TY - GEN

T1 - Video Quality Estimator for Wireless Mesh Networks

AU - Aguiar, Elisangela

AU - Riker, André

AU - Jorge Gomes Abelem, Antonio

AU - Cerqueira, Eduardo

AU - Mu, Mu

PY - 2012

Y1 - 2012

N2 - As Wireless Mesh Networks (WMNs) have been increasingly deployed, where users can share, create and access videos with different characteristics, the need for new quality estimator mechanisms has become important because operators want to control the quality of video delivery and optimize their network resources, while increasing the user satisfaction. However, the development of in-service Quality of Experience (QoE) estimation schemes for Internet videos (e.g., real-time streaming and gaming) with different complexities, motions, Group of Picture (GoP) sizes and contents remains a significant challenge and is crucial for the success of wireless multimedia systems. To address this challenge, we propose a real-time quality estimator approach, HyQoE, for real-time multimedia applications. The performance evaluation in a WMN scenario demonstrates the high accuracy of HyQoE in estimating the Mean Opinion Score (MOS). Moreover, the results highlight the lack of performance of the well-known objective methods and the Pseudo-Subjective Quality Assessment (PSQA) approach.

AB - As Wireless Mesh Networks (WMNs) have been increasingly deployed, where users can share, create and access videos with different characteristics, the need for new quality estimator mechanisms has become important because operators want to control the quality of video delivery and optimize their network resources, while increasing the user satisfaction. However, the development of in-service Quality of Experience (QoE) estimation schemes for Internet videos (e.g., real-time streaming and gaming) with different complexities, motions, Group of Picture (GoP) sizes and contents remains a significant challenge and is crucial for the success of wireless multimedia systems. To address this challenge, we propose a real-time quality estimator approach, HyQoE, for real-time multimedia applications. The performance evaluation in a WMN scenario demonstrates the high accuracy of HyQoE in estimating the Mean Opinion Score (MOS). Moreover, the results highlight the lack of performance of the well-known objective methods and the Pseudo-Subjective Quality Assessment (PSQA) approach.

KW - Multimedia

KW - quality of experience

KW - random neural networks

KW - video quality prediction

KW - video streaming

KW - wireless mesh networks

KW - wireless networks

U2 - 10.1109/IWQoS.2012.6245980

DO - 10.1109/IWQoS.2012.6245980

M3 - Conference contribution/Paper

SN - 978-1-4673-1296-7

BT - Quality of Service (IWQoS), 2012 IEEE 20th International Workshop on

PB - IEEE International Workshop on Quality of Service

ER -