Multimedia streaming is one of the killer applications for cellular communications. Although the 3GPP proposes the Packet-Switched Streaming (PSS) protocol to support the multimedia streaming services, the performances are still not good enough. To improve the performances, most of the researches divide the cellular networks into two parts: the wired network and the wireless network, and focus on the wireless network part. Hence the adaptive streaming was proposed. It utilizes the RTCP feedback in RTP to monitor the wireless network, and makes appropriate transmission parameters adjustments to prevent from buffer underflow and packet loss. But the overall performance may not be only limited by the wireless network part. Also, with high mobility, the link quality may be influenced severely by many factors. Hence, we will evaluate the performance of streaming services over 3G cellular networks on the train of Taiwan high speed railway in this paper and propose a mechanism to improve the performance.

Not long ago streaming video over the Internet included only short clips of low quality video. Now the possibilities seem endless as professional productions are made available in high definition. This explosion of growth is the result of several factors, such as increasing network performance, advancements in video encoding technology, improvements to video streaming techniques, and a growing number of devices capable of handling video. However, despite the improvements to Internet video streaming this paradigm is still evolving. HTTP adaptive streaming involves encoding a video at multiple quality levels then dividing those quality levels into small chunks. The player can then determine which quality level to retrieve the next chunk from in order to optimize video playback when considering the underlying network conditions. This thesis first presents an experimental framework that allows for adaptive streaming players to be analyzed and evaluated. Evaluation is beneficial because there are several concerns with the adaptive video streaming ecosystem such as achieving a high video playback quality while also ensuring stable playback quality. The primary contribution of this thesis is the evaluation of prefetching by a proxy server as a means to improve streaming performance. This work considers an implementation of a proxy server that is functional with the extremely popular Netflix streaming service, and it is evaluated using two Netflix players. The results show its potential to improve video streaming performance in several scenarios. It effectively increases the buffer capacity of the player as chunks can be prefetched in advance of the player's request then stored on the proxy to be quickly delivered once requested. This allows for degradation in network conditions to be hidden from the player while the proxy serves prefetched data, preventing a reduction to the video quality as a result of an overreaction by the player. Further, the proxy can reduce the impact of the bottleneck in the network, achieving higher throughput by utilizing parallel connections to the server.

One of the main challenges in delivering content over the Internet today is the absence of a centralized monitoring and control system [38]. Software Defined Networking has paved the way to provide a much needed control over network traffic. OpenFlow is now being standardized as part of the Open Networking Foundation, and Software Defined Exchanges (SDXes) provide a framework to use OpenFlow for multi-domain routing. Prototype deployments of Software Defined Exchanges have recently come into existence as a platform for Future Internet Architecture to eliminate the need for core routing technology used in today’s Internet. In this work, we look at how application delivery, in particular, Dynamic Adaptive Streaming over HTTP (DASH) and Nowcasting take advantage of a Software Defined Exchange. We compare unsophisticated controllers to more sophisticated ones which we call a ”load balancer” and find that implementing a good controller for inter-domain routing can result in better network utilization and application performance. We then design, develop and evaluate a prototype for a Content Distribution Network (CDN) that uses resources at SDXes to provide higher quality bitrates for a DASH client.

Being able to interact with video streams can be both fun, educational and provide help during disaster situations. However, to achieve the best user experience the interaction must be seamless. This thesis presents the design and implementation of an interface for a media player that allows for users to view multiple video streams of the same event from different geographical positions and angles. The thesis first describes the system design and methods used to implement this kind of media player and explains how to achieve a seemingly good and, to a higher extent, enjoyable video streaming experience. Second, an algorithm is developed for placing each video stream object on the interface's geographic-based map automatically. These objects are placed to ensure the relative positions of the objects compared to the real world. The end result of this project is a proof-of-concept media player which enables a user to see an overview over a geographical streaming area. Presented with the relative location of each stream to the point of interest the player allows the user to click on that stream and switch to viewing the recordings from that point of view. While the resulting player is not yet seamless, the result of this project shows the command-and-control center as initially envisioned. Implementing seamless, uninterrupted, switching between the video streams is outside the scope of this thesis. However, as demonstrated and argued in the thesis, the work done here and the developed software code will allow for easy integration of more advanced prefetching algorithms in future and parallel works.

