No silver bullet: QoE metrics, QoE fairness, and user diversity in the context of QoE management

Hosfeld, Tobias; Heegaard, Poul E.; Skorin‐Kapov, Lea; Varela, Martín

doi:10.1109/qomex.2017.7965671

Cited by 21 publications

(25 citation statements)

References 14 publications

(27 reference statements)

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“…The idea was first presented in [18] and later in [22]. The subject model further extends the toolkit for subjective data analysis [9,20]. It also helps make existing analyses more precise [8,21].…”

Section: Related Workmentioning

confidence: 99%

Describing Subjective Experiment Consistency by p-Value P--P Plot

Nawała

Janowski

Ćmiel

et al. 2020

Proceedings of the 28th ACM International Conference on Multimedia

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There are phenomena that cannot be measured without subjective testing. However, subjective testing is a complex issue with many influencing factors. These interplay to yield either precise or incorrect results. Researchers require a tool to classify results of subjective experiment as either consistent or inconsistent. This is necessary in order to decide whether to treat the gathered scores as quality ground truth data. Knowing if subjective scores can be trusted is key to drawing valid conclusions and building functional tools based on those scores (e.g., algorithms assessing the perceived quality of multimedia materials). We provide a tool to classify subjective experiment (and all its results) as either consistent or inconsistent. Additionally, the tool identifies stimuli having irregular score distribution. The approach is based on treating subjective scores as a random variable coming from the discrete Generalized Score Distribution (GSD). The GSD, in combination with a bootstrapped G-test of goodness-of-fit, allows to construct-value P-P plot that visualizes experiment's consistency. The tool safeguards researchers from using inconsistent subjective data. In this way, it makes sure

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Section: Related Workmentioning

confidence: 99%

Describing Subjective Experiment Consistency by p-Value P--P Plot

Nawała

Janowski

Ćmiel

et al. 2020

Proceedings of the 28th ACM International Conference on Multimedia

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“…The existence of a QoE fairness metric does not imply that operators must use only QoE fair assignment of resources, but should they need to, they have a well-founded metric at their disposal. For further discussions related to QoE management, different QoE metrics and fairness, the interested reader is referred to Hoßfeld et al [18].…”

Section: Qoe Fairness and Qoe Managementmentioning

confidence: 99%

A new QoE fairness index for QoE management

et al. 2018

Self Cite

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The user-centric management of networks and services focuses on the Quality of Experience (QoE) as perceived by the end user. In general, the goal is to maximize (or at least ensure an acceptable) QoE, while ensuring fairness among users, e.g., in terms of resource allocation and scheduling in shared systems. A problem arising in this context is that the notions of fairness commonly applied in the QoS domain do not translate well to the QoE domain. We have recently proposed a QoE fairness index F, which solves these issues. In this paper, we provide a detailed rationale for it, along with a thorough comparison of the proposed index and its properties against the most widely used QoS fairness indices, showing its advantages. We furthermore explore the potential uses of the index, in the context of QoE management and describe future research lines on this topic.

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“…QoE can change from person to person for the same video, based on the user's personality and current state of mind. Furthermore, it has been argued that identifying the right set of QoE metrics for a given service is hard and can change based on several factors including user diversity [57].…”

Section: Quality Of Service (Qos) and Quality Of Experience (Qoe)mentioning

confidence: 99%

Efficient HTTP-based Adaptive Streaming of Linear and Interactive Videos

Krishnamoorthi¹

2018

Linköping Studies in Science and Technology. Dissertations

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Online video streaming has gained tremendous popularity over recent years and currently constitutes the majority of Internet traffic. As large-scale ondemand streaming continues to gain popularity, several important questions and challenges remain unanswered. This thesis addresses open questions in the areas of efficient content delivery for HTTP-based Adaptive Streaming (HAS) from different perspectives (client, network and content provider) and in the design, implementation, and evaluation of interactive streaming applications over HAS.As streaming usage scales and new streaming services emerge, continuous improvements are required to both the infrastructure and the techniques used to deliver high-quality streams. In the context of Content Delivery Network (CDN) nodes or proxies, this thesis investigates the interaction between HAS clients and proxy caches. In particular, we propose and evaluate classes of content-aware and collaborative policies that take advantage of information that is already available, or share information among elements in the delivery chain, where all involved parties can benefit. Asides from the users' playback experience, it is also important for content providers to minimize users' startup times. We have designed and evaluated different classes of client-side policies that can prefetch data from the videos that the users are most likely to watch next, without negatively affecting the currently watched video. To help network providers to monitor and ensure that their customers enjoy good playback experiences, we have proposed and evaluated techniques that can be used to estimate clients' current buffer conditions. Since several services today stream over HTTPS, our solution is adapted to predict client buffer conditions by only observing encrypted network-level traffic. Our solution allows the operator to identify clients with low-buffer conditions and implement policies that help avoid playback stalls.The emergence of HAS as the de facto standard for delivering streaming content also opens the door to use it to deliver the next generation of streaming services, such as various forms of interactive services. This class of services is gaining popularity and is expected to be the next big thing in entertainment. For the area of interactive streaming, this thesis proposes, models, designs, and evaluates novel streaming applications such as interactive branched videos and multi-video stream bundles. For these applications, we design and evaluate careful prefetching policies that provides seamless playback (without stalls or switching delay) even when interactive branched video viewers defer their choices to the last possible moment and when users switches between alternative streams within multi-video stream bundles. Using optimization frameworks, we design and implement effective buffer management techniques for seamless playback experiences and evaluate several tradeoffs using our policies. Populärvetenskaplig sammanfattningInternet och World Wide Web (WWW) har vuxit till vik...

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No silver bullet: QoE metrics, QoE fairness, and user diversity in the context of QoE management

Cited by 21 publications

References 14 publications

Describing Subjective Experiment Consistency by p-Value P--P Plot

Describing Subjective Experiment Consistency by p-Value P--P Plot

A new QoE fairness index for QoE management

Efficient HTTP-based Adaptive Streaming of Linear and Interactive Videos

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