Combined stateful classification and session splicing for high-speed NFV service chaining
2021 (English)In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566, Vol. 29, no 6, p. 2560-2573Article in journal (Refereed) Published
Abstract [en]
Network functions such as firewalls, NAT, DPI, content-aware optimizers, and load-balancers are increasingly realized as software to reduce costs and enable outsourcing. To meet performance requirements these virtual network functions (VNFs) often bypass the kernel and use their own user-space networking stack. A naïve realization of a chain of VNFs will exchange raw packets, leading to many redundant operations, wasting resources. In this work, we design a system to execute a pipeline of VNFs. We provide the user facilities to define (i) a traffic class of interest for the VNF, (ii) a session to group the packets (such as the TCP 4-tuple), and (iii) the amount of space per session. The system synthesizes a classifier and builds an efficient flow table that when possible will automatically be partially offloaded and accelerated by the network interface. We utilize an abstract view of flows to support seamless inspection and modification of the content of any flow (such as TCP or HTTP). By applying only surgical modifications to the protocol headers, we avoid the need for a complex, hard-to-maintain user-space TCP stack and can chain multiple VNFs without re-constructing the stream multiple times, allowing up to 5x improvement over standard approaches.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. Vol. 29, no 6, p. 2560-2573
Keywords [en]
Middleboxes, Protocols, Monitoring, Software, Payloads, Technological innovation, Splicing, Computer networks, network function virtualization, internet, middleboxes
National Category
Communication Systems Computer Systems
Research subject
Telecommunication; Information and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-299200DOI: 10.1109/TNET.2021.3099240ISI: 000731147300017Scopus ID: 2-s2.0-85112647277OAI: oai:DiVA.org:kth-299200DiVA, id: diva2:1582880
Projects
ePIULTRA
Funder
European Commission, 770889
Note
QC 20250429
2021-08-042021-08-042025-04-29Bibliographically approved