I am part of the group of students working with the Debian organization. You can see my profile on the Debian wiki here.
Improving distributed and secure communication using free software
This the title of my project for this summer. It sounds good, but what am I going to really do? Well, since I’m a student at Université du Québec à Montréal, I have had the opportunity to meet with the company Savoir-Faire Linux in Montreal last year and that’s when I found out about their exciting project: Ring.
Ring is one of the few projects which bring communication confidentiality and freedom in the hands of the users.
Ring is divided in multiple components as explained here: https://ring.cx/en/about/technical. The component I work on is called OpenDHT. This is the distributed hash table which enables Ring users to communicate in a decentralized network.
I have already been working on this project for a year now, so you won’t see me posting reports where I say I have to find my way around in this project. In fact, I have contributed to rewriting a major part of the code for better maintainability.
In the begining of last summer, I was able to be part of a research association between Savoir-Faire Linux and Université du Québec à Montréal. We have been working on adding two major features to OpenDHT.
Short introduction to Distributed Hash Tables
OpenDHT is based on the Kademlia design. If you know about DHTs, you are
aware that they define the notion of distance using the XOR metric. This
makes the tuple
(H_n, xor) a metric space, where
H_n is the space of
identifier keys of length
n. This way, you can find an identifier be the
closest to a target hash than the rest of the nodes in the network.
In order to find some data that is associated with some hash
h, you have to
find the nodes in the network for which the distance between their hash
identifier and the target hash
h is minimized. The group of nodes which are
the closest to the target hash (OpenDHT allows up to 8 nodes) will hold data for
Let’s say you ask a group of 8 nodes to hold some data for a hash and you want the data to hold the whole time until its expiration time as come. If the group of 8 nodes change because that for some reason those nodes leave or others just arrive and have an id that is closer to the target hash than the initial group of 8 nodes. The data would then not be found on the new group of 8 nodes. A first and simple solution was to count on the initial creator of the value to periodically announce the value to the group of 8 nodes. However, what if this node leaves? This is one of the main problem that I’ve been working on solving since 2015. A first version of this was produced on September 2015. However, we experienced traffic issues and were forced to redesign the OpenDHT network requests engine. We are presently working on adding a Query feature that would enable filtering of data on remote nodes, hence substantially lowering the overall traffic produced by a response to a ‘get’ request.
During the last year, I have also been working on the design of a solution for the use case of indexation. In a more technical way, this is the capability to find data by providing a map where its key is a string field and the mapped value is the value associated to that field, much like in a form. This could help find data for which you don’t know the hash, but you have specific information about its content. In other words, this would be a search engine for OpenDHT. I have already created a working, but still in progress, version of this. You can find it on http://opendht.net, on the index branch. Now, Nicolas Reynaud (kaldoran) is contributing to this during the GSOC.
As I explained on my page on the Debian Wiki, I am going to work on:
- Developing new functionalities in OpenDHT aiming at reducing overall generated traffic.
- Maintenance and optimization of the OpenDHT code in general.
- Optimizing data persistence solution over the distributed hash table.
- Merge (1) in the Ring daemon component in order to benefit from lower traffic in Ring.
- Make OpenDHT use TCP protocol instead of UDP. This is going to reduce code complexity and enhance robsutness of the DHT.
For further details, read my reports!