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  5. An Analysis of BitTorrent Cross-Swarm Peer Participation and Geolocational Distribution
 
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An Analysis of BitTorrent Cross-Swarm Peer Participation and Geolocational Distribution

Author(s)
Scanlon, Mark  
Shen, Huijie  
Uri
http://hdl.handle.net/10197/7680
Date Issued
2014-08-07
Date Available
2016-06-21T15:53:48Z
Abstract
Peer-to-Peer (P2P) file-sharing is becoming increasingly popular in recent years. In 2012, it was reported that P2P traffic consumed over 5,374 petabytes per month, which accounted for approximately 20.5% of consumer internet traffic. TV is the popular content type on The Pirate Bay (the world's largest BitTorrent indexing website). In this paper, an analysis of the swarms of the most popular pirated TV shows is conducted. The purpose of this data gathering exercise is to enumerate the peer distribution at different geolocational levels, to measure the temporal trend of the swarm and to discover the amount of cross-swarm peer participation. Snapshots containing peer related information involved in the unauthorised distribution of this content were collected at a high frequency resulting in a more accurate landscape of the total involvement. The volume of data collected throughout the monitoring of the network exceeded 2 terabytes. The presented analysis and the results presented can aid in network usage prediction, bandwidth provisioning and future network design.
Type of Material
Conference Publication
Publisher
IEEE
Start Page
1
End Page
6
Copyright (Published Version)
2014 IEEE
Subjects

BitTorrent

Piracy

Swarm analysis

DOI
10.1109/ICCCN.2014.6911846
Language
English
Status of Item
Peer reviewed
Conference Details
The First International Workshop on Hot Topics in Big Data and Networking (HotData I) in conjunction with the 23rd IEEE International Conference on Computer Communications and Networks (ICCCN), Shanghai, China, 7 August 2014
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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AnAnalysisOfBitTorrentCrossSwarmPeerParticipation.pdf

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Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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