Mechanisms for QoE optimisation of video traffic: a review paper

Transmission of video traffic over the Internet has grown exponentially in the past few years with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise the Quality of Experience (QoE) of end users’ video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted

Seamless multimedia delivery within a heterogeneous wireless networks environment: are we there yet?

The increasing popularity of live video streaming from mobile devices such as Facebook Live, Instagram Stories, Snapchat, etc. pressurises the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of Quality of Experience (QoE) as the basis for network control, customer loyalty and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users’ quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: adaptation, energy efficiency and multipath content delivery. Discussions, challenges and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots

Quality-Driven Cross-Layer Protocols for Video Streaming over Vehicular Ad-Hoc Networks

The emerging vehicular ad-hoc networks (VANETs) offer a variety of applications and new potential markets related to safety, convenience and entertainment, however, they suffer from a number of challenges not shared so deeply by other types of existing networks, particularly, in terms of mobility of nodes, and end-to-end quality of service (QoS) provision. Although several existing works in the literature have attempted to provide efficient protocols at different layers targeted mostly for safety applications, there remain many barriers to be overcome in order to constrain the widespread use of such networks for non-safety applications, specifically, for video streaming: 1) impact of high speed mobility of nodes on end-to-end QoS provision; 2) cross-layer protocol design while keeping low computational complexity; 3) considering customer-oriented QoS metrics in the design of protocols; and 4) maintaining seamless single-hop and multi-hop connection between the destination vehicle and the road side unit (RSU) while network is moving. This thesis addresses each of the above limitations in design of cross-layer protocols for video streaming application. 1) An adaptive MAC retransmission limit selection scheme is proposed to improve the performance of IEEE 802.11p standard MAC protocol for video streaming applications over VANETs. A multi-objective optimization framework, which jointly minimizes the probability of playback freezes and start-up delay of the streamed video at the destination vehicle by tuning the MAC retransmission limit with respect to channel statistics as well as packet transmission rate, is applied at road side unit (RSU). Two-hop transmission is applied in zones in which the destination vehicle is not within the transmission range of any RSU. In the multi-hop scenario, we discuss the computation of access probability used in the MAC adaptation scheme and propose a cross-layer path selection scheme; 2) We take advantage of similarity between multi-hop urban VANETs in dense traffic conditions and mesh connected networks. First, we investigate an application-centric routing scheme for video streaming over mesh connected overlays. Next, we introduce the challenges of urban VANETs compared to mesh networks and extend the proposed scheme in mesh network into a protocol for urban VANETs. A classification-based method is proposed to select an optimal path for video streaming over multi-hop mesh networks. The novelty is to translate the path selection over multi-hop networks to a standard classification problem. The classification is based on minimizing average video packet distortion at the receiving nodes. The classifiers are trained offline using a vast collection of video sequences and wireless channel conditions in order to yield optimal performance during real time path selection. Our method substantially reduces the complexity of conventional exhaustive optimization methods and results in high quality (low distortion). Next, we propose an application-centric routing scheme for real-time video transmission over urban multi-hop vehicular ad-hoc network (VANET) scenarios. Queuing based mobility model, spatial traffic distribution and prob- ability of connectivity for sparse and dense VANET scenarios are taken into consideration in designing the routing protocol. Numerical results demonstrate the gain achieved by the proposed routing scheme versus geographic greedy forwarding in terms of video frame distortion and streaming start-up delay in several urban communication scenarios for various vehicle entrance rate and traffic densities; and 3) finally, the proposed quality-driven routing scheme for delivering video streams is combined with a novel IP management scheme. The routing scheme aims to optimize the visual quality of the transmitted video frames by minimizing the distortion, the start-up delay, and the frequency of the streaming freezes. As the destination vehicle is in motion, it is unrealistic to assume that the vehicle will remain connected to the same access router (AR) for the whole trip. Mobile IP management schemes can benefit from the proposed multi-hop routing protocol in order to adapt proxy mobile IPv6 (PMIPv6) for multi-hop VANET for video streaming applications. The proposed cross-layer protocols can significantly improve the video streaming quality in terms of the number of streaming freezes and start-up delay over VANETs while achieving low computational complexity by using pattern classification methods for optimization

Network reputation-based quality optimization of video delivery in heterogeneous wireless environments

The mass-market adoption of high-end mobile devices and increasing amount of video traffic has led the mobile operators to adopt various solutions to help them cope with the explosion of mobile broadband data traffic, while ensuring high Quality of Service (QoS) levels to their services. Deploying small-cell base stations within the existing macro-cellular networks and offloading traffic from the large macro-cells to the small cells is seen as a promising solution to increase capacity and improve network performance at low cost. Parallel use of diverse technologies is also employed. The result is a heterogeneous network environment (HetNets), part of the next generation network deployments. In this context, this thesis makes a step forward towards the “Always Best Experience” paradigm, which considers mobile users seamlessly roaming in the HetNets environment. Supporting ubiquitous connectivity and enabling very good quality of rich mobile services anywhere and anytime is highly challenging, mostly due to the heterogeneity of the selection criteria, such as: application requirements (e.g., voice, video, data, etc.); different device types and with various capabilities (e.g., smartphones, netbooks, laptops, etc.); multiple overlapping networks using diverse technologies (e.g., Wireless Local Area Networks (IEEE 802.11), Cellular Networks Long Term Evolution (LTE), etc.) and different user preferences. In fact, the mobile users are facing a complex decision when they need to dynamically select the best value network to connect to in order to get the “Always Best Experience”. This thesis presents three major contributions to solve the problem described above: 1) The Location-based Network Prediction mechanism in heterogeneous wireless networks (LNP) provides a shortlist of best available networks to the mobile user based on his location, history record and routing plan; 2) Reputation-oriented Access Network Selection mechanism (RANS) selects the best reputation network from the available networks for the mobile user based on the best trade-off between QoS, energy consumptions and monetary cost. The network reputation is defined based on previous user-network interaction, and consequent user experience with the network. 3) Network Reputation-based Quality Optimization of Video Delivery in heterogeneous networks (NRQOVD) makes use of a reputation mechanism to enhance the video content quality via multipath delivery or delivery adaptation