QoE Management

The increasing consumption of multimedia services and the demand of high-quality services from customers has triggered a fundamental change in how we administer networks in terms of abstraction, separation, and mapping of forwarding, control and management aspects of services. The industry and academia are embracing 5G as the future network capable to support next generation vertical applications with different service requirements. To realize this vision in 5G network, the physical network has to be sliced into multiple isolated logical networks of varying sizes and structures which are dedicated to different types of services based on their requirements with different characteristics and requirements (e.g., a slice for massive IoT devices, smartphones or autonomous cars, etc.). Softwarization using Software-Defined Networking (SDN) and Network Function Virtualization (NFV)in 5G networks are expected to fill the void of programmable control and management of network resources. In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.

Dynamic Adaptive Streaming over HTTP (DASH) enhances the Quality of Experience (QoE) for users by automatically switching quality levels according to network conditions. Various adaptation schemes have been proposed to select the most suitable quality level during video playback. Adaptation schemes are currently based on the measured TCP throughput received by the video player. Although video buffer can mitigate throughput fluctuations, it does not take into account the effect of the transition of quality levels on the QoE. In this paper, we propose a QoE-aware DASH system (or QDASH) to improve the user-perceived quality of video watching. We integrate available bandwidth measurement into the video data probes with a measurement proxy architecture. We have found that our available bandwidth measurement method facilitates the selection of video quality levels. Moreover, we assess the QoE of the quality transitions by carrying out subjective experiments. Our results show that users prefer a gradual quality change between the best and worst quality levels, instead of an abrupt switching. Hence, we propose a QoE-aware quality adaptation algorithm for DASH based on our findings. Finally, we integrate both network measurement and the QoE-aware quality adaptation into a comprehensive DASH system.

This chapter discusses prospects of QoE management for future networks and applications. After motivating QoE management, it first provides an introduction to the concept by discussing its origins, key terms and giving an overview of the most relevant existing theoretical frameworks. Then, recent research on promising technical approaches to QoE-driven management that operate across different layers of the networking stack is discussed. Finally, the chapter provides conclusions and an outlook on the future of QoE management with a focus on those key enablers (including cooperation, business models and key technologies) that are essential for ultimately turning QoE-aware network and application management into reality.

Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational.

The ever-increasing network traffic and user expectations at reduced cost make the delivery of high Quality of Experience (QoE) for multimedia services more vital than ever in the eyes of Internet Service Providers (ISPs). Real-time quality monitoring, with a Multimed Tools Appl focus on the user, has become essential as the first step in cost-effective provisioning of high quality services. With the recent changes in the perception of user privacy, the rising level of application-layer encryption and the introduction and deployment of virtualized networks, QoE monitoring solutions need to be adapted to the fast changing Internet landscape. In this contribution, we provide an overview of state-of-the-art quality monitoring models and probing technologies, and highlight the major challenges ISPs have to face when they want to ensure high service quality for their customers.

The provisioning of the quality to end users is a major objective for the successful deployment of multimedia services over the Internet. It is more and more evident from past research and service deployments that such an objective often requires a collaboration among the different parties that are involved in the delivery of the service. This paper specifically focuses on the cooperation between the Over-The-Top (OTTs) and the Internet Service Providers (ISPs) and propose a novel service delivery approach that is purely driven by the Quality of Experience (QoE) provided to the final common users. Initially, we identify the need of the collaboration among the OTTs and the ISPs where we not only highlight some of the enterprise level motivations (revenue generation) but also the technical aspects which require collaboration. Later, we provide a reference architecture with the required modules and vertical interfaces for the interaction among the OTTs and the ISPs. Then, we provide a collaboration model where we focus on the modeling of the revenue, whose maximization drives the collaboration. The revenue is considered to be dependent on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlight how the proposed strategy increases the revenue generation and QoE for the OTTs and the ISPs hence providing a ground for ISP to join the loop of revenue generation between OTTs and users.

