Abstract
The rising popularity of data calls and the slowed global economy have posed a challenge to voice data networking—how to satisfy the growing user demand for VoIP calls under limited network resources. In a bandwidth-constrained network in particular, raising the bitrate for one call implies a lowered bitrate for another. Therefore, knowing whether it is worthwhile to raise one call's bitrate while other users might complain is crucial to the design of a user-centric rate control mechanism. To this end, previous work (Chen et al. 2012) has reported a log-like relationship between bitrate and user experience (i.e., QoE) in Skype calls. To show that the relationship extends to more general VoIP calls, we conduct a 60-participant user study via the Amazon Mechanical Turk crowdsourcing platform and reaffirm the log-like relationship between the call bitrate and user experience in widely used AMR-WB. The relationship gives rise to a simple and practical rate control scheme that exponentially quantizes the steps of rate change, therefore the name—exponential quantization (EQ). To support that EQ is effective in addressing the challenge, we show through a formal analysis that the resulting bandwidth allocation is optimal in both the overall QoE and the number of calls served. To relate EQ to existing rate control mechanisms, we show in a simulation study that the bitrates of calls administered by EQ converge over time and outperform those controlled by a (naïve) greedy mechanism and the mechanism implemented in Skype.
- 3GPP. 2011. 3GPP TS26.171: Speech codec speech processing functions: Adaptive multi-rate - wideband (AMR-WB) speech codec; general description.Google Scholar
- ITU-T. 1996. ITU-T Recommendation P.800, Methods for Subjective Determination of Transmission Quality.Google Scholar
- ITU-T. 1996. ITU-T Recommendation P.830, Subjective Performance Assessment of Telephone-band and Wideband Digital Codecs.Google Scholar
- ITU-T. 2006. ITU-T Recommendation P, 10/G.100. Vocabulary for Performance and Quality of Service.Google Scholar
- ITU-T. 2008. ITU-T Recommendation P.910, Subjective Video Quality Assessment Methods for Multimedia Applications.Google Scholar
- ITU-T. 2012. ITU-T Recommendation G.729: Coding of speech at 8 kbit/s using conjugate-structure algebraic-code-excited linear prediction.Google Scholar
- Amazon Mechanical Turk. Retrieved from https://www.mturk.com/mturk/welcome.Google Scholar
- S. A. Baset and H. Schulzrinne. 2006. An analysis of the Skype peer-to-peer internet telephony protocol. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM’06).Google Scholar
- D. Bertsekas and R. Gallager. 1992. Data Networks. Prentice-Hall, Englewood Cliffs, NJ, 1992. Google ScholarDigital Library
- K. R. Boff, L. Kaufman, and J. P. Thomas. 1986. Handbook of Perception and Human Performance. Wiley-Interscience.Google Scholar
- J. Bolot and T. Turletti. 1994. A rate control mechanism for packet video in the internet. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM’94).Google Scholar
- D. Bonfiglio, M. Mellia, M. Meo, N. Ritacca, and D. Rossi. 2008. Tracking down Skype traffic. IEEE International Conference on Computer Communications (INFOCOM’08).Google Scholar
- T. Bu, Y. Liu, and D. Towsley. 2006. On the TCP-friendliness of VoIP traffic. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM’06).Google Scholar
- C.-N. Chen, C.-Y. Chu, S.-L. Yeh, H.-H. Chu, and P. Hunag. 2012. Measuring the perceptual quality of Skype sources. In Proceedings of ACM Communications and Computer Networks (SIGCOMM, W-MUST’12). Google ScholarDigital Library
- C.-N. Chen, C.-Y. Chu, S.-L. Yeh, H.-H. Chu, and P. Hunag. 2014. Modeling the QoE of rate changes in Skype/SILK VoIP Calls. IEEE/ACM Transactions on Networking 22, 6 (December 2014), 1781--1793. Google ScholarDigital Library
