QoE-Driven Sender Bitrate Adaptation Scheme for Video Applications over IP Multimedia Subsystem

Khan, Asiya; Mkwawa, Is-Haka; Sun, Lingfen; Ifeachor, Emmanuel

doi:10.1109/icc.2011.5962458

Cited by 17 publications

(10 citation statements)

References 17 publications

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“…Depending on the determination of the appropriate QoE IFs which may need to be adjusted for a given service, QoE optimization may be performed at different locations, as depicted in Figure 2. Thus, as summarized in Table 4, the optimization can be conducted by applying various control mechanisms at the base stations within various access networks [109][110][111] by applying policy management rules at the gateways or routers within the core network [97,103,112,113], by conducting adjustments at the servers in the service/application [104,113,114], content or cloud domains, or the combination thereof [107], as well as on end-user device [115]. Since QoE control relies on QoE monitoring and measurement information, usually the control locations are the same as monitoring and measurement points.…”

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confidence: 99%

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Survey and Challenges of QoE Management Issues in Wireless Networks

Baraković

Skorin‐Kapov

2013

Journal of Computer Networks and Communications

120

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With the move towards converged all-IP wireless network environments, managing end-user Quality of Experience (QoE) poses a challenging task, aimed at meeting high user expectations and requirements regarding reliable and cost-effective communication, access to any service, anytime and anywhere, and across multiple operator domains. In this paper, we give a survey of state-of-the-art research activities addressing the field of QoE management, focusing in particular on the domain of wireless networks and addressing three management aspects: QoE modeling, monitoring and measurement, and adaptation and optimization. Furthermore, we identify and discuss the key aspects and challenges that need to be considered when conducting research in this area.

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mentioning

confidence: 99%

“…The addressed approaches propose various QoE optimization strategies that are aimed at optimal network resource allocation [100,101,112,113]; optimal radio resource allocation [97,103,107,109]; service optimization [97,100,102,107,110,114]; optimized handover decision [113]; access network selection [111]; or battery consumption [115].…”

mentioning

confidence: 99%

Survey and Challenges of QoE Management Issues in Wireless Networks

Baraković

Skorin‐Kapov

2013

Journal of Computer Networks and Communications

120

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“…In [18], subjective view tests for assessing the perceptual quality of low bit-rate video is conducted, which include five distinctive dimensions, such as encoder type, video content, bit rate, frame size (FS), and FR. The QoE-driven model presented in [19] is proposed, which encompassed the content provision and network bandwidth availability. By finding the impact of QoE mapping parameters on end-to-end perceptual video quality, the adaptive SBR scheme is investigated at pre-encoding stage, which is QoE-driven for video applications.…”

Section: Quality-of-experience Perceptive Modelmentioning

confidence: 99%

QoE‐based pseudo heartbeat message compression mechanism for future wireless network

Wen

et al. 2016

Int J Communication

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SUMMARYWireless multimedia services are increasingly becoming popular, which boosts the need for better qualityof-experience (QoE). However, there are many aspects leading to the degradation of real-time video QoE, especially, a large number of always-on-line (AOL) applications existing in future wireless networks transmit heartbeat message periodically to keep always-on, and hence induce heavy signaling costs and overload wireless networks. In this paper, we propose QoE-based pseudo heartbeat message compression mechanism to reduce the number of signaling loads in the radio access network by intercepting the heartbeat message at a certain frequency in the proxy client. To maintain the protocol feature of the AOL applications, the heartbeat messages are reconstructed by the proxy server and sent to the application server. Furthermore, to analyze the influence of this mechanism on the video user, a new QoE perception model is proposed. Finally, combined the QoE perception model for video services with AOL services, the utility function for joint optimization multi-services is developed to determine the optimum compression frequency. The simulation results show that the proposed mechanism greatly alleviates the signaling load and leads to a significant performance improvement on the QoE of video users, while a slight decrease in the QoE of AOL users.

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“…And in [5], a model is proposed based on dynamic sender bit rate control to subjectively estimate the quality of video streaming. In [6], the authors present a new fuzzy logic based SBR adaptation scheme at preencoding stage. The scheme adapts SBR based on feedback information of the QoE prediction model which evaluates Mean Opinion Score (MOS) according to the current congestion and degradation on the receiver.…”

Section: Introductionmentioning

confidence: 99%

A QoE-based sender bit rate adaptation scheme for real-time video transmission in wireless networks

Qian

Wang²,

Zhu

2013

2013 6th International Congress on Image and Signal Processing (CISP)

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Adaptive video transmission schemes are important for real-time video services in wireless networks due to dynamic and volatile wireless environment. Traditional adaptation schemes always take network status of the sender or perceived quality of receiver into consideration, which are rather significant for endto-end video transmission. This paper proposes a novel Quality of Experience (QoE) based end-to-end adaptation scheme for wireless video transmission, which allows the sender to intelligently adapt sender bit rate (SBR) to the dynamic network conditions and perceived quality, as well as the content type. Also it is implemented and tested in an open Android-based test platform. Experimental results show that the proposed scheme can adapt to the dynamic wireless environment to provide the video streaming service with better QoE for users.

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QoE-Driven Sender Bitrate Adaptation Scheme for Video Applications over IP Multimedia Subsystem

Cited by 17 publications

References 17 publications

Survey and Challenges of QoE Management Issues in Wireless Networks

Survey and Challenges of QoE Management Issues in Wireless Networks

QoE‐based pseudo heartbeat message compression mechanism for future wireless network

A QoE-based sender bit rate adaptation scheme for real-time video transmission in wireless networks

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