@phdthesis{Schlosser2011,
  author    = {Schlosser, Daniel},
  title     = {Quality of Experience Management in Virtual Future Networks},
  doi       = {10.25972/OPUS-5719},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-69986},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {Aktuell beobachten wir eine drastische Vervielf{\"a}ltigung der Dienste und Anwendungen, die das Internet f{\"u}r den Datentransport nutzen. Dabei unterscheiden sich die Anforderungen dieser Dienste an das Netzwerk deutlich. Das Netzwerkmanagement wird durch diese Diversit{\"a}t der nutzenden Dienste aber deutlich erschwert, da es einem Datentransportdienstleister kaum m{\"o}glich ist, die unterschiedlichen Verbindungen zu unterscheiden, ohne den Inhalt der transportierten Daten zu analysieren. Netzwerkvirtualisierung ist eine vielversprechende L{\"o}sung f{\"u}r dieses Problem, da sie es erm{\"o}glicht f{\"u}r verschiedene Dienste unterschiedliche virtuelle Netze auf dem gleichen physikalischen Substrat zu betreiben. Diese Diensttrennung erm{\"o}glicht es, jedes einzelne Netz anwendungsspezifisch zu steuern. Ziel einer solchen Netzsteuerung ist es, sowohl die vom Nutzer erfahrene Dienstg{\"u}te als auch die Kosteneffizienz des Datentransports zu optimieren. Dar{\"u}ber hinaus wird es mit Netzwerkvirtualisierung m{\"o}glich das physikalische Netz so weit zu abstrahieren, dass die aktuell fest verzahnten Rollen von Netzwerkbesitzer und Netzwerkbetreiber entkoppelt werden k{\"o}nnen. Dar{\"u}ber hinaus stellt Netzwerkvirtualisierung sicher, dass unterschiedliche Datennetze, die gleichzeitig auf dem gleichen physikalischen Netz betrieben werden, sich gegenseitig weder beeinflussen noch st{\"o}ren k{\"o}nnen. Diese Arbeit  besch{\"a}ftigt sich mit ausgew{\"a}hlten Aspekten dieses Themenkomplexes und fokussiert sich darauf, ein virtuelles Netzwerk mit bestm{\"o}glicher Dienstqualit{\"a}t f{\"u}r den Nutzer zu betreiben und zu steuern. Daf{\"u}r wird ein Top-down-Ansatz gew{\"a}hlt, der von den Anwendungsf{\"a}llen, einer m{\"o}glichen Netzwerkvirtualisierungs-Architektur und aktuellen M{\"o}glichkeiten der Hardwarevirtualisierung ausgeht. Im Weiteren fokussiert sich die Arbeit dann in Richtung Bestimmung und Optimierung der vom Nutzer erfahrenen Dienstqualit{\"a}t (QoE) auf Applikationsschicht und diskutiert M{\"o}glichkeiten zur Messung und {\"U}berwachung von wesentlichen Netzparametern in virtualisierten Netzen.},
  subject      = {Netzwerkmanagement},
  language  = {en}
}
@phdthesis{Pries2010,
  author    = {Pries, Jan Rastin},
  title     = {Performance Optimization of Wireless Infrastructure and Mesh Networks},
  doi       = {10.25972/OPUS-3723},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-46097},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {Future broadband wireless networks should be able to support not only best effort traffic but also real-time traffic with strict Quality of Service (QoS) constraints. In addition, their available resources are scare and limit the number of users. To facilitate QoS guarantees and increase the maximum number of concurrent users, wireless networks require careful planning and optimization. In this monograph, we studied three aspects of performance optimization in wireless networks: resource optimization in WLAN infrastructure networks, quality of experience control in wireless mesh networks, and planning and optimization of wireless mesh networks. An adaptive resource management system is required to effectively utilize the limited resources on the air interface and to guarantee QoS for real-time applications. Thereby, both WLAN infrastructure and WLAN mesh networks have to be considered. An a-priori setting of the access parameters is not meaningful due to the contention-based medium access and the high dynamics of the system. Thus, a management system is required which dynamically adjusts the channel access parameters based on the network load. While this is sufficient for wireless infrastructure networks, interferences on neighboring paths and self-interferences have to be considered for wireless mesh networks. In addition, a careful channel allocation and route assignment is needed. Due to the large parameter space, standard optimization techniques fail for optimizing large wireless mesh networks. In this monograph, we reveal that biology-inspired optimization techniques, namely genetic algorithms, are well-suitable for the planning and optimization of wireless mesh networks. Although genetic algorithms generally do not always find the optimal solution, we show that with a good parameter set for the genetic algorithm, the overall throughput of the wireless mesh network can be significantly improved while still sharing the resources fairly among the users.},
  subject      = {IEEE 802.11},
  language  = {en}
}
@phdthesis{Moldovan2021,
  author    = {Moldovan, Christian},
  title     = {Performance Modeling of Mobile Video Streaming},
  issn      = {1432-8801},
