Towards multi-dimensional data representation and routing in Cognitive Radio Networks

Today, an increasing amount of the functionality traditionally associated with stationary computers is moving into mobile devices. Furthermore, the number of applications that retrieve data via networks is increasing in view of the recent growth of video streaming to the browsers, further emphasizing the Quality of Experience (QoE) requirements of mobile users today. Obviously, QoE demands are not necessarily connected to the fact that the link is mobile, which puts significant QoS demands onto the mobile systems involved. Consequently, this requires mobile systems to be flexible and adaptable to meet the QoS demands and cope with dynamic operating environments. Additionally, the rapid migration towards wireless connectivity and the abundance of mobile devices has put even greater strain on current wireless access technology designs. The frequency spectrum is a limited resource and must be efficiently utilized to conserve capacity and avoid overcrowding, particularly in densely populated areas. Hence, new wireless technologies and innovative architectural designs are needed to manage and to govern the wireless domain. The thesis is about combining the potential of Dynamic Spectrum Access (DSA) provided by Cognitive Radio (CR) with the scalability and fault tolerance capabilities demonstrated by Peer-to-Peer (P2P) systems. By combining these two technologies, we show that we can improve the resource utilization in crowded metropolitan areas to ensure service continuation between local mobile devices with minimal infrastructure requirements. The aim is to optimize the communication between Cognitive Radio Devices (CRD) in a Cognitive Radio Network (CRN) according to end-to-end (e2e) goals and user preferences