Fast Packet Classification Using Multi-Dimensional Encoding

1. Fast Packet Classification Using Multi-Dimensional Encoding Author: Manfred Georg, Christoph Jechlitschek, Sergey Gorinsky Publisher:High Performance Switching and Routing, 2007 Presenter: Chun-Yi Li Date: 2008/11/12

2. Outline • Related Work • Bitmap intersection • Aggregated Bit Vector (ABV) • Bit Compression Algorithm (BCA) • Multi-Dimensional Encoding • Performance • Conclusion

3. Bitmap intersection P1: X2&Y4 ->0011 & 1111 =0011 P2: X4&Y4 ->1101 & 1111 =1101

4. Aggregated Bit Vector • Aggregation of bit vector - Aggregation tries to decrease the memory access time by adding ABV • Generates false matching. - Rule rearrangement. • Faster than bitmap intersection, but use more space.

5. Bit Compression Algorithm • Memory storage - θ(d.N.㏒N) • Require additional time for decompression

7. Bit Compression Algorithm

8. Introduction • New Coding Vector – Layer Coding Vectors(LCVs) • Memory storage - θ(L.N.㏒N) L : Number of collision-free rule set N : Number of rules

9. Layer Coding Vector • Find minimum collision-free sets • To minimize memory storage, the wildcards of X dimension are only stored in the LCV of Y dimension

10. P 4

11. Number Of Layer Analysis β : The probability that prefix PA is a prefix of prefix PB

12. Performance

13. Conclusion • Storage complexity Bitmap intersection - O(d N2) Multi-Dimensional Encoding - θ(L.N.㏒N) • Less memory than bitmap intersection and bit compression • Requires additional processing time for decoding, it still outperforms bitmap intersection, bit-compression and even ABV in terms of classification speed.