  doi       = {10.25972/OPUS-22871},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-228715},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {In the past two decades, there has been a trend to move from traditional television to Internet-based video services. With video streaming becoming one of the most popular applications in the Internet and the current state of the art in media consumption, quality expectations of consumers are increasing. Low quality videos are no longer considered acceptable in contrast to some years ago due to the increased sizes and resolution of devices. If the high expectations of the users are not met and a video is delivered in poor quality, they often abandon the service. Therefore, Internet Service Providers (ISPs) and video service providers are facing the challenge of providing seamless multimedia delivery in high quality. Currently, during peak hours, video streaming causes almost 58\\% of the downstream traffic on the Internet. With higher mobile bandwidth, mobile video streaming has also become commonplace. According to the 2019 Cisco Visual Networking Index, in 2022 79\% of mobile traffic will be video traffic and, according to Ericsson, by 2025 video is forecasted to make up 76\% of total Internet traffic. Ericsson further predicts that in 2024 over 1.4 billion devices will be subscribed to 5G, which will offer a downlink data rate of 100 Mbit/s in dense urban environments. One of the most important goals of ISPs and video service providers is for their users to have a high Quality of Experience (QoE). The QoE describes the degree of delight or annoyance a user experiences when using a service or application. In video streaming the QoE depends on how seamless a video is played and whether there are stalling events or quality degradations. These characteristics of a transmitted video are described as the application layer Quality of Service (QoS). In general, the QoS is defined as "the totality of characteristics of a telecommunications service that bear on its ability to satisfy stated and implied needs of the user of the service" by the ITU. The network layer QoS describes the performance of the network and is decisive for the application layer QoS. In Internet video, typically a buffer is used to store downloaded video segments to compensate for network fluctuations. If the buffer runs empty, stalling occurs. If the available bandwidth decreases temporarily, the video can still be played out from the buffer without interruption. There are different policies and parameters that determine how large the buffer is, at what buffer level to start the video, and at what buffer level to resume playout after stalling. These have to be finely tuned to achieve the highest QoE for the user. If the bandwidth decreases for a longer time period, a limited buffer will deplete and stalling can not be avoided. An important research question is how to configure the buffer optimally for different users and situations. In this work, we tackle this question using analytic models and measurement studies. With HTTP Adaptive Streaming (HAS), the video players have the capability to adapt the video bit rate at the client side according to the available network capacity. This way the depletion of the video buffer and thus stalling can be avoided. In HAS, the quality in which the video is played and the number of quality switches also has an impact on the QoE. Thus, an important problem is the adaptation of video streaming so that these parameters are optimized. In a shared WiFi multiple video users share a single bottleneck link and compete for bandwidth. In such a scenario, it is important that resources are allocated to users in a way that all can have a similar QoE. In this work, we therefore investigate the possible fairness gain when moving from network fairness towards application-layer QoS fairness. In mobile scenarios, the energy and data consumption of the user device are limited resources and they must be managed besides the QoE. Therefore, it is also necessary, to investigate solutions, that conserve these resources in mobile devices. But how can resources be conserved without sacrificing application layer QoS? As an example for such a solution, this work presents a new probabilistic adaptation algorithm that uses abandonment statistics for ts decision making, aiming at minimizing the resource consumption while maintaining high QoS. With current protocol developments such as 5G, bandwidths are increasing, latencies are decreasing and networks are becoming more stable, leading to higher QoS. This allows for new real time data intensive applications such as cloud gaming, virtual reality and augmented reality applications to become feasible on mobile devices which pose completely new research questions. The high energy consumption of such applications still remains an issue as the energy capacity of devices is currently not increasing as quickly as the available data rates. In this work we compare the optimal performance of different strategies for adaptive 360-degree video streaming.},
  subject      = {Video{\"u}bertragung},
