1. ABC : Adaptive Binary Cuttings for Multidimensional Packet Classification
Publisher : TRANSACTIONS ON NETWORKING Author : Haoyu Song, Jonathan S. Turner Presenter : Yu-Hsiang Wang Date : 2012/05/09

2. Outline Observations Algorithm Description Algorithm Optimizations
Performance Evaluation

3. Observations
In HiCuts and HyperCuts, a global expansion factor may not be suitable for all nodes. Bucket Size cannot guarantee either throughput or storage.
Our goal is to make the “optimal” decisions that consistently improve the throughput until the given storage is used up.

4. Algorithm Description
DT : Decision Tree
CST : Cutting Shape Tree
CSB : Encode each CST with a Cutting Shape Bitmap.

5. Algorithm Description
ABC Variation I
The maximum number of cuttings is constrained by the DT node size.
Choose one of the subregions produced so far and split it into two equal-sized subregions along a certain dimension until we run out of space in the DT node.

6. Algorithm Description
preference value :

7. Algorithm Description
If the current number of leaf nodes is less than k, we choose one leaf node to cut on a specific dimension.
Our goal is to find the leaf node i and the dimension d that can minimize the preference value.

8. Algorithm Description
i : current index in CSB j: the current index in CDV. Next index i’ in CSB is Next index j’ in CDV is

9. Algorithm Description
ABC Variation II
Generate up to D separate CSTs, each for one dimension.

10. Algorithm Description
ABC Variation III
Any bit can be chosen to split the filter set
Assume DT size = 128 bits
ABC Variation I = 22 cuts
ABC Variation III = 13 cuts

11. Algorithm Description

12. Algorithm Description

13. Algorithm Optimizations
Reduce Filters Using a Hash Table.
Filter Partition on the Protocol Field.
Partitioning Filters Based on Duplication Factor.
Holding Filters Internally and Reversing Search Order.

14. Performance Evaluation
Performance : bytes retrieved per lookup
Scalability on Filter Set Size

15. Performance Evaluation

16. Performance Evaluation

17. Performance Evaluation