Please use this identifier to cite or link to this item:
Title: Performance analysis of BitTorrent-like systems with heterogeneous users
Authors: Psounis, Konstantinos
Liao, Wei Cherng 
Papadopoulos, Fragkiskos 
Keywords: BitTorrent | Fairness/delay tradeoff | P2P networks | Performance analysis | Token-based scheme
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: 1-Oct-2007
Source: Performance Evaluation, Volume 64, Issues 9–12, October 2007, Pages 876-891
Journal: Performance Evaluation 
Abstract: Among all peer-to-peer (P2P) systems, BitTorrent seems to be the most prevalent one. This success has drawn a great deal of research interest on the system. In particular, there have been many lines of research studying its scalability, performance, efficiency, and fairness. However, despite the large body of work, there has been no attempt mathematically to model, in a heterogeneous (and hence realistic) environment, what is perhaps the most important performance metric from an end user's point of view: the average file download delay. In this paper we propose a mathematical model that accurately predicts the average file download delay in a heterogeneous BitTorrent-like system. Our model is quite general, has been derived with minimal assumptions, and requires minimal system information. Then, we propose a flexible token-based scheme for BitTorrent-like systems that can be used to tradeoff between overall system performance and fairness to high bandwidth users, by properly setting its parameters. We extend our mathematical model to predict the average file download delays in the token- based system, and demonstrate how this model can be used to decide on the scheme's parameters that achieve a target performance/fairness. © 2007 Elsevier Ltd. All rights reserved.
ISSN: 0166-5316
DOI: 10.1016/j.peva.2007.06.008
Type: Article
Appears in Collections:Άρθρα/Articles

Show full item record


checked on Oct 13, 2019


checked on Oct 16, 2019

Page view(s)

Last Week
Last month
checked on Oct 18, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.