Abstract
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.
Highlights
Quality of Experience (QoE) is “the degree of delight or annoyance of the user of an application or service” [26]
The motivation for defining a fairness index comes primarily from the operator’s perspective, as QoE fairness measures can be used to drive resource allocation mechanisms aimed at maximizing the satisfied customer base
We have introduced a definition for a QoE fairness index, and showed that QoE fairness does not, due to the nature of Quality of service (QoS) to QoE mappings for most services, necessarily follow from QoS fairness
Summary
Quality of Experience (QoE) is “the degree of delight or annoyance of the user of an application or service” [26]. It is generally accepted that the quality experienced by a user of a networked service is dependent, in a non-trivial and often non-linear way, on the network’s QoS. From a network operator’s point of view, QoE is an important aspect in keeping customers satisfied, e.g., decreasing churn. This has lead to a number of mechanisms for QoE-driven network resource management, aimed at maintaining quality above a certain threshold for every user (or in some proposals, “premium” users, at least). An issue common to all those efforts is that of dividing the available resources among users so as to maintain a satisfied customer base. We explore (in depth) a notion of QoE fairness, first introduced in our previous work [15],
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