An analytic framework for modeling peer to peer networks

This paper presents an analytic framework to evaluate the performance of peer to peer (P2P) networks. Using the time to download or replicate an arbitrary file as the metric, we present a model which accurately captures the impact of various network and peer level characteristics on the performance of a P2P network. We propose a queueing model which evaluates the delays in the routers using a single class open queueing network and the peers as M/G/1/K processor sharing queues. The framework takes into account the underlying physical network topology and arbitrary file sizes, the search time, load distribution at peers and number of concurrent downloads allowed by a peer. The model has been validated using extensive simulations with campus level, power law AS level and ISP level topologies. The paper also describes the impact of various parameters associated with the network and peers including external traffic rates, service variability, file popularity etc. on the download times. We also show that in scenarios with multi-part downloads from different peers, a rate proportional allocation strategy minimizes the download times.

[1]  Hui Zhang,et al.  Measurement-based optimization techniques for bandwidth-demanding peer-to-peer systems , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[2]  Rayadurgam Srikant,et al.  Modeling and performance analysis of BitTorrent-like peer-to-peer networks , 2004, SIGCOMM 2004.

[3]  Ian T. Foster,et al.  Mapping the Gnutella Network , 2002, IEEE Internet Comput..

[4]  Desmond P. Taylor,et al.  On the SelfSimilar Nature of Ethernet Traffic (Extended Version) , 2007 .

[5]  Bruce M. Maggs,et al.  Globally Distributed Content Delivery , 2002, IEEE Internet Comput..

[6]  Sally Floyd,et al.  Wide area traffic: the failure of Poisson modeling , 1995, TNET.

[7]  David R. Karger,et al.  Observations on the Dynamic Evolution of Peer-to-Peer Networks , 2002, IPTPS.

[8]  Sally Floyd,et al.  Wide-area traffic: the failure of Poisson modeling , 1994 .

[9]  Eytan Adar,et al.  Free Riding on Gnutella , 2000, First Monday.

[10]  Michalis Faloutsos,et al.  On power-law relationships of the Internet topology , 1999, SIGCOMM '99.

[11]  Krishna P. Gummadi,et al.  An analysis of Internet content delivery systems , 2002, OPSR.

[12]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1997, TNET.

[13]  W. Whitt,et al.  The Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[14]  Gustavo de Veciana,et al.  Performance of peer-to-peer networks: Service capacity and role of resource sharing policies , 2006, Perform. Evaluation.

[15]  Stefan Saroiu,et al.  A Measurement Study of Peer-to-Peer File Sharing Systems , 2001 .

[16]  Gustavo de Veciana,et al.  Service capacity of peer to peer networks , 2004, IEEE INFOCOM 2004.

[17]  F. Clevenot,et al.  A simple fluid model for the analysis of the squirrel peer-to-peer caching system , 2004, IEEE INFOCOM 2004.

[18]  M. Newman,et al.  Random graphs with arbitrary degree distributions and their applications. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  W. Whitt,et al.  Performance of the Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[20]  Donald F. Towsley,et al.  Modeling peer-peer file sharing systems , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[21]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[22]  J. Frankel,et al.  The gnutella protocol specification v0.4 document revision 1.2 , 2000 .

[23]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.

[24]  H. Apte,et al.  An Analysis of Internet Content Delivery Systems , 2006 .