- K.-T. Chen, C.-Y. Huang, P. Huang, and C.-L. Lei. 2006. Quantifying Skype user satisfaction. In Proceedings of ACM Communications and Computer Networks (SIGCOMM’06). Google ScholarDigital Library
- L. D. Cicco, S. Mascolo, and V. Palmisano. 2007. An experimental investigation of the congestion control used by Skype VoIP. In Proceedings of Wired/Wireless Internet Communications (WWIC’07). Google ScholarDigital Library
- L. De Cicco and S. Mascolo. 2008. A mathematical model of the Skype VoIP congestion control algorithm. In Proceedings of IEEE Conference on Decision and Control (CDC’08).Google Scholar
- T. Dieker. 2002. Simulation of Fractional Brownian Motion. Master's thesis, University of Twente, the Netherlands.Google Scholar
- M. Fiedler, T. Hossfeld, and P. Tran-Gia. 2010. A generic quantitative relationship between quality of experience and quality of service. IEEE Network 24, 2 (2010), 36--41. Google ScholarDigital Library
- S. Floyd and K. Fall. 1999. Promoting the use of end-to-end congestion control in the internet. IEEE/ACM Transactions on Networking 7, 4 (1999), 458--472. Google ScholarDigital Library
- S. Floyd, M. Handley, J. Padhye, and J. Widmer. 2000. Equation-based congestion control for unicast applications. In Proceedings of ACM Communications and Computer Networks (SIGCOMM’00). Google ScholarDigital Library
- C. Fraleigh, F. Tobagi, and C. Diot. 2003. Provisioning IP backbone networks to support latency sensitive traffic. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM’03).Google Scholar
- M. Ghobadi, R. Mahajan, A. Phanishayee, H. Rastegarfar, P.-A. Blanche, M. Glick, D. Kilper, J. Kulkarni, G. Ranade, and N. Devanur. 2016. ProjecToR: Agile reconfigurable datacenter interconnect. In ACM SIGCOMM. Google ScholarDigital Library
- M. Handley, S. Floyd, J. Padhye, and J. Widmer. 2003. TCP friendly rate control (TFRC): Protocol specification. RFC 3348 (2003).Google Scholar
- T.-Y. Huang, P. Huang, K.-T. Chen, and P.-J. Wang. 2010. Can Skype be more satisfying? A QoE-centric study of the FEC mechanism in the internet-scale VoIP system. IEEE Network 24, 2 (2010), 42--48. Google ScholarDigital Library
- F. Kelly. 1997. Charging and rate control for elastic traffic. European Transactions on Telecommunications 8 (1997), 33--37.Google ScholarCross Ref
- F. P. Kelly, A. Maulloo, and D. Tan. 1998. Rate control for communication networks: Shadow price proportional fairness and stability. Journal of the Operational Research Society 49 (1998), 237--252.Google ScholarCross Ref
- H. Kim, K. Kim, Y. Han, and S. Yun. 2004. A proportional fair scheduling for multicarrier transmission systems. IEEE Vehicular Technology Conference (VTC’04).Google Scholar
- R. Kwan, C. Leung, and J. Zhang, 2009. Proportional fair multiuser scheduling in LTE. Signal Processing Letters 16 (2009), 461--464.Google ScholarCross Ref
- R. J. La and V. Anantharam. 2002. Utility-based rate control in the Internet for elastic traffic. IEEE/ACM Transactions on Networking 10, 2 (2002), 272--286. Google ScholarDigital Library
- M. R. Longo and S. F. Lourenco. 2007. Spatial attention and the mental number line: Evidence for characteristic biases and compression. Neuropsychologia 45 (2007), 1400--1406.Google ScholarCross Ref
- R. S. Moyer and T. K. Landauer. 1967. Time required for judgments of numerical inequality. Nature 215, 5109 (1967), 1519--1520.Google ScholarCross Ref
- P. Reichl, S. Egger, R. Schatz, and A. DAlconzo. 2010. The logarithmic nature of QoE and the role of the weber- fechner law in qoe assessment. In Proceedings of ICC’10.Google ScholarCross Ref
