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Performance Evaluation
Volume 63, Issue 3, March 2006, Pages 175-194
P2P Computing Systems
 
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doi:10.1016/j.peva.2005.01.005    
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Copyright © 2005 Elsevier B.V. All rights reserved.

Performance of peer-to-peer networks: Service capacity and role of resource sharing policies

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Xiangying YangCorresponding Author Contact Information, E-mail The Corresponding Author and Gustavo de VecianaE-mail The Corresponding Author

ECE Department, University of Texas at Austin, Austin, TX 78712, USA


Available online 23 February 2005.

Abstract

In this paper we model and study the performance of peer-to-peer (P2P) file sharing systems in terms of their ‘service capacity’. We identify two regimes of interest: the transient and stationary regimes. We show that in both regimes, the performance of P2P systems exhibits a favorable scaling with the offered load. P2P systems achieve this by efficiently leveraging the service capacity of other peers, who possibly are concurrently downloading the same file. Therefore to improve the performance, it is important to design mechanisms to give peers incentives for sharing/cooperation. One approach is to introduce mechanisms for resource allocation that are ‘fair’, such that a peer's performance improves with his contributions. We find that some intuitive ‘fairness’ notions may unexpectedly lead to ‘unfair’ allocations, which do not provide the right incentives for peers. Thus, implementation of P2P systems may want to compromise the degree of ‘fairness’ in favor of maintaining system robustness and reducing overheads.

Keywords: Peer-to-peer; File sharing; Service capacity; Incentive; Fairness

Article Outline

1. Introduction
1.1. Related work and paper organization
2. Service capacity of P2P systems
2.1. Transient analysis of service capacity
2.1.1. Deterministic model
2.1.2. Branching process model
2.1.2.1. Basic branching process model
2.1.2.2. Service capacity has exponential growth under supercritical condition
2.1.2.3. Increased parallelism typically decreases the growth exponent
2.1.2.4. Parallel uploads improve transient capacity when peers are uncooperative
2.2. Stationary regime analysis of service capacity
2.3. Trace measurements
2.3.1. Transient growth in service capacity
2.3.2. Impact of offered load on average throughput performance
3. Fairness, incentives and their implications on performance
3.1. Notions of fairness in stationary regime
3.1.1. Global proportional fairness
3.1.2. Peerwise proportional fairness
3.1.3. var epsilon-Peerwise proportional fairness
3.2. How to improve incentives under traffic dynamics?
4. Conclusion
Appendix A. Appendix
References
Vitae





Part of this work was presented at IEEE INFOCOM 2004.


Corresponding Author Contact InformationCorresponding author. Tel.: +1 512 731 0175/471 1573; fax: +1 512 471 5532.

Performance Evaluation
Volume 63, Issue 3, March 2006, Pages 175-194
P2P Computing Systems
 
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