A study of learning experience with a dash-based multimedia delivery system

In order to create an improved learning experience in variable network delivery conditions, multimedia content adjustment is performed when delivered over existing network environments. This paper introduces a study of user learning when multimedia-based study material is distributed at different quality levels in the context of the European Horizon2020 project NEWTON. This paper studies the learning experience with multimedia when employing an MPEG-DASH-based adaptive multimedia delivery in a real life subjective experiment with 88 Data Network students from two Irish and Slovak universities

QoE Driven Multimedia Service Schemes in Wireless Networks Resource Allocation: Evolution from Optimization, Game Theory, to Economics

In order to deal with the Quality of Experience (QoE) improvement issue in the wireless networks services. In this dissertation we first investigated the Device to Device (D2D) relaying approach in the conventional Base Station (BS) to User Equipment (UE) two entities multimedia service system. In this part, the Multiple Input Multiple Output (MIMO) technology will be implemented in the D2D communication. Furthermore, factors such as the multimedia content distribution (i.e., Quad-tree fractal image compression method), the power allocation strategy, and modulation size are jointly considered to improve the QoE performance and energy efficiency. In addition, the emerging Non-Orthogonal Multiple Access (NOMA) transmission method is becoming very popular and being considered as one of the most potential technologies for the next generation of wireless networks. For the purpose of improving the QoE of UE in the wireless multimedia service, the power allocation method and the corresponding limitations are studied in detail in the wireless system where the traditional Orthogonal Multiple Access (OMA) technology and the promising NOMA technology are compared. At last, facing the real business model in the wireless network services, where the Content Provider (CP), Wireless Carrier (WC), and UE are included, we extend on work from the conventional BS-UE two entities research model to the CP-WC-UE three entities model. More specifically, a generalized best response Smart Media Pricing (SMP) method is studied in this dissertation. In our work, the CP and WC are treated as the service provider alliance. The SMP approach and the game theory are utilized to determine the data length of UE and the data price rate determined by the CP-WC union. It is worth pointing out that the concavity of utility function is no longer necessary for seeking the game equilibrium under the proposed best response game solution. Numerical simulation results also validate the system performance improvement of our proposed transmission schemes

