstract
This thesis proposes new solutions for LoRaWAN networks taking advantages of Software Defined Networking architectures. In particular, an analysis of the current implementation of the Adaptive Data Rate mechanism developed by LoRaWAN standard, as well as a proposal of a new algorithm, will be provided. This will be addressed by considering both a cloud-based and a fog-based architecture in order to observe differences between the two approaches in a number of different scenarios. The proposed algorithms and the two architectures are compared via numerical results achieved through simulations and experimental tests.
Abstract
This thesis proposes new solutions for LoRaWAN networks taking advantages of Software Defined Networking architectures. In particular, an analysis of the current implementation of the Adaptive Data Rate mechanism developed by LoRaWAN standard, as well as a proposal of a new algorithm, will be provided. This will be addressed by considering both a cloud-based and a fog-based architecture in order to observe differences between the two approaches in a number of different scenarios. The proposed algorithms and the two architectures are compared via numerical results achieved through simulations and experimental tests.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Marini, Riccardo
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
LoRa,LoRaWAN,Adaptive Data Rate,Cloud computing,fog computing
Data di discussione della Tesi
3 Ottobre 2019
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Marini, Riccardo
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
LoRa,LoRaWAN,Adaptive Data Rate,Cloud computing,fog computing
Data di discussione della Tesi
3 Ottobre 2019
URI
Gestione del documento: