Scalable Packet Classification Using Bit Vector Aggregating and Folding
Name
MIT-LCS-TM-637.pdf
Size
119.69 KB
Format
Adobe PDF
Checksum (MD5)
2d630bcf0cefd4d9dc115e368ba98997
Author(s)
Li, Ji
Liu, Haiyang
Sollins, Karen
Date Issued
April 2003
Series/Report no.
MIT-LCS-TM-637
Abstract
Packet classification is a central function for a number of network applications, such as routing and firewalls. Most existing algorithms for packet classification scale poorly in either time or space when the database size grows. The scalable algorithm Aggregated Bit Vector (ABV) is an improvement on the Lucent bit vector scheme (BV), but has some limitations. Our algorithm, Aggregated and Folded Bit Vector (AFBV), seeks to reduce false matches while keeping the benefits of bit vector aggregation and avoiding rule rearrangement. It combines bit vector aggregation and folding to achieve this goal. Experiments showed that our algorithm outperforms both the BV and ABV schemes in synthetically generated databases.
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