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Offloading Virtual Network Functions – Hierarchical Approach
Karlstad University.
2020 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Next generation mobile networks are designed to run in a virtualized environment, enabling rapid infrastructure deployment and high flexibility for coping with increasing traffic demands and new service requirements. Such network function virtualization imposes additional packet latencies and potential bottlenecks not present in legacy network equipment when run on dedicated hardware; such bottlenecks include PCIe transfer delays, virtualization overhead, and utilizing commodity server hardware which is not optimized for packet processing operations.Through recent developments in P4 programmable networking devices, it is possible to implement complex packet processing pipelines directly in the network data plane; allowing critical traffic flows to be offloaded and flexibly hardware accelerated on new programmable packet processing hardware, prior to entering the virtualized environment.In this thesis, we design and implement a novel hybrid NFV processing architecture which integrates programmable NICs and commodity server hardware, capable of offloading virtual network functions for specified traffic flows directly to the server network card; allowing these flows to completely bypass softwarization overhead, while less sensitive traffic process on the underlying host server.An evaluation in a testbed with customized traffic generators show that accelerated flows have significantly lower jitter and latency, compared with flows processed on commodity server hardware. Our evaluation gives important insights into the designs of such hardware accelerated virtual network deployments, showing that hybrid network architectures are a viable solution for enabling infrastructure scalability without sacrificing critical flow performance.

Place, publisher, year, edition, pages
2020. , p. 68
Keywords [en]
vnf, hardware acceleration, 5g, nfv, smartnic, offloading
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kau:diva-79090OAI: oai:DiVA.org:kau-79090DiVA, id: diva2:1453437
Presentation
2020-06-15, 21E415A, 09:57 (English)
Supervisors
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Available from: 2020-12-01 Created: 2020-07-10 Last updated: 2020-12-01Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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