Real-time QoE prediction for multimedia applications in Wireless Mesh Networks

As Wireless Mesh Networks (WMNs) are being increasingly deployed, there is an increasing demand for new quality assessment mechanisms that allow service operators to evaluate and optimize the utilization of network resources, while ensuring a good quality level on multimedia applications as perceived by end-users. However, existing real-time assessment schemes for WMNs are not capable of capturing the actual quality of received multimedia content with regard to user perception. Therefore, it is not possible to assure the user experience of content services. To address this problem, this paper introduces the Hybrid Quality of Experience (HyQoE) Prediction, which is a quality estimator specially designed to assess real-time multimedia applications. HyQoE is designed based on the framework of the widely used Pseudo-Subjective Quality Assessment (PSQA) Tool which exploits Random Neural Network (RNN). Crucial extension work has been implemented to achieve our objectives. A performance evaluation verifies the effectiveness and advantages of HyQoE in predicting users' perception of multimedia content in WMNs over existing subjective and hybrid methods.