Affiliation:
1. University of Essex, UK
Abstract
This chapter considers the various parameters that affect the user’s Quality-of-Experience (QoE) in mobile peer-to-peer streaming systems, which are a form of content delivery network. Network and content providers do not necessarily focus on users’ QoE when designing the content delivery strategies and business models. The outcome of this is quite often the over-provisioning of network resources and also a lack of knowledge in respect to the user’s satisfaction. The focus is the methodology for quantifying the user’s perception of service quality for mobile video services and user contexts. The statistical technique of discriminant analysis is employed in defining prediction models to map Quality-of-Service (QoS) parameters onto estimates of the user’s QoE ratings. The chapter considers the relative contribution of the QoS parameters to predicting user responses. The chapter also demonstrates the value of the prediction models in developing QoE management strategies in order to optimize network resource utilization. To investigate the versatility of the framework, a feasibility study was applied to a P2P TV system. P2P systems continue to develop and as such, not a lot is known about their QoE characteristics, which situation this chapter seeks to remedy.
Reference82 articles.
1. Aldridge, R. P. (1996). Continuous quality assessment of digitally-coded television pictures. PhD Thesis, University of Essex, Colchester.
2. Video acceptability and frame rate.;R. T.Apteker;IEEE Transactions on Multimedia,1995
3. Multimedia transport protocols for wireless networks;P.Balaouras;Emerging wireless multimedia services and technologies,2005
4. Bouch, A., Sasse, M. A., & DeMeer, H. (2000). Of packets and people: A user-centred approach to quality of service. In Eighth International Workshop on Quality of Service.
5. Brun, P., Hauske, G., & Stockhammer, T. (2004). Subjective assessment of H.264/AVC video for low-bitrate multimedia messaging services. In IEEE International Conference on Image Processing (pp. 1145-1148).