The highly demanding Over-The-Top (OTT) multi-media applications pose increased challenges to Internet Service Providers (ISPs) for assuring a reasonable Quality of Experience (QoE) to their customers due to lack of flexibility, agility and scal-ability in traditional networks. The future networks are shifting towards the cloudification of the network resources via Software Defined Networks (SDN) and Network Function Virtualization (NFV). This will equip ISPs with cutting-edge technologies to provide service customization during service delivery and offer QoE which meets customers' needs via intelligent QoE control and management approaches. Towards this end, we provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high-level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality , mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

The objective of this work is the investigation of a possible collaboration between Over-The-Top (OTTs) service providers and Internet Service Providers (ISPs), which is centered around the Quality of Experience (QoE). Initially, we define a reference architecture with the required modules and interfaces for the interaction between the two providers. Then, we focus on the modeling of the revenue, whose maximization drives the collaboration. It is considered as depending on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlights how the proposed strategy increases the revenue generation and QoE for both players hence providing a ground for ISP to join the loop of revenue generation between OTT and users.

—In this work, we propose a QoE-aware collaboration approach between Over-The-Top providers (OTT) and Internet Service Providers (ISP) based on the maximization of the profit by considering the user churn of Most Profitable Customers (MPCs), which are classified in terms of the Customer Lifetime Value (CLV). The contribution of this work is multifold. Firstly, we investigate the different perspectives of ISPs and OTTs regarding QoE management and why they should collaborate. Secondly, we investigate the current ongoing collaboration scenarios in the multimedia industry. Thirdly, we propose the QoE-aware collaboration framework based on the CLV, which includes the interfaces for information sharing between OTTs and ISPs and the use of Content Delivery Networks (CDN) and surrogate servers. Finally, we provide simulation results aiming at demonstrating the higher profit is achieved when collaboration is introduced, by engaging more MPCs with respect to current solutions. Index Terms—Quality of Experience (QoE), Over-The-Top (OTT) service, Internet Service Provider (ISP), Customer Lifetime Value (CLV).

—This paper focuses on passive Quality of Experience (QoE) monitoring at user end devices as a necessary activity of the ISP (Internet Service Provider) for an effective quality-based service delivery. The contribution of the work is threefold. Firstly, we highlight the opportunities and challenges for the QoE monitoring of the Over-The-Top (OTT) applications while investigating the available interfaces for monitoring the deployed applications at the end-device. Secondly, we propose a multilayer passive QoE monitor for OTT applications at the user terminal with ISPs prospect. Five layers are considered: user profile, context, resource, application and network layers. Thirdly, we consider YouTube as a case study for OTT video streaming applications in our experiments for analyzing the impact of the monitoring cycle on the user end device resources, such as the battery, RAM and CPU utilization at end user device.

—This work is based on the investigation of the passive Quality of Experience (QoE) monitoring of Over-The-Top (OTT) applications at the user terminal with the perspective of the Internet Service Provider (ISP). The contribution is multi-fold. Firstly, we investigate the advantages and drawbacks of QoE monitoring at the user terminal by highlighting the roles of the different entities involved in multimedia service delivery, i.e., users, OTTs and ISPs. Secondly, a survey is conducted related to user's privacy and preferences with reference to the installation of monitoring probes at the terminal. The analysis of survey results highlights the applicability of the approach in terms of users' willingness to have probes at their terminals in exchange for higher quality, discounts or extra data usage. Thirdly, we propose a multi-layered passive monitoring approach at the user terminal which considers the activation of the probes only in case quality degradation is revealed (in an event-based fashion), in contrast to conventional passive monitoring solutions whose probes send monitored data to the collection centers on regular intervals basis (constant frequency). As a case study, YouTube is considered as video streaming service in our experiments to investigate the effectiveness of the proposed approach. Index Terms—Quality of Experience (QoE), QoE-centric network and application management, QoE Monitoring.