Adaptive streaming is a popular technique that allows quality adaption for videos based on the current playback conditions. The purpose of this thesis is to investigate how chunks in video files downloaded from YouTube correlate to each other. We investigate how the chunk size characteristics depend on the category and encoding of the video. The main focus is to analyze the chunk sizes of the video, focusing on distinctness between 360$^\circ$ and 2D videos. This is performed using the YouTube API. The videos are downloaded and analysed using youtube-dl and mkv-info. The results show that chunk sizes for adjacent qualities have higher correlation and that videos having a similarity between scenes have higher correlation. In addition, 360$^\circ$ videos differ primarily from regular 2D videos by the amount of qualities used and a generally higher correlation for all qualities.

Thanks to their increasing sophistication and popularity, mobile devices, in the form of smartphones and tablets, have become the fastest growing contributors to Internet traffic. Indeed, smartphones are projected to account for 50% of global Internet traffic by 2017, with the share of mobile video increasing to about 40% of total Internet traffic. As users embrace Internet streaming of video, several studies have found that a small decrease in video quality leads to a substantial increase in viewer abandonment and disengagement rates. To handle the explosive growth in video traffic, Adaptive HTTP streaming, which exploits the prevalence of commodity web servers and content distribution networks, has emerged as the key technology for delivering video to end users. Although a number of systems have been proposed for HTTP video streaming in traditional environments and for fixed clients, existing platforms for video streaming on mobile devices are still in their infancy and do not address the additional challenges often experienced by mobile clients: high fluctuations in network conditions, heterogeneous networking interfaces, multiple form-factors, and limited battery life. In this dissertation, we propose a number of solutions for improving the Quality of Experience of HTTP video streaming on mobile devices. We begin by evaluating the performance of several existing video quality adaptation schemes when deployed on mobile platforms. Through experiments with smartphones in wide-area environments, we assemble several key findings. First, we show that the high fluctuations in network throughput on cellular and Wi-Fi networks impose significant challenges for efficiently architecting the video adaptation scheme. Second, we find significant differences between the performance of the current state-of-the-art schemes in controlled experimental settings and their performance in mobile settings on key quality metrics such as inefficiency, instability, rebuffering ratio, and startup latency. We also find noticeable differences in the behavior of the schemes under Wi-Fi and cellular network access, with most of the schemes performing worse when the network access is cellular. Given these observations, we hypothesize on the possible causes of these inefficiencies. We also identify the best practices of existing schemes and key insights from experimental results that can serve as foundations for addressing many of the limitations. Armed with these measurement-driven insights, we propose a novel video quality adaptation scheme, called MASS, which is more robust to the vagaries of the wireless networking conditions. We implement and evaluate our solution on commodity Android smartphones, and demonstrate significant performance gains over existing schemes. To further improve the streaming experience, we introduce an extension to HTTP video streaming that leverages the synergy between social network participation and video streaming to optimize end-user Quality of Experience. Our system, called SDASH, integrates and applies well-known concepts such as cooperative caching, prefetching, and P2P streaming for reducing bitrate fluctuations and optimizing the viewing experience. Finally, we develop a general infrastructure for constructing temporally and spatially localized P2P communities of mobile devices sharing similar interests. The platform enables on-demand cooperation among mobile clients based on device context and client preferences. We use a concrete implementation of the mobile P2P infrastructure for evaluating the performance of SDASH. This dissertation addresses the challenges facing Adaptive HTTP Streaming under mobile networking conditions. Through experimentation with commodity mobile devices, we show that the proposed techniques for bitrate adaptation and cooperative streaming can significantly improve the video viewing experience.

