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Analyzing peer-to-peer traffic across large networks

Authors:

Subhabrata Sen,

Jia WangAuthors Info & Claims

IEEE/ACM Transactions on Networking (TON), Volume 12, Issue 2

Pages 219 - 232

https://doi.org/10.1109/TNET.2004.826277

Published: 01 April 2004 Publication History

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Abstract

The use of peer-to-peer (P2P) applications is growing dramatically, particularly for sharing large video/audio files and software. In this paper, we analyze P2P traffic by measuring flow-level information collected at multiple border routers across a large ISP network, and report our investigation of three popular P2P systems--FastTrack, Gnutella, and Direct-Connect. We characterize the P2P trafffic observed at a single ISP and its impact on the underlying network. We observe very skewed distribution in the traffic across the network at different levels of spatial aggregation (IP, prefix, AS). All three P2P systems exhibit significant dynamics at short time scale and particularly at the IP address level. Still, the fraction of P2P traffic contributed by each prefix is more stable than the corresponding distribution of either Web traffic or overall traffic. The high volume and good stability properties of P2P traffic suggests that the P2P workload is a good candidate for being managed via application-specific layer-3 traffic engineering in an ISP's network.

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Mills GPomary PTogo ESowah R(2022)Detection and Management of P2P Traffic in Networks using Artificial Neural NetworksaJournal of Network and Systems Management10.1007/s10922-021-09637-130:2Online publication date: 1-Apr-2022
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Analyzing peer-to-peer traffic across large networks

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Reviews

Reviewer: Dimitrios I Kagklis

This paper analyzes peer-to-peer (P2P) traffic on a real-life, large Internet service provider (ISP) network, by examining three of the most popular P2P applications: FastTrack, Gnutella, and Direct-Connect. It studies traffic generated by both signaling and data transfer, and tries to answer three main questions: how P2P traffic is distributed across the Internet, what the characteristics of the application-level P2P network connectivity are, and how dynamic the P2P systems are. The main finding is that ten percent of clients are usually the most popular servers, and are responsible for originating 99 percent of the overall network traffic. This fact makes P2P systems vulnerable to failure, looking at the network level, since a failure of one of these popular servers can affect the overall P2P network behavior. Furthermore, most users join P2P networks after work, and their number constantly increases until late at night. Moreover, over 60 percent of P2P clients spent more than ten minutes per day connected, and two-thirds of them have broadband network lines. Finally, one of the most interesting results is that the good stability of P2P traffic indicates that application-specific layer-three traffic engineering schemes could be a promising way to manage P2P workload in an ISP network. Overall, this is a very interesting paper, tackling a complicated issue, and offering valuable information about P2P traffic and its impact on the underlying network. Online Computing Reviews Service

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cover image IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking Volume 12, Issue 2

April 2004

193 pages

ISSN:1063-6692

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IEEE Press

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Published: 01 April 2004

Published in TON Volume 12, Issue 2

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https://dl.acm.org/doi/10.1007/s10922-021-09637-1
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