scholarly journals The Impact of Throughput Fluctuation on Quality of Experience for YouTube Service

2017 ◽  
Keyword(s):  
Quality Of Experience ◽  
The Impact

scholarly journals An Adaptive Bitrate Switching Algorithm for Speech Applications in Context of WebRTC

2021 ◽  
Vol 17 (4) ◽  
pp. 1-21
Author(s):  
Mohannad Alahmadi ◽  
Peter Pocta ◽  
Hugh Melvin
Keyword(s):  
Real Time ◽  
Data Exchange ◽  
Quality Of Experience ◽  
End User ◽  
High Quality ◽  
Content Type ◽  
Switching Algorithm ◽  
Wide Range ◽  
The Impact

Web Real-Time Communication (WebRTC) combines a set of standards and technologies to enable high-quality audio, video, and auxiliary data exchange in web browsers and mobile applications. It enables peer-to-peer multimedia sessions over IP networks without the need for additional plugins. The Opus codec, which is deployed as the default audio codec for speech and music streaming in WebRTC, supports a wide range of bitrates. This range of bitrates covers narrowband, wideband, and super-wideband up to fullband bandwidths. Users of IP-based telephony always demand high-quality audio. In addition to users’ expectation, their emotional state, content type, and many other psychological factors; network quality of service; and distortions introduced at the end terminals could determine their quality of experience. To measure the quality experienced by the end user for voice transmission service, the E-model standardized in the ITU-T Rec. G.107 (a narrowband version), ITU-T Rec. G.107.1 (a wideband version), and the most recent ITU-T Rec. G.107.2 extension for the super-wideband E-model can be used. In this work, we present a quality of experience model built on the E-model to measure the impact of coding and packet loss to assess the quality perceived by the end user in WebRTC speech applications. Based on the computed Mean Opinion Score, a real-time adaptive codec parameter switching mechanism is used to switch to the most optimum codec bitrate under the present network conditions. We present the evaluation results to show the effectiveness of the proposed approach when compared with the default codec configuration in WebRTC.

The Impact of Scent Type on Olfaction-Enhanced Multimedia Quality of Experience

2016 ◽  
pp. 1-13 ◽  
Author(s):  
Niall Murray ◽  
Brian Lee ◽  
Yuansong Qiao ◽  
Gabriel Miro-Muntean
Keyword(s):  
Quality Of Experience ◽  
The Impact

scholarly journals A study on the impact of AL-FEC techniques on TV over IP Quality of Experience

2011 ◽  
Vol 2011 (1) ◽  
Author(s):  
Federica Battisti ◽  
Marco Carli ◽  
Elena Mammi ◽  
Alessandro Neri
Keyword(s):  
Quality Of Experience ◽  
The Impact

scholarly journals Network Performance Criteria for Telecommunication Traffic Types driven by Quality of Experience

2019 ◽  
Vol 15 (3) ◽  
pp. 233-244 ◽  
Author(s):  
Ines Ramadža ◽  
Vesna Pekić ◽  
Julije Ožegović
Keyword(s):  
Network Performance ◽  
Quality Of Experience ◽  
Performance Criteria ◽  
Live Streaming ◽  
Traffic Routing ◽  
Different Types ◽  
Telecom Operator ◽  
The Impact ◽  
The Given

A common reason for changing the chosen service provider is the users' perception of service. Quality of Experience (QoE) describes the end user's perception of service while using it. A frequent cause of QoE degradation is inadequate traffic routing, where, other than throughput, selected routes do not satisfy minimum network requirements for the given service or services. In order to enable QoE-driven routing, per traffic type defined routing criteria are required. Our goal was to obtain those criteria for relevant services of a telecom operator. For the purpose of identifying services of interest, we first provide short results of user traffic analysis within the telecom operator network. Next, our work presents testbed measurements which explore the impact of packet loss and delay on user QoE for video, voice, and management traffic. For video services, we investigated separately multicast delivery, unicast HTTP Live Streaming (HLS), and unicast Real Time Streaming Protocol (RTSP) traffic. Applying a threshold to QoE values, from the measured dependencies we extracted minimum network performance criteria for the investigated different types of traffic. Finally, we provide a comparison with results available in the literature on the topic.

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