A Fast, Smart Packet Classification Algorithm Based on Decomposition. (15th October 2020)
- Record Type:
- Journal Article
- Title:
- A Fast, Smart Packet Classification Algorithm Based on Decomposition. (15th October 2020)
- Main Title:
- A Fast, Smart Packet Classification Algorithm Based on Decomposition
- Authors:
- Li, Chuanhong
Zeng, Xuewen
Song, Lei
Jiang, Yan - Other Names:
- Morinigo-Sotelo Daniel Academic Editor.
- Abstract:
- Abstract : Packet classification algorithms have been the focus of research for the last few years, due to the vital role they play in various services based on packet forwarding. However, as the number of rules in the rule set increases, not only the preprocessing time but also the memory consumption is increasing greatly. In this paper, we first model and analyze the above issue in depth. Then, a fast, smart packet classification algorithm based on decomposition is proposed. By boundary-based rule traversal and smart rule set partitioning, both the preprocessing time and memory consumption are reduced dramatically. Experimental results show that the preprocessing time of our method achieves 8.8-time improvement at maximum compared with the PCIU and achieves about 31.5-time improvement on average compared with CutSplit for large rule sets. Meanwhile, the memory overhead is reduced by 40% at maximum and 27.5% on average compared with the PCIU.
- Is Part Of:
- Journal of control science and engineering. Volume 2020(2020)
- Journal:
- Journal of control science and engineering
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10-15
- Subjects:
- Control theory -- Periodicals
629.831205 - Journal URLs:
- https://www.hindawi.com/journals/jcse/ ↗
- DOI:
- 10.1155/2020/8843471 ↗
- Languages:
- English
- ISSNs:
- 1687-5249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14766.xml