# Crowdsourcing Framework for QoE-Aware SD-WAN +
###### Abstract
Objective QoE assessment techniques are based on network analysis and technical comparisons that aim to produce a quantitative estimation of quality. This is tightly related to the QoS of an application or service. For instance, peak signal-to-noise ratio (PSNR) is considered an objective approach for measuring quality, as it assesses how much similarity exists between two different video images. It is widely used in video streaming assessment [3], where a higher PSNR value denotes higher similarity between the original and received video images. Subjective techniques are based on user interaction and feedback. A common subjective approach is mean opinion score (MOS) based on a quality rating system on a scale from 1 to 5, where 1 stands for 'bad' and 5 stands for 'excellent', with 3.5 representing the minimum acceptable threshold for a video MOS [4]. MOS scaling still may give room for inaccurate representation of user perception [5], due to the non-similarity of the scale interpretation by different participants; as such, other approaches based on a simple like/dislike of the service quality have been proposed to better capture user perception. While subjective approaches reflect users' perception more directly and accurately, they are expensive to roll out because such QoE assessments require a large scale of participants in order to obtain reliable results. They are also time-consuming, as traditional QoE experiments are conducted in a controlled lab environment, making it difficult to collect sufficient results from experiments in a limited timeframe [6]. QoE crowdsourcing techniques have been proposed to overcome these constraints, where, taking advantage of employing a diverse group of online participants, getting subjective results becomes relatively cheaper and more efficient than traditional methods. It must be noted that the use of subjective and objective quality assessments is not exclusive; in fact, the two approaches can be used to complement each other. Data collected from users' feedback and from network devices can be analyzed together to better match user perception with network conditions. A software-defined network provides an excellent framework for such data collection and analysis through controller-based applications, which could employ learning techniques to deploy, test, and improve global network decisions in response to degradation of service quality. In terms of transport services, the Real-Time Transport Protocol (RTP), along with Real-Time Control Protocol (RTCP) or Real-Time Streaming Protocol (RTSP), provides a reliable foundation for real-time services [6]. The emergence of software-defined networking (SDN) has promised better control and management of end-to-end service quality in the networks [7]. Leveraging SDN's advantages, such as dynamic programmability, central control, cost efficiency, and adaptability to changes in a networking environment, makes the software-defined wide-area network (SD-WAN) a desirable architecture to control QoE for multimedia streaming applications and services. SD-WAN controllers can make use of QoE assessments collected through user feedback by enhancing and updating streaming routes. Furthermore, SD-WAN controllers incorporate the emerging concept of intent-based networking (IBN), which would allow network administrators to define their QoE requirements in the form of service intents, i.e., as a collection of policies, goals, and network-level performance targets, rather than specific device-level configuration parameters. Such an implementation greatly facilitates the management of service-level QoE requirements for multimedia service delivery. In this paper, a framework is proposed based on a combination of real-time QoE measurement application and QoS quality parameters, which can accommodate a variety of streaming protocols while deployed in an SD-WAN. This framework emphasizes the correlation between QoE and QoS and how the overall user QoE perspective can be affected.