  language  = {en}
}
@phdthesis{Hossfeld2009,
  author    = {Hoßfeld, Tobias},
  title     = {Performance Evaluation of Future Internet Applications and Emerging User Behavior},
  doi       = {10.25972/OPUS-3067},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-37570},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {In future telecommunication systems, we observe an increasing diversity of access networks. The separation of transport services and applications or services leads to multi-network services, i.e., a future service has to work transparently to the underlying network infrastructure. Multi-network services with edge-based intelligence, like P2P file sharing or the Skype VoIP service, impose new traffic control paradigms on the future Internet. Such services adapt the amount of consumed bandwidth to reach different goals. A selfish behavior tries to keep the QoE of a single user above a certain level. Skype, for instance, repeats voice samples depending on the perceived end-to-end loss. From the viewpoint of a single user, the replication of voice data overcomes the degradation caused by packet loss and enables to maintain a certain QoE. The cost for this achievement is a higher amount of consumed bandwidth. However, if the packet loss is caused by congestion in the network, this additionally required bandwidth even worsens the network situation. Altruistic behavior, on the other side, would reduce the bandwidth consumption in such a way that the pressure on the network is released and thus the overall network performance is improved. In this monograph, we analyzed the impact of the overlay, P2P, and QoE paradigms in future Internet applications and the interactions from the observing user behavior. The shift of intelligence toward the edge is accompanied by a change in the emerging user behavior and traffic profile, as well as a change from multi-service networks to multi-networks services. In addition, edge-based intelligence may lead to a higher dynamics in the network topology, since the applications are often controlled by an overlay network, which can rapidly change in size and structure as new nodes can leave or join the overlay network in an entirely distributed manner. As a result, we found that the performance evaluation of such services provides new challenges, since novel key performance factors have to be first identified, like pollution of P2P systems, and appropriate models of the emerging user behavior are required, e.g. taking into account user impatience. As common denominator of the presented studies in this work, we focus on a user-centric view when evaluating the performance of future Internet applications. For a subscriber of a certain application or service, the perceived quality expressed as QoE will be the major criterion of the user's satisfaction with the network and service providers. We selected three different case studies and characterized the application's performance from the end user's point of view. Those are (1) cooperation in mobile P2P file sharing networks, (2) modeling of online TV recording services, and (3) QoE of edge-based VoIP applications. The user-centric approach facilitates the development of new mechanisms to overcome problems arising from the changing user behavior. An example is the proposed CycPriM cooperation strategy, which copes with selfish user behavior in mobile P2P file sharing system. An adequate mechanism has also been shown to be efficient in a heterogeneous B3G network with mobile users conducting vertical handovers between different wireless access technologies. The consideration of the user behavior and the user perceived quality guides to an appropriate modeling of future Internet applications. In the case of the online TV recording service, this enables the comparison between different technical realizations of the system, e.g. using server clusters or P2P technology, to properly dimension the installed network elements and to assess the costs for service providers. Technologies like P2P help to overcome phenomena like flash crowds and improve scalability compared to server clusters, which may get overloaded in such situations. Nevertheless, P2P technology invokes additional challenges and different user behavior to that seen in traditional client/server systems. Beside the willingness to share files and the churn of users, peers may be malicious and offer fake contents to disturb the data dissemination. Finally, the understanding and the quantification of QoE with respect to QoS degradations permits designing sophisticated edge-based applications. To this end, we identified and formulated the IQX hypothesis as an exponential interdependency between QoE and QoS parameters, which we validated for different examples. The appropriate modeling of the emerging user behavior taking into account the user's perceived quality and its interactions with the overlay and P2P paradigm will finally help to design future Internet applications.},
  subject      = {Leistungsbewertung},
  language  = {en}
}