Over the last decade or so, significant research has
focused on defining Quality of Experience (QoE) of Multimedia Systems and identifying the key factors that collectively determine it. Some consensus thus exists as to the role of System Factors, Human Factors and Context Factors. In this paper, the notion of context is broadened to include information gleaned from simultaneous out-of-band channels, such as social network trend analytics, that can be used if interpreted in a timely manner, to help further optimise QoE. A case study involving simulation of HTTP adaptive streaming (HAS) and load balancing in a content distribution network (CDN) in a flash crowd scenario is presented with encouraging results.

The Quality of Experience (QoE) management procedures for multimedia services benefit from an effective collaboration between the Mobile Network Operators (MNOs) and the Over-The-Top (OTT) service providers as the former can allocate the appropriate network resources to the users and the latter has access to key influence factors for having a proper view of the provided QoE. One successful collaboration model is the zero-rated data rate approach, according to which the MNO limits the data rate of the users towards the collaborating OTT applications with the benefit for the user that the generated traffic is not counted in her monthly contract data limit. Accordingly, the MNO may reduce the network congestion, and the users are encouraged to select the collaborating OTT applications. Though, this approach does not consider the resulting QoE, which may vary significantly from one user to another even if the same throughput is given. Based on this consideration, in this paper, we proposed the zero-rated QoE approach, according to which the limit is introduced in terms of QoE rather than throughput. This clearly requires a stronger collaboration between the OTT and the MNO, as the first has to give access to the second to quality influence factors and the latter to allocate resources according to the predicted QoE. The contributions of this paper are: the introduction of the novel zero-rated QoE approach with particular reference to video streaming services; the definition of novel components in the 3GPP architecture so that this approach can be introduced; the definition of the algorithm for the allocation of the appropriate radio resources to each user; a simulation analysis where the proposed approach is compared with respect to the former zero-rated approach, which shows significant improvements in terms of average provided quality and quality fairness at the same overall throughput.

Recent studies implemented collaboration between Over-The-Top (OTT) service and Internet Service Provider (ISP) concerning information exchange between the providers. This information is used to accurately predict the delivered Quality of Experience (QoE) and decide the correcting network management actions. In this scenario, we aim to investigate the impact of the frequency of information exchange between OTT and ISP on end users' QoE and network resource utilization. Firstly, we propose our information-centric QoE-aware collaborative service management approach by defining the type of information to be acquired and exchanged between OTT and ISP. Secondly, we present our platform based on the Software-Defined Networking (SDN) paradigm, which we used to conduct the experiments. Finally, we conduct experiment results that compare the proposed collaborative approach with the case of no collaboration when the sampling interval of information exchange varies between 2 s and 32 s. The experiment results show that a higher frequency of information exchange may result in better network reliability and delivered QoE, but a frequency higher than 1/4 Hz may not further improve the delivered QoE.

Cloud gaming is an emerging technology that combines cloud computing with computer games. Compared to traditional gaming, its core advantages include ease of development/deployment for developers, and lower technology costs for users given the potential to play on thin client devices. In this chapter, we firstly describe the approach, and then focus on the impact of latency, known as lag, on Quality of Experience, for so-called First Person Shooter games. We outline our approach to lag compensation whereby we equalize within reason the up and downlink delays in real-time for all players. We describe the testbed in detail, the open source Gaming Anywhere platform, the use of NTP to synchronise time, the network emulator and the role of the centralized log server. We then present results that firstly validate the mechanism and also use small scale and preliminary subjective tests to assess and prove its performance. We conclude the chapter by outlining ongoing and future work.

—This paper deals with a video content classification based on spatial and temporal information. The main goal of the paper is to find out whether the non-expert test subjects are able to correctly recognize the spatial and temporal information and how precise is the corresponding parameterization of video content based on these two attributes. Moreover, how well do the objective values provided by the tool deployed in this experiment correlate with the subjective ones. The subjective measurement has shown that the non-expert test subjects are able to correctly recognize the spatial and temporal information only for the extreme scenes in terms of the spatial and temporal information but have experienced some problems when it comes to a more granular classification. When it comes to the objective assessment, the SI and TI values provided by the tool used in this experiment correlate quite well with the subjective data obtained from the basic test for the spatial information.

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