Abstract
This paper proposes a curve fitting technique for fast and accurate estimation of the perceived quality of streaming media contents, delivered within a wireless network. The model accounts for the effects of various network parameters such as congestion, radio link power, and video transmission bit rate. The evaluation of the perceived quality of service (PQoS) is based on the well-known VQM objective metric, a powerful technique which is highly correlated to the more expensive and time consuming subjective metrics. Currently, PQoS is used only for offline analysis after delivery of the entire video content. Thanks to the proposed simple model, we can estimate in real time the video PQoS and we can rapidly adapt the content transmission through scalable video coding and bit rates in order to offer the best perceived quality to the end users. The designed model has been validated through many different measurements in realistic wireless environments using an ad hoc WiFi test bed.
Highlights
It is well known that the goal of any QoS mechanism is to maintain a good level of user-perceived QoS even when the network conditions are changing unpredictably.Typical QoS provisioning solutions for multimedia video applications have been always based on the idea of trying to reserve or assure certain network guarantees, so that packets coming from delay or bandwidth sensitive applications receive a better treatment in the network
Showing that subjectively derived perceived quality of service (PQoS) versus bit rate curves can be successfully approximated by a group of exponential functions, the authors propose a method for exploiting a simple objective metric, which is obtained from the mean frame rate versus bit rate curves of an encoded clip; even in this work no network-level parameters have been considered
With the aim of implementing a more realistic scenario, we considered the data traffic generated from other mobile devices within the AP coverage area; this aggregated data traffic represents a set of different applications such as download of audiovideo contents, text files, or web surfing; it can be considered as “background traffic” handled by the access point without stringent delay constraints, the amount of this background data traffic has, for sure, a heavy impact on the multimedia video transmission in terms of perceived quality, the evaluation of the PQoS metric and the resulting analytical models cannot be designed without considering this kind of traffic
Summary
It is well known that the goal of any QoS mechanism is to maintain a good level of user-perceived QoS even when the network conditions are changing unpredictably. One of the critical issues to keep in mind when dealing with provision of multimedia services is the quality of sound or picture presented to the end user, assuming a high-quality source and an error-free environment This quality is directly proportional to the bit-rate used in the encoding process, more recently, diverse solutions were proposed for scalable multimedia transmissions over wireless networks [3, 4]. Any two users who may be sharing a common experience (i.e., identical applications) are likely to have significantly different views of the QoS; the important thing is to understand how such individual views are used for estimating the connection between wireless network parameters and user perception of QoS provided over that network This linkage will typically take the form of a numerical mapping (mathematical relation) between some measure of the user-perceived quality (e.g., the mean opinion score (MOS) [5]) and a particular set of network parameters (e.g., available bandwidth). There is a need for a quality metric estimator, based on the VQM objective metric [6, 7] that accurately matches the subjective quality and can be implemented in real-time video systems
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