End-to-end Publishing Using Bittorrent

Bittorrent Bittorrent is a widely used peer-to- peer network used to distribute files, especially large ones It has a number of legal uses which separate it from other P2P

Practical Applications Distributing large files Podcasting Vlogging Disk images Legal distribution of movies (see bittorrent.com)

Traditional vs. Bittorrent One server provides many clients Many clients provide many clients

Terminology Swarm – clients downloading or uploading a given file through BIttorrent Tracker – centralized server that clients connect to to ask for lists of other clients connected to the swarm Seed – A client that has a complete copy of the file Peer (Leecher) – A client that does not have a complete copy of the file

Problem Torrents that are less popular may eventually “die” when there are no longer any complete copies of the file in the swarm

Everseed Permanent seed running on the same server as the tracker Guarantees that there will always be a complete copy of the file

Related Research The creator of Bittorrent wrote a paper on the process of downloading a file using Bittorrent at Maintainers of various Bittorrent clients wrote which is like the official specification except far more in depth Osprey ( seems to have thought of something similar, but haven't made any visible progresshttp://osprey.ibiblio.org/

Explanation The.torrent metadata file provides info about where to find the tracker and about the file being distributed Client connects to tracker Tracker gives client a list of other clients Client then downloads file from other clients (not a centralized server) Periodic update with tracker for new client list

Goals Complete internet publishing solution using Bittorrent Metadata file generator (.torrent) Tracker “Everseed” Web interface

.torrent File Official documention on bittorrent.org Metadata on the file to be downloaded (tracker URL, filename, size, checksum hashes) Stored as “bencoded” strings, integers, lists, dictionaries

Bencoding Integer: 6 => “i6e” String: “hello” => “5:hello” List: [“hello”,”world”] => “l5:hello5:worlde” Dictionary: {“hello”:”world”} => “d5:hello5:worlde”

Bencoding implementation Python, good string manipulation Structure of a.torrent file is a dictionary containing string keys and integer, string, list, and dictionary values Recursion to encode/decode

Tracker Makes use of the bencoding algorithm Handles two types of requests: “announce” and “scrape” Stores data on peers and torrents in a SQLite database No performance issues

Network performance Peer List Size

Database performance

Announce requests Used by a client to announce presence in a Bittorrent swarm Client sends an HTTP GET request to the announce URL in the.torrent file Tracker parses request, urldecodes data about the peer Tracker stores data in the database, sends appropriate response as bencoded string in a text/plain document Client bdecodes string, connects to other clients

Scrape requests Used by client to obtain info about the torrents the tracker is tracking Client sends an HTTP GET request to the scrape url found by transforming the announce url Tracker urldecodes and parses the request Tracker fetches data about torrent from the database Tracker returns a bencoded dictionary which the client decodes

Smart Peer List Response Seeds often disconnect from other seeds Tracker can also do this to some extent Announce requests contain a list of random peers If a client is seeding, it doesn't need IPs of other seeds Increased overall swarm performance

Peer List Compression Peer list in the tracker response to peer lists is normally ASCII encoded The peer list can be compressed to 4 bytes for the IP address, 2 bytes for the port Huge bandwidth savings, ~80% Greatly enhanced tracker performance Reduced tracker hardware requirements

Test Client Concurrent development of a test Bittorrent client written in Python Can send both announce and scrape requests Key-value pairs are easily configurable

Testing Generalized method of handling exceptions in the initialization methods Increased use of try/except statements to improve robustness Testing with incorrect or missing data

Summary Python Benefits of P2P technology “Everseed” concept.torrent files and bencoding Tracker