With the increasing demand of video applications in wireless networks, how to better support video transmission over wireless networks has drawn much attention to the research community. Time-varying and error-prone nature of wireless channel makes video transmission in wireless networks a challenging task to provide the users with satisfactory watching experience. For different video applications, we choose different video coding techniques accordingly. E.g., for Internet video streaming, we choose standardized H.264 video codec; for video transmission in sensor networks or multicast, we choose simple and energy-conserving video coding technique based on compressive sensing. Thus, the challenges for different video transmission applications are different. Therefore, This dissertation tackles video transmission problem in three different applications. First, for dynamic adaptive streaming over HTTP (DASH), we investigate the streaming strategy. Specifically, we focus on the rate adaptation algorithm for streaming scalable video (H.264/SVC) in wireless networks. We model the rate adaptation problem as a Markov Decision Process (MDP), aiming to find an optimal streaming strategy in terms of user-perceived quality of experience (QoE) such as playback interruption, average playback quality and playback smoothness. We then obtain the optimal MDP solution using dynamic programming. However, the optimal solution requires the knowledge of the available bandwidth statistics and has a large number of states, which makes it difficult to obtain the optimal solution in real time. Therefore, we further propose an online algorithm which integrates the learning and planning process. The proposed online algorithm collects bandwidth statistics and makes streaming decisions in real time. A reward parameter has been defined in our proposed streaming strategy, which can be adjusted to make a good trade-off between the average playback quality and playback smoothness.We also use a simple testbed to validate our proposed algorithm. Second, for video transmission in wireless sensor networks, we consider a wireless sensor node monitoring the environment and it is equipped with a compressive-sensing based, single-pixel image camera and other sensors such as temperature and humidity sensors. The wireless node needs to send the data out in a timely and energy efficient way. This transmission control problem is challenging in that we need to jointly consider perceived video quality, quality variation, power consumption and transmission delay requirements, and the wireless channel uncertainty. We address the above issues by first building a rate-distortion model for compressive sensing video. Then we formulate the deterministic and stochastic optimization problems and design the transmission control algorithm which jointly performs rate control, scheduling and power control. Third, we propose a low-complex, scalable video coding architecture based on compressive sensing (SVCCS) for wireless unicast and multicast transmissions. SVCCS achieves good scalability, error resilience and coding efficiency. SVCCS encoded bitstream is divided into base and enhancement layers. The layered structure provides quality and temporal scalability. While in the enhancement layer, the CS measurements provide fine granular quality scalability. We also investigate the rate allocation problem for multicasting SVCCS encoded bitstream to a group of receivers with heterogeneous channel conditions. Specifically, we study how to allocate rate between the base and enhancement layer to improve the overall perceived video quality for all the receivers. / Graduate / 0984 / siyxiang@ece.uvic.ca

Dynamic Adaptive Streaming over HTTP (DASH) is a convenient approach to transfer videos in an adaptive and dynamic way to the user. Therefore, this system makes best use of the bandwidth available. In this thesis, we investigate Dynamic Adaptive Streaming over HTTP (DASH) based on data collected from the lab experiments and user’s experiments. The objectives include investigation of how three different DASH players behave at different network conditions and up to which limit the players are tolerating the disturbances. We summarized the outcome of lab experiments on DASH at different adverse conditions and checked the lab results with user quality of experience at different adverse conditions to see up to which extent the users could tolerate the disturbances in different DASH players.

Streaming multimedia over the Internet is omnipresent but still in its infancy, specifically when it comes to theadaptation based on bandwidth/throughput measurements, clients competing for limited/shared bandwidth, and thepresence of a caching infrastructure. Nowadays the streaming infrastructure is existing over-the-top (OTT).Interestingly, these services are all delivered over-the-top of the existing networking infrastructure using the HypertextTransfer Protocol (HTTP) which resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP(DASH).Video traffic is over 80% of the total internet traffic. Since Dynamic adaptive streaming over HTTP hasemerged it has a popular technique for video streaming on the internet. DASH allows the video player to adapt thebitrate according to the network conditions. DASH streaming client receives a manifest file, downloaded the referredvideo segments over HTTP, and play them back seamlessly emulated video streaming. This introduces latency of atleast one segment duration which decreases the quality of the user experience. In order to improve users over allQuality of Experience(QoE) a large number of adaptaion schemes were introduced to DASH.With such an importance of QoE on DASH, this thesis work investigates user acceptability of different DASHplayers. These players are exposed to different network conditions and the user analysis is given for each of thestreaming dash video for each player. The results of this thesis work include the analysis of the user rating for threedifferent players (Dash.js, GPAC and Shaka). The conclusion of this thesis is given by the quality of experience of thevideo streaming by the users which concludes that the Shaka player is preferred by the users compared to the othertwo players.

The purpose of this thesis is to investigate and test the usage of HTTP/2 in dynamic adaptive video streaming as well as to take a look into how it can be used to benefit prefetching algorithms used with branched video. With a series of experiments the performance gains of using HTTP/2 rather than the older standard HTTP/1.1 has been investigated. The results has shown no significant change to player quality and buffer occupancy when using HTTP/2, though our tests has shown in a slight decrease in overall playback quality when using HTTP/2. When using a linear prefetch of two fragments an average quality improvement of 4.59% has been shown, however, the result is inconclusive due to variations in average quality between different values for how many fragments to prefetch. Average buffer occupancy has shown promise with a maximum increase of 12.58%, when using linear prefetch with three fragments. The values for buffer occupancy gains are conclusive. Two implementations for non-linear prefetching has been made. The first one uses HTTP/2 server push to deliver fragments for prefetching and the second one uses client-side invoked HTTP requests to pull fragments from the server. Using HTTP/2 server push has shown in a decrease of 2.5% in average total load time while using client-side pulling has shown in a decrease of 34% in average total load time.