If you have a need for thousands of rules, for example if you have a lot of clients or computers, all with different QoS specifications, you may find that the kernel spends a lot of time matching all those rules.

By default, all filters reside in one big chain which is matched in descending order of priority. If you have 1000 rules, 1000 checks may be needed to determine what to do with a packet.

Matching would go much quicker if you would have 256 chains with each four rules - if you could divide packets over those 256 chains, so that the right rule will be there.

Hashing makes this possible. Let's say you have 1024 cable modem customers in your network, with IP addresses ranging from 1.2.0.0 to 1.2.3.255, and each has to go in another bin, for example 'lite', 'regular' and 'premium'. You would then have 1024 rules like this:

# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.0.0 classid 1:1
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.0.1 classid 1:1
...
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.3.254 classid 1:3
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.3.255 classid 1:2

To speed this up, we can use the last part of the IP address as a 'hash key'. We then get 256 tables, the first of which looks like this:

# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.0.0 classid 1:1
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.1.0 classid 1:1
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.2.0 classid 1:3
# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.3.0 classid 1:2

The next one starts like this:

# tc filter add dev eth1 parent 1:0 protocol ip prio 100 match ip src \
1.2.0.1 classid 1:1
...

This way, only four checks are needed at most, two on average.

Configuration is pretty complicated, but very worth it by the time you have this many rules. First we make a filter root, then we create a table with 256 entries:

# tc filter add dev eth1 parent 1:0 prio 5 protocol ip u32
# tc filter add dev eth1 parent 1:0 prio 5 handle 2: protocol ip u32 divisor 256

Now we add some rules to entries in the created table:

# tc filter add dev eth1 protocol ip parent 1:0 prio 5 u32 ht 2:7b: \
match ip src 1.2.0.123 flowid 1:1
# tc filter add dev eth1 protocol ip parent 1:0 prio 5 u32 ht 2:7b: \
match ip src 1.2.1.123 flowid 1:2
# tc filter add dev eth1 protocol ip parent 1:0 prio 5 u32 ht 2:7b: \
match ip src 1.2.3.123 flowid 1:3
# tc filter add dev eth1 protocol ip parent 1:0 prio 5 u32 ht 2:7b: \
match ip src 1.2.4.123 flowid 1:2

This is entry 123, which contains matches for 1.2.0.123, 1.2.1.123, 1.2.2.123, 1.2.3.123, and sends them to 1:1, 1:2, 1:3 and 1:2 respectively. Note that we need to specify our hash bucket in hex, 0x7b is 123.

Next create a 'hashing filter' that directs traffic to the right entry in the hashing table:

# tc filter add dev eth1 protocol ip parent 1:0 prio 5 u32 ht 800:: \
match ip src 1.2.0.0/16 \
hashkey mask 0x000000ff at 12 \
link 2:

Ok, some numbers need explaining. The default hash table is called 800:: and all filtering starts there. Then we select the source address, which lives as position 12, 13, 14 and 15 in the IP header, and indicate that we are only interested in the last part. This will be sent to hash table 2:, which we created earlier.

It is quite complicated, but it does work in practice and performance will be staggering. Note that this example could be improved to the ideal case where each chain contains 1 filter!

Hashing filters for very fast massive filtering的更多相关文章

  1. 基于Fast Bilateral Filtering 算法的 High-Dynamic Range(HDR) 图像显示技术。

    一.引言 本人初次接触HDR方面的知识,有描述不正确的地方烦请见谅. 为方便文章描述,引用部分百度中的文章对HDR图像进行简单的描述. 高动态范围图像(High-Dynamic Range,简称HDR ...

  2. Tone Mapping算法系列一:基于Fast Bilateral Filtering 算法的 High-Dynamic Range(HDR) 图像显示技术。

    一.引言 本人初次接触HDR方面的知识,有描述不正确的地方烦请见谅. 为方便文章描述,引用部分百度中的文章对HDR图像进行简单的描述. 高动态范围图像(High-Dynamic Range,简称HDR ...

  3. Optimizing shaper — hashing filters (HTB)

    I have a very nice shaper in my linux box :-) How the configurator works — it’s another question, he ...

  4. 阅读Real-Time O(1) Bilateral Filtering 一文的相关感受。

    研究双边滤波有很长一段时间了,最近看了一篇Real-Time O(1) Bilateral Filtering的论文,标题很吸引人,就研读了一番,经过几天的攻读,基本已理解其思想,现将这一过程做一简单 ...

  5. 编写 capture filters

    编写 capture filters 如有转载,请在转载前给我提一些建议.谢谢. 百度查不到资料,为无能的百度搜索增加点营养的料. 读 http://www.n-cg.net/CaptureFilte ...

  6. Gradle Goodness: Copy Files with Filtering

    Gradle Goodness: Copy Files with Filtering Gradle's copy task is very powerful and includes filterin ...

  7. CV code references

    转:http://www.sigvc.org/bbs/thread-72-1-1.html 一.特征提取Feature Extraction:   SIFT [1] [Demo program][SI ...

  8. CV codes代码分类整理合集 《转》

    from:http://www.sigvc.org/bbs/thread-72-1-1.html 一.特征提取Feature Extraction:   SIFT [1] [Demo program] ...

  9. [转]awsome c++

    原文链接 Awesome C++ A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny th ...

随机推荐

  1. 部署步骤“回收 IIS 应用程序池”中出现错误: <nativehr>0x80070005</nativehr><nativestack></nativestack>拒绝访问。

    解决方法:以sharepoint管理员身份进入主站点,修改站点的网站集管理员.

  2. ubuntu 设置静态ip

    1. 为网卡配置静态IP地址 编辑文件/etc/network/interfaces: sudo vi /etc/network/interfaces 并用下面的行来替换有关eth0的行: # The ...

  3. getParamValues()

    http://blog.csdn.net/msg_java2011/article/details/6529226

  4. bzoj 2456: mode

    #include<cstdio> #include<algorithm> using namespace std; int n,t,sum; int main() { scan ...

  5. 精通JS 笔记

    一,javascript数据类型:undefined,null,boolean,number,string,object 五种加一种复杂类型. 注意大小写,区分大不写函数:functiontypeof ...

  6. 关于oc运行时 isa指针详解

    Cocoa框架是iOS应用程序的基础,了解Cocoa框架,对开发iOS应用有很大的帮助. 1.Cocoa是什么? Cocoa是OS X和 iOS操作系统的程序的运行环境. 是什么因素使一个程序成为Co ...

  7. PL/SQL

    function & procedure packages function --> arguments or parameters with arguments, IN, read o ...

  8. jquery api调用

    本框架内置组件以及部分插件都可以通过jquery选择器进行API调用,支持链式操作,如下示例. <script type="text/javascript"> $(&q ...

  9. Java 多线程间的通讯

    在前一小节,介绍了在多线程编程中使用同步机制的重要性,并学会了如何实现同步的方法来正确地访问共享资源.这些线程之间的关系是平等的,彼此之间并不存在任何依赖,它们各自竞争CPU资源,互不相让,并且还无条 ...

  10. JVM-类文件结构

    无关性的基石 I> "平台无关性"实现在操作系统的应用层上:sun公司以及其他虚拟机提供商发布了许多可以运行在各种不同平台上的虚拟机,这些虚拟机都可以载入和执行同一种平台无关 ...