期刊文献+

基于网络处理器的多维IP分类算法 被引量:2

Multi-Dimensional IP Classification Based On Network Processor
在线阅读 下载PDF
导出
摘要 IP分类算法是提高网络设备性能的关键,无冲突规则集则是正确进行IP报文分类的前提和保证。网络处理器IntelIXP1200具有强大的可编程能力和并行分组处理能力。本文在IXP1200处理器平台上设计实现了一种无冲突的多维IP分类算法,用于保证当规则数量增加时,网络设备的数据分组转发仍能够保持正确和高速。 IP Classification algorithm is the key for improving the performance of network equipments, while conflict-free filters is the premise and can assure the correctness of the IP packet classification. With its programmable ability, the network processor Intel IXP1200 is particularly powerful in parallel packetprocessing. This paper describes the design and implementation of a conflict-free multi-dimensional IP classification algorithm based on IXP 1200 network processor, which has the special ability to keep a fast and correct transmission of the data packets under the boosting number of the rules.
出处 《微计算机信息》 北大核心 2005年第08X期55-57,共3页 Control & Automation
基金 河南省杰出人才创新基金(基于NP架构的高速安全平台技术研究)编号:0521000200
关键词 网络处理器 多维IP分类 规则冲突 并行 network processor, multi-dimensional IP classification, conflict-filter, parallel
  • 相关文献

参考文献3

  • 1Pankaj Gupta, Nick McKeown, "Algorithms for Packet Classification.".
  • 2Mohammad J. Rashti, H. R. R., Amir Foroutan, Meisam Lavasani. "A Multi-Dimensional Packet Classifier for NP-Based Firewalls.".
  • 3Adiseshu Hari, Subhash Suri, Guru Parulkar,"Detecting and Resolving Packet Filter Conflicts.".

同被引文献3

  • 1Dakshi Agrawal and Charu C.Aggarwal.On the design and quantification of privacy preserving data mining algorithms.In Proceedings of the 20th Symposium on Principles of Database Systems,Santa Barbara,California,USA,May 2001.
  • 2Wenliang Du and Zhijun Zhan.Using Randomized Response Techniques for Privacy-Preserving Data Mining.In Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery in Databases and Data Mining,Washington,DC,USA,August 24-27 2003.
  • 3Vassilios S.Verykios,Elisa Bertino,Igor Nai Fovino,Loredana Parasiliti Provenza,Yucel Saygin,Yannis Theodoridis.State -of -the-art in Privacy Preserving Data Mining.ACM SIGMOD Record,v.33 n.1,March 2004.

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部