FlexStream: SDN-Based Framework for Programmable and Flexible Adaptive Video Streaming

With the tremendous increase in video traffic fueled by smartphones, tablets, 4G LTE networks, and other mobile devices and technologies, providing satisfactory services to end users in terms of playback quality and a fair share of network resources become challenging. As a result, an HTTP video streaming protocol was invented and widely adopted by most video providers today with the goal of maximizing the user’s quality of experience. However, despite the intensive efforts of major video providers such as YouTube and Netflix to improve their players, several studies as well as our measurements indicate that the players still suffer from several performance issues including instability and sub-optimality in the video bitrate, stalls in the playback, unfairness in sharing the available bandwidth, and inefficiency with regard to network utilization, considerably degrading the user’s QoE. These issues are frequently experienced when several players start competing over a common bottleneck. Interestingly, the root cause of these issues is the intermittent traffic pattern of the HTTP adaptive protocol that causes the players to over-estimate the available bandwidth and stream unsustainable video bitrates. In addition, the wireless network standards today do not allow the network to have a fine-grain control over individual devices which is necessary for providing resource usage coordination and global policy enforcement. We show that enabling such a network-side control would drive each device to fairly and efficiently utilize the network resources based on its current context, which would result in maximizing the overall viewing experience in the network and optimizing the bandwidth utilization. In this dissertation, we propose FlexStream, a flexible and programmable Software-Defined Network (SDN) based framework that solves all the adaptive streaming problems mentioned above. We develop FlexStream on top of the SDN-based framework that extends SDN functionality to mobile end devices, allowing for a fine-grained control and management of bandwidth based on real time context-awareness and specified policy. We demonstrate that FlexStream can be used to manage video delivery for a set of end devices over WiFi and cellular links and can effectively alleviate common problems such as player instability, playback stalls, large startup delay, and inappropriate bandwidth allocation. FlexStream offloads several tasks such as monitoring and policy enforcement to end-devices, while a network element (i.e., Global Controller), which has a global view of a network condition, is primarily employed to manage the resource allocation. This also alleviates the need for intrusive, large and costly traffic management solutions within the network, or modifications to servers that are not feasible in practice. We define an optimization method within the global controller for resource allocation to maximize video QoE considering context information, such as screen size and user priority. All features of FlexStream are implemented and validated on real mobile devices over real Wi-Fi and cellular networks. To the best of our knowledge, FlexStream is the first implementation of SDN-based control in a live cellular network that does not require any internal network support for SDN functionality

MMBnet 2017 - Proceedings of the 9th GI/ITG Workshop „Leistungs-, Verlässlichkeits- und Zuverlässigkeitsbewertung von Kommunikationsnetzen und Verteilten Systemen“

Nowadays, mathematical methods of systems and network monitoring, modeling, simulation, and performance, dependability and reliability analysis constitute the foundation of quantitative evaluation methods with regard to software-defined next-generation networks and advanced cloud computing systems. Considering the application of the underlying methodologies in engineering practice, these sophisticated techniques provide the basis in many different areas. The GI/ITG Technical Committee “Measurement, Modelling and Evaluation of Computing Systems“ (MMB) and its members have investigated corresponding research topics and initiated a series of MMB conferences and workshops over the last decades. Its 9th GI/ITG Workshop MMBnet 2017 „Leistungs-, Verlässlichkeits- und Zuverlässigkeitsbewertung von Kommunikationsnetzen und Verteilten Systemen“ was held at Hamburg University of Technology (TUHH), Germany, on September 14, 2017. The proceedings of MMBnet 2017 summarize the contributions of one invited talk and four contributed papers of young researchers. They deal with current research issues in next-generation networks, IP-based real-time communication systems, and new application architectures and intend to stimulate the reader‘s future research in these vital areas of modern information society

Advanced modelling of adaptive bitrate selection

Nowadays, a typical video content provider serves a variety of platforms e.g. smartphones, web browsers, and smart TVs. Each of these platforms has specific requirements with respect to transmission and video quality. Moreover, since these devices are increasingly being used on-the-go, the environment within which most of these video streaming clients operate is both unreliable and time-varying. To cater for these heterogeneous requirements, content providers are increasingly adopting adaptive streaming services. Through such services, the quality of the video content received by a user is adapted to fit its specific requirements and capabilities. To adapt the video quality, system capabilities such as network capacity and memory have to be continuously monitored and measured, chunk requests have to be scheduled, and then the optimal video rate has to be decided. Each of these tasks is usually managed by a sub-module of the adaptive bitrate selection function. However, these sub-components interact in a non-trivial manner. For example, while on-off chunk scheduling helps to prevent buffer overflow, it negatively affects the TCP throughput. Hence, these complex interactions between these different sub-components of the adaptive streaming algorithm result in unnecessary rebufferings, undesirable variability, and sub-optimal video quality. To help simplify these interactions, this thesis develops several frameworks and models that define the relationships between the various components of the adaptive bitrate selection system. This includes deriving the valid system state space, which defines the state that an algorithm can be in at any given time, determining the allowable interactions between the various components, and identifying the video quality evolution rules that optimise QoE. Using this information, some state-of-the-art algorithms are improved and novel ones developed to demonstrate the effectiveness of the proposed approach. The result of extensive evaluations conducted both within a real-world Internet environment and with network trace shows the proposed schemes help in reducing the convergence time, startup delay, and rebuffering events, while at the same time increasing both the average and the stability of the video quality. All this is obtained without any adverse impact on the fairness among the competing players