Abstract
Most of the work related to QoE maps objective variables (QoS-related) into a single one that predicts the quality the user perceives. In this paper we present a new approach to model multimedia OTT services, integrating not only the functional aspects of the service but also non-functional variables, which are classified into objective, subjective and business-related. Non-functional metrics might affect the Quality of Service (QoS), Quality of Experience (QoE) and Quality of Business (QoBiz) correspondingly. We also discuss how all these variables can be taken into account to predict the QoE of the service being studied. The functional requirements are modeled into a Timed Extended Finite State Machine (TEFSM), which is augmented with context variables (and their updating functions) representing non-functional requirements related to QoS, QoE and QoBiz. We use these parameters to evaluate the QoE using a trace model derived from the TEFSM previously built.
Highlights
Nowadays, well-known multimedia services like Netflix, Youtube, Spotify or beIN Sports Connect [1] are gaining popularity, since they provide an easy and often cheaper way to access movies and series, video on demand and music respectively
In this paper we propose a framework to estimate Quality of Experience (QoE) of an Over-The-Top Services (OTT) Service based on the formalism of Extended Finite States Machine with timeouts (TEFSM), representing the functional requirements of the service being modeled
1 ... we propose to derive a Timed Extended Finite State Machine (TEFSM) that preserves the functional behavior of the OTT service, and, captures, ... , parameters as corresponding context variables
Summary
Well-known multimedia services like Netflix, Youtube, Spotify or beIN Sports Connect [1] are gaining popularity, since they provide an easy and often cheaper way to access movies and series, video on demand and music respectively. In this work we aim to ensure three main types of quality: the Quality of Experience (QoE) to the user, granting him/her the best service experience; the Quality of Service (QoS), to the service providers avoiding network congestion; and the Quality of Business (QoBiz) to the stakeholders, maximizing the revenues. Meeting all these objectives may not be an easy task due to the high correlation among the variables.
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