Abstract
When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service, i.e., the user’s quality of experience (QoE). However, the two are not independent from each other and their relationship has to be studied through metrics that go beyond the typical network parameters. To better explore the value of assessing QoE alongside QoS in high-speed, lossy networks, this paper presents an experimental methodology to understand the relation between network QoS onto service QoE, with the aim to perform a combined network-service assessment. Using video streaming services as the test-case (given their extended usage nowadays), in this paper, we provide studies on three network-impaired video-sets with the aim to provide a comprehensive evaluation of the effects of networks on video quality. First, the ReTRIeVED video set provides the means to understand the most impairing effects on networks. Furthermore, it triggered the idea to create our own sets, specialized in the most impairing conditions for 2-D and 3-D: the LIMP Video Quality Database and the 3-D-HEVC-Net Video Quality Database. Our study and methodology are meant to provide service providers with the means to pinpoint the working boundaries of their video-sets in face of different network conditions. At the same time, network operators may use our findings to predict how network control policies affect the user’s perception of the service.
Highlights
Satisfying users, devices and services’ requirements is fundamental to successfully manage an ever-growing world-wide wireless network [1]
When dealing with lossy networks, a mere Quality of Service (QoS)-based analysis comes insufficient. That in this case quality emerges as an end-to-end factor, for it is sensitive to the end-user perception of the overall service, i.e. the user’s experienced quality (QoE)
To better explore the value of assessing Quality of Experience (QoE) alongside QoS in high-speed, lossy networks, in this work we have presented an experimental, systematic, general evaluation methodology to map QoS onto QoE
Summary
Satisfying users, devices and services’ requirements is fundamental to successfully manage an ever-growing world-wide wireless network [1]. New streaming protocols increase bandwidth requirements and transmission complexity, which are critical elements for service and network providers [7] In this type of services the relation between QoS parameters and their effect on the experienced quality becomes more challenging. The effect of the QoS impairments on the user’s perceived quality will heavily depend on the transmission protocol used for streaming This means that QoE has to be modeled in a protocol-dependent way. We present a general experimental methodology to assess the effects of QoS on QoE for RTP-based video streaming services.
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