scalable packet classification using hybrid and dynamic cuttings authors : wenjun li,xianfeng li...
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Scalable Packet Classification Using Hybrid andDynamic Cuttings
Authors : Wenjun Li ,Xianfeng Li Publisher :Engineering Lab on Intelligent Perception for Internet of Things (ELIP) Presenter : Kai-Hsun Li Date : 2014/12/24
Department of Computer Science and Information Engineering National Cheng Kung University, Taiwan R.O.C.
Introduction
Decision-tree based schemes are the most well-known solutions for packet classification.
HiCuts and HyperCuts, suffer from memory explosion problem.
EffiCuts , suffers from excessive memory accesses.
In this paper, propose HD-Cuts use hybrid and dynamic cuttings to improve memory accesses and performance simultaneously
National Cheng Kung University CSIE Computer & Internet Architecture Lab
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Observation
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Proposed Scheme(1/6)- Rule Set Partitioning(1/2)
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partition the rules into the following four subsets to separate large rules.
1) Subset_SA: rules with wildcard in SA.
2) Subset_DA: rules with wildcard in DA.
3) Subset_Small: rules with no wildcard in SA and DA.
4) Subset_Large: rules with wildcard in both SA and DA.
Proposed Scheme(2/6)- Rule Set Partitioning(2/2)
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thresh_large = 0.5
Subset_SA = {R1, R3, R5, R7, R9, R10, R13}
Proposed Scheme(2/6)- Rule Set Partitioning(2/2)
National Cheng Kung University CSIE Computer & Internet Architecture Lab
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thresh_large = 0.5
Subset_SA = {R1, R3, R5, R7, R9, R10, R13}
Subset_DA ={R2, R4, R6, R8}
Proposed Scheme(2/6)- Rule Set Partitioning(2/2)
National Cheng Kung University CSIE Computer & Internet Architecture Lab
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thresh_large = 0.5
Subset_SA = {R1, R3, R5, R7, R9, R10, R13}
Subset_DA ={R2, R4, R6, R8}
Subset_Small = {R11, R12}
Proposed Scheme(2/6)- Rule Set Partitioning(2/2)
National Cheng Kung University CSIE Computer & Internet Architecture Lab
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thresh_large = 0.5
Subset_SA = {R1, R3, R5, R7, R9, R10, R13}
Subset_DA ={R2, R4, R6, R8}
Subset_Small = {R11, R12}
Subset_Large = {R14}
Proposed Scheme(3/6)-Hybrid and Dynamic Cuttings (1/4)
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Subset_SA => step1. conduct HiCuts by considering SA、 DA. step2. if next cut is not “DA “ or rules in current node rules > binth
then extend to five field with HyperCut.
Subset_DA => step1. conduct HiCuts by considering SA、 DA. step2. if next cut is not “SA “
or rules in current node > binth then extend to five field with hypercut.
Subset_Small => step1.conduct HyperCuts by considering SA、 DA.step2.if rule replications become serious
or rules in current node rules > binth then extend to five field with HyperCut.
Subset_Large => HyperCut considering all five fields simultaneously.
Proposed Scheme(4/6)-Hybrid and Dynamic Cuttings (2/4)
National Cheng Kung University CSIE Computer & Internet Architecture Lab
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Subset_SA = {R1, R3, R5, R7, R9, R10, R13}
Proposed Scheme(5/6)-Hybrid and Dynamic Cuttings (3/4)
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Root(Hicuts)(DA_cuts:4)
Leaf 1R1
Leaf 2R3
Node 1R5,R7,R9,R13
Leaf 3R13
rules in current node rules > binth
=> extend to five field with hypercut
Proposed Scheme(6/6)-Hybrid and Dynamic Cuttings (4/4)
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Root(Hicuts)(DA_cuts:4)
Leaf 1R1
Leaf 2R3
Node 1(Hypercuts)(SA_cuts:1)(DA_cuts:1)(SP_cuts:2)(DP_cuts:2)(Port_cuts:1)
Leaf 3R13
Leaf 4R5
Leaf 5R7
Leaf 6R9
Leaf 7R10
Experiment Results(1/2)
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Total Memory for HiCuts, HyperCuts, EffiCuts and HD-Cuts(binth=8, thresh_large=0.05)
Experiment Results(2/2)
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Memory Access for HiCuts, HyperCuts, EffiCuts and HD-Cuts(binth=8, thresh_large=0.05)