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Packet Classification on Multiple Fields 참고 논문 : Pankaj Gupta and Nick McKeown SigComm 1999.

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Presentation on theme: "Packet Classification on Multiple Fields 참고 논문 : Pankaj Gupta and Nick McKeown SigComm 1999."— Presentation transcript:

1 Packet Classification on Multiple Fields 참고 논문 : Pankaj Gupta and Nick McKeown SigComm 1999

2 2 IP Lookup Longest-prefix address lookup Rule: Each Prefix Action: Next hop Classifier: Forwarding table

3 3 Outline Packet Classification Application, Information, Characteristics Design Goal Previous Work Recursive Flow Classification (RFC)

4 4 Packet classification (Application) Packet Filtering Deny all traffic from ISP3 destined to E2 Accounting & Billing Treat all video traffic to E1 as highest priority and perform accounting for the traffic sent this way

5 5 Packet classification (Application)

6 6 Packet Header http://vulcan.ee.iastate.edu/~dougj/class/580/index.htm

7 7 Example

8 8 Example (Cont.)

9 9 Definition of Packet Classification Each rule Specifies a class Based on criterion on F fields Associates with an identifier, classID i-th component of the rule R, R[i]  A regular expression on the i-th filed of the packet header

10 10 Characteristics of P-C 793 packet classifiers 101 different ISP and enterprise networks Total 41505 rules ? Data representative? Conclusion: Trivial or non-trivial?

11 11 Distribution of total number of rules per classifier

12 12 Characteristics 1 The classifiers do not contain a large number of rules. 0.7% of the classifiers contain more than 1000 rules Mean number: 50 rules

13 13 Characteristics 2 The syntax allows a maximum of 8 fields to be specified: Source/destination Network-Layer address(32-bits) Source/destination Transport-layer port number(16-bits for TCP/UDP) Type-of-service field(8-bits) Protocol field (8-bits) Transport-Layer protocol flags(8-bits)

14 14 Characteristics 3-4 Transport-Layer protocol field is restricted to a small set of values: TCP, UDP, ICMP, IGMP, (E)IGRP, GRE and IPINIP or wildcard Transport-layer fields Many (10.2%) are range specifications

15 15 Characteristics 5-6 14% of all the classifiers had a rule with a non-contiguous mask. Many different rules share a number of field specifications.

16 16 Characteristics 7 Redundant Backward redundancy  Rule T appears earlier than Rule R, and R is a subset of T. Forward redundancy  Rule T apperas after R R is a subset of T R, T have the same action Rules inbetween R and T The same action Disjoint from R. 8% of the rules were redundant.

17 17 Goals Fast enough Matching on arbitrary fields Support general classification rules Prefixes, operators(like range, less than, greater than…) and wildcards. Suitable for software and hardware implementation Memory efficient Scalability For steady classifier

18 18 Previous Work Sequential evaluations Grid of Tries Crossproducting Bit-level parallelism TCAM

19 19 Abstract The point location problem in multidimensional space Find the enclosing region of a point, given a set of regions. Complexity O(logn) in time with O(n F ) space O(log F-1 n) time with O(n) space

20 20 Structure of classifiers

21 21 Overlapping is small For the biggest classifier with 1734 rules, the number of distinct overlapping regions in four dimensions to be 4316, compared to a worst possible case of approximately 10 13.

22 22 Recursive Flow Classification

23 23 Chunks of Packet header

24 24 Packet flow in RFC

25 25 Phase number =3

26 26 Phase number =4

27 27 Select Phase number Combine those chunks together which have the most “correlation”. Combine as many chunks as possible without causing unreasonable memory consumption. Best case: P=3 Tree B P=4 Tree A

28 28 Performance (Storage requirement for P=2)

29 29 Performance (Storage requirement for P=3)

30 30 Performance (Storage requirement for P=4)

31 31 Preprocess Time

32 32 Hardware implementation

33 33 Larger classifiers I Concatenating the classifiers belonging to the same network.

34 34 Larger classifiers II Concatenate all the classifiers of a few (up to ten) different networks. RFC frequently runs into storage problems for classifiers with more than 6000 rules.

35 35 Variations Process a larger number of fields in each packet header. Use available fast lookup algorithms Use Adjacency group

36 36 Adjacency Groups Two rules (R, S)are considered adjacent R appears first The same Action All but one field have the same specification All rules in between R and S  Either have the same action  Disjoint from R

37 37 An example

38 38 Storage (Adjacency groups)

39 39 Comments Trade off? Memory, Speed, Dynamic Change, etc Application and Demand oriented Further discussion? scai@ecs.umass.edu Thank you!


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