| This dissertation evaluates the analytical correlations between the quantitative quality of service parameters and qualitative quality of experience; and defines the desired quality of experience and realized quality of experience, to aid in optimizing the quality of experience. Next, this dissertation proposes a cloud-enabled wireless access network architecture that implements software defined networking for control and optimization. And lastly, this dissertation evaluates the benefits of the proposed architecture, utilizing the desired quality of experience.;The proliferation of mobile devices and broadband applications has placed tremendous demands on wireless network services. Demands for network accessible multimedia content, especially video, has been growing at a rapid pace. When accessed using mobile devices via wireless or mobile networks, a high demand is placed on these resource constrained dynamic environments. Optimizing the performance of wireless edge networks to ensure a high quality of experience for all connected users requires employing new capabilities on the edge network. This dissertation introduces the concepts of desired and realized quality of experience, which can be used to normalize the quality that users perceive in order to make more accurate comparisons across a wide range of devices and scenarios.;The trend of combining advanced communications and information technologies has created unprecedented opportunities for innovation in network-centric services. The rapid growth in cloud computing and middlebox deployment is an outcome of such integration. A similar level of success should be expected if this paradigm is adopted by access networks. This dissertation presents a computation-capable and programmable wireless access network architecture to enable more efficient and robust content delivery. The proposed architecture integrates cloud computing technology to support in-network processing and caching, and software defined networking for flexible management and control of network resources. Finally, this dissertation proposes the framework and algorithms for optimizing the quality of experience of multiple video streams in real-time, subject to wireless transmission capacity and in-network computational power constraints. The framework and algorithms address the multiple resource management challenges that arise in exploiting such integration. The evaluation results show the proposed algorithms significantly improve the average quality of experience of wireless users, especially in congested environments. |
