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arxiv: 1306.0221 · v1 · pith:NAZFL3SPnew · submitted 2013-06-02 · 💻 cs.MM · cs.NI

Survey on QoEQoS Correlation Models For Multimedia Services

classification 💻 cs.MM cs.NI
keywords modelsmultimediaqualitycorrelationexperiencegivennetworkpredict
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This paper presents a brief review of some existing correlation models which attempt to map Quality of Service (QoS) to Quality of Experience (QoE) for multimedia services. The term QoS refers to deterministic network behaviour, so that data can be transported with a minimum of packet loss, delay and maximum bandwidth. QoE is a subjective measure that involves human dimensions; it ties together user perception, expectations, and experience of the application and network performance. The Holy Grail of subjective measurement is to predict it from the objective measurements; in other words predict QoE from a given set of QoS parameters or vice versa. Whilst there are many quality models for multimedia, most of them are only partial solutions to predicting QoE from a given QoS. This contribution analyses a number of previous attempts and optimisation techniquesthat can reliably compute the weighting coefficients for the QoS/QoE mapping.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Edge User Allocation with Dynamic Quality of Service

    cs.DC 2019-07 unverdicted novelty 5.0

    Extends fixed-QoS edge user allocation to dynamic QoS levels and gives optimal plus heuristic algorithms to maximize aggregate QoE.