- P. Reichl, B. Tuffin, and R. Schatz. 2010. Economics of logarithmic quality-of-experience in communication networks. In Proceedings of the IEEE Conference on Telecommunications Internet and Media Techno Economics. CTTE, 2010.Google Scholar
- F. Ribeiro, D. Florencio, C. Zhang, and M. Seltzer. 2011. CROWDMOS: An approach for crowdsourcing mean opinion score studies. In IEEE ICASSP.Google Scholar
- L. Rizzo. 1998. Dummynet and forward error correction. In Proceedings of the USENIX Annual Technical Conference. Google ScholarDigital Library
- L. Rizzo. 2000. Pgmcc: A TCP-friendly single-rate multicast congestion control scheme. In Proceedings of ACM Communications and Computer Networks (SIGCOMM’00). Google ScholarDigital Library
- E. D. Scheirer. 1998. Tempo and beat analysis of acoustic musical signals. Journal of the Acoustical Society of America 103, 1 (1998), 588--601.Google ScholarCross Ref
- J. Shen. 2003. On the foundations of vision modeling: I. Weber's law and Weberized TV restoration. Physica D: Nonlinear Phenomena 175, 3--4 (2003), 241--251.Google ScholarCross Ref
- Statistic Brain. 2016. Retrieved from http://www.statisticbrain.com/skype-statistics/.Google Scholar
- N. Wakamiya, M. Murata, and H. Miyahara. 2000. On TCP-friendly video transfer with consideration on application level QoS. In Proceedings of IEEE International Conference on Multimedia and Expo (ICME’00).Google Scholar
- K. Vos, S. Jensen, and K. Soerensen. 2010. Internet-draft: Draft-vos-silk-02, SILK speech codec. Internet Engineering Task Force (IETF).Google Scholar
- Y. Xue, B. Li, and K. Nahrstedt. 2006. Optimal resource allocation in wireless ad hoc networks: A price-based approach. IEEE Transactions on Mobile Computing 5, 4 (2006), 347--364. Google ScholarDigital Library
- J. Yan, K. Katrinis, M. May, and B. Plattner. 2006. Media- and TCP-friendly congestion control for scalable video streams. IEEE Transactions on Multimedia 8 (2006), 196--206. Google ScholarDigital Library
- Y.-C. Yen, C.-Y. Chu, C.-N. Chen, S.-L. Yeh, H.-H. Chu, and P. Huang. 2013. Exponential quantization: User-centric rate control for Skype calls. In Proceedings of the 31st ACM Annual Conference of the Special Interest Group on Data Communication (ACM SIGCOMM’13), Poster Session, Hong Kong, August. Google ScholarDigital Library
- Y.-C. Yen, C.-Y. Chu, S.-L. Yeh, H.-H. Chu, and P. Huang. 2013. Lab experiment vs. crowdsourcing: A comparative user study on skype call quality. In Proceedings of the 9th Asian Internet Engineering Conference (AINTEC’13). Google ScholarDigital Library
Index Terms
- EQ: A QoE-Centric Rate Control Mechanism for VoIP Calls
Recommendations
Exponential quantization: user-centric rate control for skype calls
As Skype has become popular and a profitable business, the long-standing problem of how to deliver Skype calls deserves a serious revisit from an economic viewpoint. This study proposes a rate control mechanism for Skype calls that satisfies more users ...
Exponential quantization: user-centric rate control for skype calls
SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMMAs Skype has become popular and a profitable business, the long-standing problem of how to deliver Skype calls deserves a serious revisit from an economic viewpoint. This study proposes a rate control mechanism for Skype calls that satisfies more users ...
Lab experiment vs. crowdsourcing: a comparative user study on Skype call quality
AINTEC '13: Proceedings of the 9th Asian Internet Engineering ConferenceTo deliver voice over the Internet in a cost-effective way, it is essential to quantify the quality of user experience (i.e., QoE) of a voice service at various provisioning levels. Conducting user studies is an inevitable step facilitating quantitative ...
Comments