One of the main goals of 5G networks is to support the technological and business needs of various industries (the so-called verticals), which wish to offer to their customers a wide range of services characterized by diverse performance requirements. In this context, a critical challenge lies in mapping in an automated manner the require- ments of verticals into decisions concerning the network infrastructure, including VNF placement, resource assignment, and traffic routing. In this paper, we seek to make such decisions jointly, accounting for their mutual interaction, and efficiently. To this end, we formulate a queuing- based model and use it at the network orchestrator to optimally match the vertical’s requirements to the available system resources. We then propose a fast and efficient solution strategy, called MaxZ, which allows us to reduce the solution complexity. Our performance evaluation, carried out accounting for multiple scenarios representative of real-world services, shows that MaxZ performs substantially better than state-of- the-art alternatives and consistently close to the optimum.

VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks / Agarwal, Satyam; Malandrino, Francesco; Chiasserini, Carla Fabiana; De, Swades. - In: IEEE-ACM TRANSACTIONS ON NETWORKING. - ISSN 1063-6692. - STAMPA. - 27:1(2019), pp. 433-446. [10.1109/TNET.2018.2890631]

VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks

Satyam Agarwal;Francesco Malandrino;Carla Fabiana Chiasserini;
2019

Abstract

One of the main goals of 5G networks is to support the technological and business needs of various industries (the so-called verticals), which wish to offer to their customers a wide range of services characterized by diverse performance requirements. In this context, a critical challenge lies in mapping in an automated manner the require- ments of verticals into decisions concerning the network infrastructure, including VNF placement, resource assignment, and traffic routing. In this paper, we seek to make such decisions jointly, accounting for their mutual interaction, and efficiently. To this end, we formulate a queuing- based model and use it at the network orchestrator to optimally match the vertical’s requirements to the available system resources. We then propose a fast and efficient solution strategy, called MaxZ, which allows us to reduce the solution complexity. Our performance evaluation, carried out accounting for multiple scenarios representative of real-world services, shows that MaxZ performs substantially better than state-of- the-art alternatives and consistently close to the optimum.
File in questo prodotto:
File Dimensione Formato  
ton_final.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 452.58 kB
Formato Adobe PDF
452.58 kB Adobe PDF Visualizza/Apri
TON_Swades_2019.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 2.01 MB
Formato Adobe PDF
2.01 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/11583/2721839
 Attenzione

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