@phdthesis{NguyenNgoc2018,
  author    = {Nguyen-Ngoc, Anh},
  title     = {On Performance Assessment of Control Mechanisms and Virtual Components in SDN-based Networks},
  issn      = {1432-8801},
  doi       = {10.25972/OPUS-16932},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-169328},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {This dissertation focuses on the performance evaluation of all components of Software Defined Networking (SDN) networks and covers whole their architecture. First, the isolation between virtual networks sharing the same physical resources is investigated with SDN switches of several vendors. Then, influence factors on the isolation are identified and evaluated. Second, the impact of control mechanisms on the performance of the data plane is examined through the flow rule installation time of SDN switches with different controllers. It is shown that both hardware-specific and controller instance have a specific influence on the installation time. Finally, several traffic flow monitoring methods of an SDN controller are investigated and a new monitoring approach is developed and evaluated. It is confirmed that the proposed method allows monitoring of particular flows as well as consumes fewer resources than the standard approach. Based on findings in this thesis, on the one hand, controller developers can refer to the work related to the control plane, such as flow monitoring or flow rule installation, to improve the performance of their applications. On the other hand, network administrators can apply the presented methods to select a suitable combination of controller and switches in their SDN networks, based on their performance requirements},
  subject      = {Leistungsbewertung},
  language  = {en}
}
@phdthesis{DinhXuan2018,
  author    = {Dinh-Xuan, Lam},
  title     = {Quality of Experience Assessment of Cloud Applications and Performance Evaluation of VNF-Based QoE Monitoring},
  issn      = {1432-8801},
  doi       = {10.25972/OPUS-16918},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-169182},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {In this thesis various aspects of Quality of Experience (QoE) research are examined. The work is divided into three major blocks: QoE Assessment, QoE Monitoring, and VNF Performance Evaluation. First, prominent cloud applications such as Google Docs and a cloud-based photo album are explored. The QoE is characterized and the influence of packet loss and delay is studied. Afterwards, objective QoE monitoring for HTTP Adaptive Video Streaming (HAS) in the cloud is investigated. Additionally, by using a Virtual Network Function (VNF) for QoE monitoring in the cloud, the feasibility of an interworking of Network Function Virtualization (NFV) and cloud paradigm is evaluated. To this end, a VNF that exploits deep packet inspection technique was used to parse the video traffic. An algorithm is then designed accordingly to estimate video quality and QoE based on network and application layer parameters. To assess the accuracy of the estimation, the VNF is measured in different scenarios under different network QoS and the virtual environment of the cloud architecture. The insights show that the different geographical deployments of the VNF influence the accuracy of the video quality and QoE estimation. Various Service Function Chain (SFC) placement algorithms have been proposed and compared in the context of edge cloud networks. On the one hand, this research is aimed at cloud service providers by providing methods for evaluating QoE for cloud applications. On the other hand, network operators can learn the pitfalls and disadvantages of using the NFV paradigm for such a QoE monitoring mechanism.},
  subject      = {Quality of Experience},
  language  = {en}
}