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Predicting the level of cooperation in a Peer-to-Peer live streaming application

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Abstract

The Peer-to-Peer (P2P) architecture has been successfully used to reduce costs and increase the scalability of Internet live streaming systems. However, the effectiveness of these applications depends largely on user (peer) cooperation. In this article we use data collected from SopCast, a popular P2P live application, to show that there is high correlation between peer centrality—out-degree, out-closeness, and betweenness—in the P2P overlay graph and peer cooperation. We use this finding to propose a new regression-based model to predict peer cooperation from its past centrality. Our model takes only peer out-degrees as input, as out-degree has the strongest correlation with peer cooperation. Our evaluation shows that our model has good accuracy and does not need to be trained too often (e.g., once each 16 min). We also use our model to sketch a mechanism to detect malicious peers that report artificially inflated cooperation aiming at, for example, receiving better quality of service.

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Notes

  1. http://www.sopcast.com, http://www.pptv.com, and http://www.uusee.com.

  2. According to Google Trends (http://www.google.com/trends), SopCast received a larger number of searches than other popular applications of its kind, such as PPLive and UUSee, from April 2011 to November 2012.

  3. In several P2P live applications, such as CoolStreaming and PPLive, a centralized server (e.g., the tracker or a log server) periodically receives control messages from the active peers [4, 7].

  4. http://www.wireshark.org.

  5. Weibull: \(p_{X}(x)\) = \(\alpha \beta x^{\beta - 1} e^{-\alpha x^\beta }I_{(0, \infty )}(x)\).

  6. Exponential: \(p_{X}(x)\) = \(\lambda e^{-\lambda x }\).

  7. The variation is mostly due to the lack of stability of PlanetLab machines during the experiments.

  8. The lack of cooperation caused by opportunistic peers that choose not to forward data to their partners is not considered here.

  9. We also tested whether any causality relationship exists between peer out-degree and cooperation level applying the Granger causality test [40]. However, for the vast majority of the peers (over 80 %), we found no clear causality relationship from either out-degree to cooperation level or cooperation level to out-degree. This indicates that even though there is a strong association between out-degree and cooperation level, which can be exploited for prediction (as we do here), we cannot claim that any variable causes the other as both may be caused by a third (unknown) factor (or factor combination), which is external to our scope (e.g., some component of the SopCast protocol).

  10. http://www.r-project.org/.

  11. We here consider only the peers to which \(i\) uploaded data as these are the ones that contribute to \(i\)’s out-degree.

  12. Since the suspect peer may have established some valid partnerships with legitimate peers, we choose not to consider all other peers in its neighborhood as suspicious automatically. Instead, we label only peers with local clustering coefficients above \(\tau _m\) as suspect.

  13. Being a local metric, the clustering coefficient can be computed in a distributed monitoring infrastructure, such as the one proposed in [44].

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Acknowledgments

This research is partially funded by the Brazilian National Institute of Science and Technology for Web Research (MCT/CNPq/INCT Web Grant Number 573871/2008-6), and by the authors’ individual grants from CNPq, CAPES, and FAPEMIG.

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Authors and Affiliations

  1. Computer Science Department, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil

    Glauber D. Gonçalves, Ítalo Cunha & Jussara M. Almeida

  2. Computer Science Department, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil

    Alex B. Vieira

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  1. Glauber D. Gonçalves
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  2. Ítalo Cunha
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  3. Alex B. Vieira
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  4. Jussara M. Almeida
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Correspondence to Ítalo Cunha.

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Communicated by R. Rejaie.

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Gonçalves, G.D., Cunha, Í., Vieira, A.B. et al. Predicting the level of cooperation in a Peer-to-Peer live streaming application. Multimedia Systems 22, 161–180 (2016). https://doi.org/10.1007/s00530-014-0434-5

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