The Transmission Control Protocol.

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

In this paper, we investigate the problem of optimal content cache management for HTTP adaptive bit rate (ABR) streaming over wireless networks. Specifically, in the media cloud, each content is transcoded into a set of media files with diverse playback rates, and appropriate files will be dynamically chosen in response to channel conditions and screen forms. Our design objective is to maximize the quality of experience (QoE) of an individual content for the end users, under a limited storage budget. Deriving a logarithmic QoE model from our experimental results, we formulate the individual content cache management for HTTP ABR streaming over wireless network as a constrained convex optimization problem. We adopt a two-step process to solve the snapshot problem. First, using the Lagrange multiplier method, we obtain the numerical solution of the set of playback rates for a fixed number of cache copies and characterize the optimal solution analytically. Our investigation reveals a fundamental phase change in the optimal solution as the number of cached files increases. Second, we develop three alternative search algorithms to find the optimal number of cached files, and compare their scalability under average and worst complexity metrics. Our numerical results suggest that, under optimal cache schemes, the maximum QoE measurement, i.e., mean-opinion-score (MOS), is a concave function of the allowable storage size. Our cache management can provide high expected QoE with low complexity, shedding light on the design of HTTP ABR streaming services over wireless networks.

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QoE-Driven Cache Management for HTTP Adaptive Bit Rate Streaming Over Wireless Networks

The immense increase in multimedia-on-demand traffic that refers to audio, video, and images, has drastically shifted the vision of the Internet of Things (IoT) from scalar to Multimedia Internet of Things (M-IoT). IoT devices are constrained in terms of energy, computing, size, and storage memory. Delay-sensitive and bandwidth-hungry multimedia applications over constrained IoT networks require revision of IoT architecture for M-IoT. This paper provides a comprehensive survey of M-IoT with an emphasis on architecture, protocols, and applications. This article starts by providing a horizontal overview of the IoT. Then, we discuss the issues considering the characteristics of multimedia and provide a summary of related M-IoT architectures. Various multimedia applications supported by IoT are surveyed, and numerous use cases related to road traffic management, security, industry, and health are illustrated to show how different M-IoT applications are revolutionizing human life. We explore the importance of Quality-of-Experience (QoE) and Quality-of-Service (QoS) for multimedia transmission over IoT. Moreover, we explore the limitations of IoT for multimedia computing and present the relationship between the M-IoT and emerging technologies including event processing, feature extraction, cloud computing, Fog/Edge computing and Software-Defined-Networks (SDNs). We also present the need for better routing and Physical-Medium Access Control (PHY-MAC) protocols for M-IoT. Finally, we present a detailed discussion on the open research issues and several potential research areas related to emerging multimedia communication in IoT.

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Multimedia Internet of Things: A Comprehensive Survey

With the move towards converged all-IP wireless network environments, managing end-user Quality of Experience (QoE) poses a challenging task, aimed at meeting high user expectations and requirements regarding reliable and cost-effective communication, access to any service, anytime and anywhere, and across multiple operator domains. In this paper, we give a survey of state-of-the-art research activities addressing the field of QoE management, focusing in particular on the domain of wireless networks and addressing three management aspects: QoE modeling, monitoring and measurement, and adaptation and optimization. Furthermore, we identify and discuss the key aspects and challenges that need to be considered when conducting research in this area.

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Survey and Challenges of QoE Management Issues in Wireless Networks

A new reference-free, objective, video quality prediction model that takes into account video content type to predict the quality of streamed high efficiency video coding (HEVC) encoded video sequences is proposed Research has shown that for the same encoder settings and network quality of service (NQoS), the video quality differs for different types of video content  This indicates that, in addition to encoder settings and NQoS, there may be other key parameters that impact video quality In this work, we hypothesized that video content type is one of the key parameters that may impact the quality of streamed videos Based on this assertion, temporal information is extracted from the motion vector (MV) information inherent in the encoded video bitstreams and spatial information is extracted from the quantisation parameter (QP) and the number of bits (Bits) of coded intra (I) and predictive (P) frames to develop a metric that quantifies the content type of different video sequences  The content type metric is subsequently used together with encoding QP setting and network packet loss rate (PLR) to develop a reference -free objective video quality prediction model for streamed HEVC encoded video sequences This model has an accuracy of 92% when the model predicted values of sequences not used in model derivation are compared with mean opinion score (MOS) obtained through subjective method

Content-Based Video Quality Prediction for HEVC Encoded Videos Streamed Over Packet Networks

The explosion of enhanced applications such as live video streaming, video gaming and Virtual Reality calls for efforts to optimize transport protocols to manage the increasing amount of data traffic on future 5G networks. Through bandwidth aggregation over multiple paths, the Multi-Path Transmission Control Protocol (MPTCP) can enhance the performance of network applications. MPTCP can split a large multimedia flow into subflows and apply a congestion control mechanism on each subflow. Segment Routing (SR), a promising source routing approach, has emerged to provide advanced packet forwarding over 5G networks. In this paper, we explore the utilization of MPTCP and SR in SDN-based networks to improve network resources utilization and end- user's QoE for delivering multimedia services over 5G networks. We propose a novel QoE-aware, SDN- based MPTCP/SR approach for service delivery. In order to demonstrate the feasibility of our approach, we implemented an intelligent QoE- centric Multipath Routing Algorithm (QoMRA) on an SDN source routing platform using Mininet and POX controller. We carried out experiments on Dynamic Adaptive video Steaming over HTTP (DASH) applications over various network conditions. The preliminary results show that, our QoE-aware SDN- based MPTCP/SR scheme performs better compared to the conventional TCP approach in terms of throughput, link utilization and the end-user's QoE.

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A Novel QoE-Centric SDN-Based Multipath Routing Approach for Multimedia Services over 5G Networks

The LTE specification provides Quality of Service (QoS) of multimedia services with fast connectivity, high mobility, and security. However, 3GPP specifications have not defined scheduling algorithms to support real-time and non-realtime application services, this has led to the development of a variety of scheduling algorithms in the recent years. Performance is a key factor for assessing the scheduling algorithms. However, the performance analysis and evaluation for existing scheduling algorithms are limited to QoS parameters (e.g. in terms of throughput, packet loss and delay) and/or fairness metrics. It is not clear how these scheduling algorithms perform in terms of Quality of Experience (QoE) metrics (e.g. MOS score) which are more closely linked with end user experience or user perceived quality. In this paper, we investigate and evaluate the performance of three popular LTE downlink schedulers (proportional fairness (PF), exponential proportional fairness (EXP-PF), and modified largest weight delay first (M-LWDF)) in terms of QoE metric (i.e. MOS score) in addition to normal QoS metrics (e.g. packet loss and delay) for VoIP applications. Simulation results (based on LTE-Sim) show that the best suitable downlink scheduling algorithm is MLWDF, which has short end-to end delay (less than 50ms) and allowing maximum number of user access (more than 50 users) at acceptable MOS score (MOS over 3.5). The widely used scheduling algorithm (PF) will increase its end-to-end delay over 200ms, when number of user access is over 30. This will limit its application for VoIP when user access number increases. This work would help to assist the design and development of QoE-driven scheduling algorithms for mobile multimedia applications in the future.

QoE-based performance evaluation of scheduling algorithms over LTE

Network quality of service (NQoS) of IP networks is unpredictable and impacts the quality of networked multimedia services. Adaptive voice and video schemes are therefore vital for the provision of voice over IP (VoIP) services for optimised quality of experience (QoE). Traditional adaptation schemes based on NQoS do not take perceived quality into consideration even though the user is the best judge of quality. Additionally, uncertainties inherent in NQoS parameter measurements make the design of adaptation schemes difficult and their performance suboptimal. This paper presents a QoE-driven adaptation scheme for voice and video over IP to solve the optimisation problem to provide optimal QoE for networked voice and video applications. The adaptive VoIP architecture was implemented and tested both in NS2 and in an Open IMS Core network to allow extensive simulation and test-bed evaluation. Results show that the scheme was optimally responsive to available network bandwidth and congestion for both voice and video and optimised delivered QoE for different network conditions, and is friendly to TCP traffic.

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

In this paper, we present a novel QoE-aware SDN/NFV system by utilizing and integrating Multi-path TCP (MPTCP) and Segment Routing (SR) paradigms We propose a QoE-based Multipath Source Routing (QoEMuSoRo) algorithm that achieve an optimized end-to-end QoE for the end-user by forwarding MPTCP subflows using SR over SDN/NFV We implement and validate the proposed scheme through DASH experiments using Mininet and POX controller To demonstrate the effectiveness of our proposal, we compare the performance of our QoE-aware MPTCP SDN/NFV SR-based proposal, the MPTCP and regular TCP in terms of system throughput and the end-user's QoE Preliminary results shows that, our approach outperforms the other aforementioned methods

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Is-Haka Mkwawa

Papers

Content-Based Video Quality Prediction for HEVC Encoded Videos Streamed Over Packet Networks

A Novel QoE-Centric SDN-Based Multipath Routing Approach for Multimedia Services over 5G Networks

QoE-based performance evaluation of scheduling algorithms over LTE

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

QualitySDN: Improving Video Quality using MPTCP and Segment Routing in SDN/NFV