LTE 네트워크에서 비디오 전달 서비스의 성능 향상

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 2. 권태경.LTE includes an enhanced multimedia broadcast/multicast service(eMBMS)but delay-sensitive real-time video streaming requires the combination of efficient handling of wireless link bandwidth and reduced handover delays, which remains a challenge. The 3GPP standard introduces a Multimedia Broadcast and multicast service over a Single Frequency Network (MBSFN) area which is a group of base stations broadcasting the same multicast packets. It can reduce the handover delay within MBSFN areas, but raises the traffic load on LTE networks. In this dissertation, we first presents an MBSFN architecture based on location management areas (LMAs) which can increase the sizes of MBSFN areas to reduce the average handover delay without too much bandwidth waste. An analytical model is developed to quantify service disruption time, bandwidth usage, and blocking probability for different sizes of MBSFN areas and LMAs while considering user mobility, user distribution, and eMBMS session popularity. Using this model, we also propose how to determine the best sizes of MBSFN areas and LMAs along with performance guarantees. Analytical and simulation results demonstrate that our LMA-based MBSFN scheme can achieve bandwidth-efficient multicast delivery while retaining an acceptable service disruption time. We next propose to transmit the real-time video streaming packets of eMBMSs proactively and probabilistically, so that the average handover delay perceived by a user is stochastically guaranteed. To quantify the tradeoff between the perceived handover delay and the bandwidth overhead of proactive transmissions, we develop an analytical model considering user mobility, user distribution, and session popularity. Comprehensive simulation is carried out to verify the analysis. On the other hand, hypertext transfer protocol (HTTP) based adaptive streaming (HAS) is expected to be a dominant technique for non-real-time video delivery in LTE networks. In this dissertation, we first analyze the root causes of the problems of the existing HAS techniques. Based on the insights gained from our analysis, we propose a network-side HAS solution to provide a fair, efficient, and stable video streaming service. The key characteristics of our solution are: (i) unification of video- and data-users into a single utility framework, (ii) direct rate control conveying the assigned rates to the video client through overwritten HTTP Response messages, and (iii) rate allocation for stability by a stateful approach. By the experiments conducted in a real LTE femtocell network, we compare the proposed solution with state-of-the-art HAS solutions. We reveal that our solution (i) enhances the average video bitrates, (ii) achieves the stability of video quality, and (iii) supports the control of the balance between video- and data-users.Abstract i I. Introduction 1 II. Performance Improvements on Real-time Multicast Video Delivery 4 2.1 Introduction 4 2.2 Related Work 7 2.3 Location Management Area Based MBSFN 9 2.3.1 Location Management Area (LMA) 10 2.3.2 Handover Delays 12 2.3.3 LMA-based MBSFN Area Planning 12 2.4 Performance Analysis 14 2.4.1 Disruption Time 17 2.4.2 Bandwidth Usage 20 2.4.3 Blocking Probability 21 2.5 Numerical Results 23 2.5.1 Effect of NZ and NL 24 2.5.2 Deciding NZ and NL 27 2.5.3 Effects of v and rho* 31 2.5.4 Effect of alpha 32 2.6 Simulation Results 35 2.7 Conclusion 37 III. Proactive Approach for LMA-based MBSFN 39 3.1 Introduction 39 3.2 Network and MBSFN Modeling 41 3.3 Proactive LMA-based MBSFN 44 3.3.1 Problem Formulation 45 3.3.2 Overall procedure 47 3.4 Performance Evaluation 48 3.4.1 Simulation Setup 48 3.4.2 Computation of pi 50 3.4.3 Simulation Results 51 3.5 Conclusions 53 IV. Performance Improvements on HTTP Adaptive Video Streaming 55 4.1 Introduction 55 4.2 Related Work 57 4.3 Problem Definition 59 4.4 Utility-aware Network-side Streaming Approach 62 4.4.1 Streaming Proxy (SP) 63 4.4.2 Message Flows 65 4.4.3 Characteristics 67 4.5 Bitrate Assignment 68 4.5.1 Bitrate Calculation 69 4.5.2 Enhancing Stability 70 4.5.3 Algorithm for Continuous Bitrates 71 4.5.4 Handling the Bottleneck of Wired Networks 71 4.6 Simulation 73 4.6.1 Static Scenario 73 4.6.2 Mobile Scenarios 75 4.6.3 Algorithm for Continuous Bitrates 77 4.7 Experiments 78 4.7.1 Implementation of DASH Player 79 4.7.2 Implementation of eNB 80 4.7.3 Implementation of Streaming Proxy 83 4.7.4 Experimental Results 83 4.8 Conclusion 87 V. Summary & FutureWork 89 Bibliography 92Docto

Video QoE Estimation using Network Measurement Data

More than even before, last-mile Internet Service Providers (ISPs) need to efficiently provision and manage their networks to meet the growing demand for Internet video (expected to be 82% of the global IP traffic in 2022). This network optimization requires ISPs to have an in-depth understanding of end-user video Quality of Experience (QoE). Understanding video QoE, however, is challenging for ISPs as they generally do not have access to applications at end user devices to observe key objective metrics impacting QoE. Instead, they have to rely on measurement of network traffic to estimate objective QoE metrics and use it for troubleshooting QoE issues. However, this can be challenging for HTTP-based Adaptive Streaming (HAS) video, the de facto standard for streaming over the Internet, because of the complex relationship between the network observable metrics and the video QoE metrics. This largely results from its robustness to short-term variations in the underlying network conditions due to the use of the video buffer and bitrate adaptation. In this thesis, we develop approaches that use network measurement to infer video QoE. In developing inference approaches, we provide a toolbox of techniques suitable for a diversity of streaming contexts as well as different types of network measurement data. We first develop two approaches for QoE estimation that model video sessions based on the network traffic dynamics of the HAS protocol under two different streaming contexts. Our first approach, MIMIC, estimates unencrypted video QoE using HTTP logs. We do a large-scale validation of MIMIC using ground truth QoE metrics from a popular video streaming service. We also deploy MIMIC in a real-world cellular network and demonstrate some preliminary use cases of QoE estimation for ISPs. Our second approach is called eMIMIC that estimates QoE metrics for encrypted video using packet-level traces. We evaluate eMIMIC using an automated experimental framework under realistic network conditions and show that it outperforms state-of-the-art QoE estimation approaches. Finally, we develop an approach to address the scalability challenges of QoE inference. We leverage machine learning to infer QoE from coarse-granular but light-weight network data in the form of Transport Layer Security (TLS) transactions. We analyze the scalability and accuracy trade-off in using such data for inference. Our evaluation shows that that the TLS transaction data can be used for detecting video performance issues with a reasonable accuracy and significantly lower computation overhead as compared to packet-level traces.Ph.D