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Quantifying Skype user satisfaction

Authors:

Kuan-Ta Chen,

Chun-Ying Huang,

Polly Huang,

Chin-Laung LeiAuthors Info & Claims

SIGCOMM '06: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications

Pages 399 - 410

https://doi.org/10.1145/1159913.1159959

Published: 11 August 2006 Publication History

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Abstract

The success of Skype has inspired a generation of peer-to-peer-based solutions for satisfactory real-time multimedia services over the Internet. However, fundamental questions, such as whether VoIP services like Skype are good enough in terms of user satisfaction,have not been formally addressed. One of the major challenges lies in the lack of an easily accessible and objective index to quantify the degree of user satisfaction.In this work, we propose a model, geared to Skype, but generalizable to other VoIP services, to quantify VoIP user satisfaction based on a rigorous analysis of the call duration from actual Skype traces. The User Satisfaction Index (USI) derived from the model is unique in that 1) it is composed by objective source-and network-level metrics, such as the bit rate, bit rate jitter, and round-trip time, 2) unlike speech quality measures based on voice signals, such as the PESQ model standardized by ITU-T, the metrics are easily accessible and computable for real-time adaptation, and 3) the model development only requires network measurements, i.e., no user surveys or voice signals are necessary. Our model is validated by an independent set of metrics that quantifies the degree of user interaction from the actual traces.

References

[1]

S. A. Baset and H. Schulzrinne. An analysis of the Skype peer-to-peer internet telephony protocol. In Proceedings of IEEE INFOCOM '06, Barcelona, Spain, Apr. 2006.

Crossref

Google Scholar

[2]

T. Berson. Skype security evaluation. ALR-2005-031, Anagram Laboratorie, 2005.

Google Scholar

[3]

D. R. Cox and D. Oakes. Analysis of Survival Data. Chapman & Hall/CRC, June 1984.

Google Scholar

[4]

D. R. Cox and E. J. Snell. A general definition of residuals (with discussion). Journal of the Royal Statistical Society, B 30:248--275, 1968.

Google Scholar

[5]

I. Daubechies. The wavelet transform, time-frequency localization and signal analysis. IEEE Transactions on Information Theory, 36(5):961--1005, Sept. 1990.

Digital Library

Google Scholar

[6]

D. L. Donoho. De-noising by soft-thresholding. IEEE Transactions on Information Theory, 41(3):613--627, May 1995.

Digital Library

Google Scholar

[7]

F. E. Harrell. Regression Modeling Strategies, with Applications to Linear Models, Survival Analysis and Logistic Regression. Springer, 2001.

Digital Library

Google Scholar

[8]

D. P. Harrington and T. R. Fleming. A class of rank test procedures for censored survival data. Biometrika, 69:553--566, 1982.

Crossref

Google Scholar

[9]

ITU-T Recommendation P.862. Perceptual evaluation of speech quality (PESQ), an objective method for end-to-end speech quality assessment of narrow-band telephone networks and speech codecs, Feb 2001.

Google Scholar

[10]

K. Lam, O. Au, C. Chan, K. Hui, and S. Lau. Objective speech quality measure for cellular phone. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, volume 1, pages 487--490, 1996.

Digital Library

Google Scholar

[11]

A. Rix, J. Beerends, M. Hollier, and A. Hekstra. Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs. In proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, volume 2, pages 73--76, 2001.

Digital Library

Google Scholar

[12]

K. Suh, D. R. Figueiredo, J. Kurose, and D. Towsley. Characterizing and detecting relayed traffic: A case study using Skype. In Proceedings of IEEE INFOCOM '06, Barcelona, Spain, Apr. 2006.

Google Scholar

[13]

T. M. Therneau and P. M. Grambsch. Modeling Survival Data: Extending the Cox Model. Springer, 1st edition, August 2001.

Google Scholar

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Published In

SIGCOMM '06: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications

September 2006

458 pages

ISBN:1595933085

DOI:10.1145/1159913

General Chair:
Luigi Rizzo
Università di Pisa, Italy
,
Program Chairs:
Tom Anderson
University of Washington, USA
,
Nick McKeown
Stanford University, USA

ACM SIGCOMM Computer Communication Review Volume 36, Issue 4
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
October 2006
445 pages
ISSN:0146-4833
DOI:10.1145/1151659
Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 August 2006

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SIGCOMM06

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SIGCOMM06: ACM SIGCOMM 2006 Conference

September 11 - 15, 2006

Pisa, Italy

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Overall Acceptance Rate 462 of 3,389 submissions, 14%

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