5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it can perform. To this end, we formulate an optimization problem accounting for the main features of 5G nodes and the traffic they serve, allowing joint decisions about (i) the nodes to activate, (ii) the network functions they run, and (iii) the traffic routing. Our optimization module is integrated within the management and orchestration framework of 5G, thus enabling swift and high-quality decisions. We test our scheme with both a real-world testbed based on OpenStack and OpenDaylight, and a large-scale emulated network whose topology and traffic come from a real-world mobile operator, finding it to consistently outperform state-of-the art alternatives and closely match the optimum.

An Optimization-enhanced MANO for Energy-efficient 5G Networks / Malandrino, Francesco; Chiasserini, Carla Fabiana; Casetti, Claudio; Landi, Giada; Capitani, Marco. - In: IEEE-ACM TRANSACTIONS ON NETWORKING. - ISSN 1063-6692. - STAMPA. - 27:4(2019), pp. 1756-1769. [10.1109/TNET.2019.2931038]

An Optimization-enhanced MANO for Energy-efficient 5G Networks

Chiasserini, Carla Fabiana;Casetti, Claudio;
2019

Abstract

5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it can perform. To this end, we formulate an optimization problem accounting for the main features of 5G nodes and the traffic they serve, allowing joint decisions about (i) the nodes to activate, (ii) the network functions they run, and (iii) the traffic routing. Our optimization module is integrated within the management and orchestration framework of 5G, thus enabling swift and high-quality decisions. We test our scheme with both a real-world testbed based on OpenStack and OpenDaylight, and a large-scale emulated network whose topology and traffic come from a real-world mobile operator, finding it to consistently outperform state-of-the art alternatives and closely match the optimum.
File in questo prodotto:
File Dimensione Formato  
optiloop_ton_final.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 504.42 kB
Formato Adobe PDF
504.42 kB Adobe PDF Visualizza/Apri
TON_2019_Energy_Final.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 1.73 MB
Formato Adobe PDF
1.73 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2743134
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo