Open AccessWildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns
Author(s) -
Hamed Khanmirza
Publication year - 2022
Publication title -
peerj. computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.806
H-Index - 24
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.809
Subject(s) - computer science , software defined networking , network packet , computer network , distributed computing , network topology , set (abstract data type) , software , operating system , programming language
Software-defined networking (SDN) enables fast service innovations through network programmability. In SDN, a logically centralized controller compiles a set of policies into the network-level rules. These rules are inserted in the TCAM memory of SDN-enabled switches enabling high-speed matching and forwarding of packets. Unfortunately, TCAMs are available in limited capacities and fall short of accommodating all intended rules, especially in networks with large distinct flows like datacenters. Rule compression is a technique that reduces the number of rules by aggregating them with some similarity factors. This paper introduces WildMinnie, a new rule compression method that aggregates rules based on their common address non-prefix wildcards derived from a group of rules with the same output port number. We explore rule conflict issues and provide solutions to resolve them. We demonstrate the capability of WildMinnie in various datacenter topologies with traffics having different diversity of source-destination addresses and show that WildMinnie outperforms the best-known compression method by 20%, on average.