排序方式: 共有86条查询结果,搜索用时 46 毫秒
1.
在三态内容寻址存储器(Ternary Content Addressable Memory, TCAM)表项宽度和存储容量约束下,该文提出一种基于匹配表项压缩的BF-TCAM算法,采用Bloom-Filter(BF)对匹配关键字进行单字节编码压缩关键字长度,解决了匹配吞吐率低和存储空间不足问题。针对BF在表项压缩过程带来的冲突率上升问题,引入向量存储空间策略,利用向量存储空间实现多个哈希函数映射,相对于比特向量策略,有利于降低匹配冲突率。测试实验表明,相对于传统的TCAM匹配算法,BF-TCAM算法不但提高了匹配吞吐率和存储空间利用率,同时可有效降低BF压缩产生的冲突率。 相似文献
2.
3.
针对基于硬件的模式匹配算法处理长模式串时吞吐率不高的问题,提出了基于将哈希压缩与TCAM查表相结合的算法——HASH-TCAM算法。通过哈希算法将待匹配的关键字预处理,减少其长度,解决了40 Gbps线速下的长模式串匹配问题,并通过40 Gbps测试仪验证了该算法的可行性。分析表明,该算法在查询的固定关键字长度为72 Byte,模式集数目为5000,哈希压缩后地址的编码宽度为46 bit时,模式识别模块以牺牲冲突的代价实现了51.2 Gbps的吞吐率,可以满足40 Gbps链路中DPI算法的逐包线速的需求 相似文献
4.
5.
6.
7.
The survivability of the future Internet is largely dependent on whether it will be able to successfully address both security and performance issues facing the Internet. On one hand, the Internet becomes more and more vulnerable due to fast spreading malicious attacks. On the other hand, it is under great stress to meet ever growing/changing application demands while having to sustain multi-gigabit forwarding performance. In this paper, we propose a Ternary Content Addressable Memory (TCAM) coprocessor based solution for high speed, integrated TCP flow anomaly detection and policy filtering. The attacking packets with spoofed source IP addresses are detected through two-dimensional (2D) matching. The key features of the solution are: (1) setting flag bits in TCAM action code to support various packet treatments; (2) managing TCP flow state in pair to do 2D matching. We evaluate the solution’s ability to detect TCP-based flooding attacks based on real-world-trace simulations. The results show that the proposed solution can match up OC-192 line rate. The possible modifications of the solution for the detection of low rate TCP-targeted attacks are also discussed. 相似文献
8.
9.
10.