Programmable network hardware is emerging as a viable option for offloading and thus accelerating network functions. However, the heterogeneous resources available in the network calls for a disaggregated deployment approach. Programmable switches, programmable Network Interface Cards (NICs), and in-network compute nodes exposes different peculiar resources and capabilities that can be maximally exploited only if the network functions are decomposed into multiple smaller network functions. This work presents a framework for the automatic deployment of disaggregated and decomposed network functions. The framework comprises an orchestrator capable of deploying the decomposed network functions on programmable network hardware and software switches running in containers. The orchestrator exploits an optimization model for choosing the best decomposition according to the traffic demands, the network topology, and other constraints. An improved seamless deployment model and heuristic also accounts for the necessity of rerouting traffic when hardware nodes need to be re-programmed. Furthermore, the framework provides a tool to combine multiple functions into a single P4 program via a template pipeline that can be deployed to a programmable switch. Numerical results highlight the advantages of offloading decomposed network functions to programmable network hardware. Furthermore, we show how the seamless deployment model and heuristic have negligible effects on the allocation time and accepted traffic requests while guaranteeing the rerouting of traffic when switches are put in maintenance mode.

Network Function Decomposition and Offloading on Heterogeneous Networks with Programmable Data Planes

Moro, Daniele;Verticale, Giacomo;Capone, Antonio
2021-01-01

Abstract

Programmable network hardware is emerging as a viable option for offloading and thus accelerating network functions. However, the heterogeneous resources available in the network calls for a disaggregated deployment approach. Programmable switches, programmable Network Interface Cards (NICs), and in-network compute nodes exposes different peculiar resources and capabilities that can be maximally exploited only if the network functions are decomposed into multiple smaller network functions. This work presents a framework for the automatic deployment of disaggregated and decomposed network functions. The framework comprises an orchestrator capable of deploying the decomposed network functions on programmable network hardware and software switches running in containers. The orchestrator exploits an optimization model for choosing the best decomposition according to the traffic demands, the network topology, and other constraints. An improved seamless deployment model and heuristic also accounts for the necessity of rerouting traffic when hardware nodes need to be re-programmed. Furthermore, the framework provides a tool to combine multiple functions into a single P4 program via a template pipeline that can be deployed to a programmable switch. Numerical results highlight the advantages of offloading decomposed network functions to programmable network hardware. Furthermore, we show how the seamless deployment model and heuristic have negligible effects on the allocation time and accepted traffic requests while guaranteeing the rerouting of traffic when switches are put in maintenance mode.
File in questo prodotto:
File Dimensione Formato  
Network_Function_Decomposition_and_Offloading_on_Heterogeneous_Networks_with_Programmable_Data_Planes.pdf

accesso aperto

Descrizione: accepted manuscript
: Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione 835 kB
Formato Adobe PDF
835 kB Adobe PDF Visualizza/Apri
Network_Function_Decomposition_and_Offloading_on_Heterogeneous_Networks_With_Programmable_Data_Planes (1).pdf

accesso aperto

Descrizione: publisher's version
: Publisher’s version
Dimensione 2.28 MB
Formato Adobe PDF
2.28 MB Adobe PDF Visualizza/Apri

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/11311/1182238
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 4
social impact