5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today’s systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high under medium-low traffic load.
Energy-efficient Traffic Allocation in SDN-based Backhaul Networks: Theory and Implementation / Tadesse, SENAY SEMU; Casetti, CLAUDIO ETTORE; Chiasserini, Carla Fabiana; Landi, G.. - STAMPA. - (2017), pp. 209-215. (Intervento presentato al convegno The 14th Annual IEEE Consumer Communications & Networking Conference (IEEE CCNC 2017) tenutosi a Las Vegas (USA) nel 08-11 January 2017) [10.1109/CCNC.2017.7983107].
Energy-efficient Traffic Allocation in SDN-based Backhaul Networks: Theory and Implementation
TADESSE, SENAY SEMU;CASETTI, CLAUDIO ETTORE;CHIASSERINI, Carla Fabiana;
2017
Abstract
5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today’s systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high under medium-low traffic load.File | Dimensione | Formato | |
---|---|---|---|
camera_ready_v2.pdf
accesso aperto
Descrizione: Articolo principale
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
PUBBLICO - Tutti i diritti riservati
Dimensione
395.93 kB
Formato
Adobe PDF
|
395.93 kB | Adobe PDF | Visualizza/Apri |
CCNC_2017.pdf
non disponibili
Descrizione: Articolo principale
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
548.13 kB
Formato
Adobe PDF
|
548.13 kB | 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.
https://hdl.handle.net/11583/2679630
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo