High Performance Packet Classificiation (HPPC)13 Feb 2007 For some time now I've been using the NF-HiPAC patch on the netfilter infrastructure, to optimize packet classification time in firewalls. But since 2 years or so, no update has been made to the code and I consider it orphaned.
Because I depend on such optimisation, I will try to bring it back to life or maybe even replace it and integrate it into netfilter. Before I can even attempt any of this, I need an understanding of the concept.
Some history is in order. NF-HiPac was developed by Michael Bellion (now working at Mara Systems) and Thomas Heinz [updated as of 20070330] as some sort of masters thesis. It is based on a paper by Anja Feldmann and S. Muthukrishnan called "Tradeoffs for Packet Classification". Anja Feldmann was a supervisor in the NF-HiPAC thesis.
After the code was developped, it was supposed to be integrated into the mainstream kernelcode. But I suspect this integration is troublesome for 2 reasons: NF-HiPAC completely replaces the iptables infrastructure in the kernel instead of adding to it, and the code is so huge that noone would want to dig through it.
Well then. First things first. I needed to read the thesis to get a look at what the concept was. But I can only get a copy of that thesis in Germany and that's too much effort. So instead, I read the underlying paper and started playing around with some ideas of my own. Once I get something working (that is decent enough...) I will go through the NF-HiPAC code and study the differences. Either the NF-HiPAC code is better than my code (or equally good), in which case I will at least understand that code, or it will be worse in which case I can replace it with my code.
The main concept I retained from the paper, was that each rule can be matched faster than it is done now. I'm not sure how it is done now, but I imagine that the rules are matched one by one. If the match fails, the next rule is processed. What is the problem with this ? Imagine you have 1000 rules, each with a match dictating some IP address as the source address of a packet. If the incoming packet doesn't match there is no need to try it 999 times more, it won't match any better those times.
So, to avoid unnecessary matching, I will build a (binary) tree of IP addresses. For every rule, I will take the source IP address and store it in the binary tree, together with the rule ID number.
When a packet comes in, I can quickly lookup it's source IP and retrieve all rules where this source IP would match on. Then, it's a matter of masking out everything that's not in my list of matching rules.
The list can be trimmed down even more by building a tree for destination IP (duh), source/destination port number, protocol number, interface ID, ... etc.
My first attempt went to trying to build an efficient binary tree to store IP addresses and IP networks (CIDR). Inspired by the paper, I built a binary tree with depth 32 (IPv4) which looks like this:
This example shows what the tree looks like for 100 randomly generated IP addresses.
The problem with this approach is pretty obvious: the tree is huge. It has useless filler nodes with only 1 child. If I want to lookup an IP address, I would need to do 32 matches. I can improve on that.
The second attempt will follow soon.