Service Quality Improvement and User Experience Optimization by Introducing Intelligence in the Network

The majority of present-day distributed applications demand a certain level of service from the transportation network and impose a number of performance requirements on it. Failure to meet these requirements will typically degrade the efficiency of the application and, more importantly, will likely have a detrimental impact on the experience of the end-user. Over the years, a number of frameworks has therefore been proposed that enable transportation networks to guarantee a certain Quality of Service (QoS) and the positive implications of these frameworks on application performance have been established. Due to the growing attention to human factors however, the focus is increasingly shifting from pure QoS provision towards user experience optimization. Stated differently, in recent years, the goal of guaranteeing a certain level of network performance is evermore being replaced with the aspiration to ensure a high end-user satisfaction or so-called Quality of Experience (QoE). The current generation of telecommunications networks, and the omnipresent Internet in particular, unfortunately lack elaborate and effective constructs for QoE optimization. Mitigating this deficiency forms the subject of this thesis. The overall contribution of this doctoral dissertation is the Network Intelligence Proxy (NIProxy), a network intermediary which has been developed to enable QoE manipulation and optimization in IPv4-based computer networks. As is hinted at by its name, the NIProxy’s methodology involves the introduction of “intelligence” in the networking infrastructure. This is achieved by accumulating contextual knowledge regarding the transportation network itself, the distributed application and the end-user (and his terminal). On a finer-grained level, this PhD research contributes to various domains, the first of which being network traffic engineering and application-layer QoS provision. The NIProxy provides two complementary techniques to improve the (multimedia) traffic handling capabilities of the transportation network in which it is deployed. The first technique, network traffic shaping (NTS),