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SIGCOMM
2010
ACM

EffiCuts: optimizing packet classification for memory and throughput

11 years 9 months ago
EffiCuts: optimizing packet classification for memory and throughput
Packet Classification is a key functionality provided by modern routers. Previous decision-tree algorithms, HiCuts and HyperCuts, cut the multi-dimensional rule space to separate a classifier's rules. Despite their optimizations, the algorithms incur considerable memory overhead due to two issues: (1) Many rules in a classifier overlap and the overlapping rules vary vastly in size, causing the algorithms' fine cuts for separating the small rules to replicate the large rules. (2) Because a classifier's rule-space density varies significantly, the algorithms' equi-sized cuts for separating the dense parts needlessly partition the sparse parts, resulting in many ineffectual nodes that hold only a few rules. We propose EffiCuts which employs four novel ideas: (1) Separable trees: To eliminate overlap among small and large rules, we separate all small and large rules. We define a subset of rules to be separable if all the rules are either small or large in each dimensio...
Balajee Vamanan, Gwendolyn Voskuilen, T. N. Vijayk
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where SIGCOMM
Authors Balajee Vamanan, Gwendolyn Voskuilen, T. N. Vijaykumar
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