1. ClassBench: A Packet Classification Benchmark
David E. Taylor, Jonathan S. Turner
Washington University in Saint Louis
Presented by Jian-Meng Yang

2. [Figure from Professor Jonathan Chao’s book]
Background
Packet classification is an enabling technology
A classifier example (5 tuples)
[Figure from Professor Jonathan Chao’s book]

3. Background
A packet classifier must compare header fields of every incoming packet
To accelerate search time or reduce storage requirements
No standard performance evaluation tools
ClassBench is presented !

4. ClassBench
A suite of tools for benchmarking packet classification algorithms and devices.
Consists of three tools:
Filter Set Analyzer
Filter Set Generator
Trace Generator

5. ClassBench Architecture
General approach
Construct a set of benchmark parameter files
Generate a synthetic filter set
Generate a sequence of packet headers

6. Analysis of Seed Filter Sets
Understanding Filter Composition
We can view a filter as having two major components:
An address prefix pair
An application specification
Address prefix pair
Identifies the communicating subnets by specifying a source address prefix and a destination address prefix.

7. Analysis of Seed Filter Sets
Application Specification
Identifies a specific application session by specifying the transport protocol, source port number, and destination port number.
Address prefix pair
The speed and efficiency of several longest prefix matching and packet classification algorithms depend upon
The number of unique prefix lengths
The distribution of filters across those unique values.

8. Analysis of Seed Filter Sets
The number of unique prefix lengths
acl: access control list
fw: firewall
ipc: IP chain

9. Analysis of Seed Filter Sets
The distribution of filters across those unique values
Real filter sets have unique prefix pair distributions that reflect the types of filters contained in the filter set.
acl5:

10. Analysis of Seed Filter Sets
2 Distributions to facilitate construction of synthetic filter sets that accurately model seed filter sets:
Branching Probability Distribution
For each level in the tree, we compute the probability that a node has one child or two children.
Skew Distribution
For nodes with TWO children, we compute skew, which is a relative measure of the “weights” of the left and right subtrees of the node.
Weight: The number of filters specifying prefixes
in the subtree

11. Analysis of Seed Filter Sets
Skew Distribution L
heavy be the subtree with the largest weight
light be the subtree with equal or less weight
The Black nodes denote a prefix specified by a single filter.
The subtrees denoted
by triangles with associated weight.

12. Analysis of Seed Filter Sets
Branching Probability
Distribution
Skew Distribution

13. Analysis of Seed Filter Sets
Application Specification
3 useful characteristics
Protocol:

14. Analysis of Seed Filter Sets
Port Ranges
WC, wildcard
HI, ephemeral user port range [1024 : 65535]
LO, well-known system port range [0 : 1023]
AR, arbitrary range
EM, exact match
Port Pair Class
The structure of source and destination port range pairs is a key point of interest for both modeling real filter sets and designing efficient search algorithms.

15. Parameter Files
Given a seed filter set, the Filter Set Analyzer generates a parameter file.
Parameter files contain
Statistics and probability distributions that allow the Filter Set Generator to produce a synthetic filter set.

16. Parameter Files Parameter files includes
Protocol specifications and the distribution of filters over those values.
Port Pair Class Matrix
Prefix pair length

17. Synthetic Filter Set Generator
High-level input parameters
size: Target size for the synthetic filter set.
smoothing: Controls the number of new
address aggregates.
Scope: The measure of the number of
possible packet headers covered by
the filter.

18. Trace Generator
Benchmarking a particular packet classification algorithm or device
We must exercise the algorithm or device using a sequence of synthetic packet headers.

19. Comment
It provides the network research scientists a good tool for evaluating their packet classifier performance.
No information about how to get or generate the Seed filter set.
How about the exceptions?