The success of Skype has inspired a generation of peer-to-peerbased solutions for real-time multimedia services over the Internet. However, there lacks still a robust metric quantifying the perceptual quality of a Skype call. The widely-used PESQ (Perceptual Evaluation of Speech Quality) falls short of modeling superwideband calls, which are characteristics of SILK -Skype's codec made public in 2011. Towards a robust QoE (Quality of Experience) metric for VoIP call analysis, we propose a model, referred to as WF-Regression model, to capture the call rate and perceptual quality relationship. The model is shown through a user study that it is robust, R-square = 0.9990 and outperform PESQ modeling the quality of Skype calls, error ratio = 3.68% vs. 14.59%.

The effective end-to-end transport of delay-sensitive voice data has long been a problem in multimedia networking. One of the major issues is determining the sending rate of real-time VoIP streams such that the user experience is maximized per unit network resource consumed. A particularly interesting complication that remains to be addressed is that the available bandwidth is often dynamic. Thus, it is unclear whether a marginal increase warrants better user experience. If a user naively tunes the sending rate to the optimum at any given opportunity, the user experience could fluctuate.To investigate the effects of magnitude and frequency of rate changes on user experience, we recruited 127 human participants to systematically score emulated Skype calls with different combinations of rate changes, including varying magnitude and frequency of rate changes. Results show that 1) the rate change frequency affects the user experience on a logarithmic scale, echoing Weber-Fechner's Law [1], 2) the effect of rate change magnitude depends on how users perceive the quality difference, and 3) this study derives a closed-form model of user perception for rate changes for Skype calls.

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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 and satisfies users more than the greedy-naïve mechanism, as well as the mechanism implemented in Skype.

Being able to detect and recognize human activities is essential for 3D collaborative applications for efficient quality of service provisioning and device management. A broad range of research has been devoted to analyze media data to identify human activity, which requires the knowledge of data format, application-specific coding technique and computationally expensive image analysis. In this paper, we propose a human activity detection technique based on application generated metadata and related system metadata. Our approach does not depend on specific data format or coding technique. We evaluate our algorithm with different cyberphysical setups, and show that we can achieve very high accuracy (above 97%) by using a good learning model.