Scalable Packet Classification Using Bit Vector Aggregating and Folding
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...
| Main Authors: | , , |
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| Published: |
2023
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| Online Access: | https://hdl.handle.net/1721.1/149324 |
| _version_ | 1826194489804324864 |
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| author | Li, Ji Liu, Haiyang Sollins, Karen |
| author_facet | Li, Ji Liu, Haiyang Sollins, Karen |
| author_sort | Li, Ji |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T09:56:53Z |
| id | mit-1721.1/149324 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:56:53Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | mit-1721.1/1493242023-03-30T04:06:26Z Scalable Packet Classification Using Bit Vector Aggregating and Folding Li, Ji Liu, Haiyang Sollins, Karen 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. 2023-03-29T14:43:10Z 2023-03-29T14:43:10Z 2003-04 https://hdl.handle.net/1721.1/149324 MIT-LCS-TM-637 application/pdf |
| spellingShingle | Li, Ji Liu, Haiyang Sollins, Karen Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title | Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title_full | Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title_fullStr | Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title_full_unstemmed | Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title_short | Scalable Packet Classification Using Bit Vector Aggregating and Folding |
| title_sort | scalable packet classification using bit vector aggregating and folding |
| url | https://hdl.handle.net/1721.1/149324 |
| work_keys_str_mv | AT liji scalablepacketclassificationusingbitvectoraggregatingandfolding AT liuhaiyang scalablepacketclassificationusingbitvectoraggregatingandfolding AT sollinskaren scalablepacketclassificationusingbitvectoraggregatingandfolding |