004 Datenverarbeitung; Informatik
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The work presents a performance evaluation and optimization of so-called overlay networks for content distribution in the Internet. Chapter 1 describes the importance which have such networks in today's Internet, for example, for the transmission of video content. The focus of this work is on overlay networks based on the peer-to-peer principle. These are characterized by the fact that users who download content, also contribute to the distribution process by sharing parts of the data to other users. This enables efficient content distribution because each user not only consumes resources in the system, but also provides its own resources. Chapter 2 of the monograph contains a detailed description of the functionality of today's most popular overlay network BitTorrent. It explains the various components and their interaction. This is followed by an illustration of why such overlay networks for Internet service providers (ISPs) are problematic. The reason lies in the large amount of inter-ISP traffic that is produced by these overlay networks. Since this inter-ISP traffic leads to high costs for ISPs, they try to reduce it by improved mechanisms for overlay networks. One optimization approach is the use of topology awareness within the overlay networks. It provides users of the overlay networks with information about the underlying physical network topology. This allows them to avoid inter-ISP traffic by exchanging data preferrentially with other users that are connected to the same ISP. Another approach to save inter-ISP traffic is caching. In this case the ISP provides additional computers in its network, called caches, which store copies of popular content. The users of this ISP can then obtain such content from the cache. This prevents that the content must be retrieved from locations outside of the ISP's network, and saves costly inter-ISP traffic in this way. In the third chapter of the thesis, the results of a comprehensive measurement study of overlay networks, which can be found in today's Internet, are presented. After a short description of the measurement methodology, the results of the measurements are described. These results contain data on a variety of characteristics of current P2P overlay networks in the Internet. These include the popularity of content, i.e., how many users are interested in specific content, the evolution of the popularity and the size of the files. The distribution of users within the Internet is investigated in detail. Special attention is given to the number of users that exchange a particular file within the same ISP. On the basis of these measurement results, an estimation of the traffic savings that can achieved by topology awareness is derived. This new estimation is of scientific and practical importance, since it is not limited to individual ISPs and files, but considers the whole Internet and the total amount of data exchanged in overlay networks. Finally, the characteristics of regional content are considered, in which the popularity is limited to certain parts of the Internet. This is for example the case of videos in German, Italian or French language. Chapter 4 of the thesis is devoted to the optimization of overlay networks for content distribution through caching. It presents a deterministic flow model that describes the influence of caches. On the basis of this model, it derives an estimate of the inter-ISP traffic that is generated by an overlay network, and which part can be saved by caches. The results show that the influence of the cache depends on the structure of the overlay networks, and that caches can also lead to an increase in inter-ISP traffic under certain circumstances. The described model is thus an important tool for ISPs to decide for which overlay networks caches are useful and to dimension them. Chapter 5 summarizes the content of the work and emphasizes the importance of the findings. In addition, it explains how the findings can be applied to the optimization of future overlay networks. Special attention is given to the growing importance of video-on-demand and real-time video transmissions.
Radiation therapy today, on account of improvements in treatment procedures over the last 60 years, allows precise treatment of static tumors inside the human body. However, irradiation of moving tumors is still a challenging task as moving tumors often leave the treatment beam and the radiation dose delivered to the tumor reduces simultaneously increasing that on healthy tissue. This research work aims to push the frontiers of radiation therapy in order to enable precise treatment of moving tumors with focus on research and development of a unique real-time system enabling active motion compensation through robotic means to compensate tumor motion. During treatment, patients lie on a treatment couch which is normally used for static position corrections of patient set-up errors prior to radiation treatment. The treatment couch used, called HexaPOD, is a parallel manipulator with six degrees of freedom which can precisely position heavy loads inside a small region. Despite the HexaPOD not initially built with dynamics in mind, it is used in this work for sustained motion compensation by moving patients such that tumors stay precisely located at the center of the treatment beam during the complete course of treatment. In order to realize real-time tumor motion compensation by means of the HexaPOD, several challanges need to be addressed. Real-time aspects are covered by the adoption of a hard real-time operation system in combination with measurement and estimation of latencies of all physical quantities in the compensation system such as tumor or breathing position measurements. Accurate timing information is respected consistently in the whole system and all software-induced latencies are adaptively compensated for. This requires knowledge of future tumor positions from predictors. Several predictors for breathing and tumor motion predictions are proposed and evaluated in terms of a variety of different performance metrics. Extensions to prediction algorithms are introduced fusing both breathing and tumor position information to allow for predictions without the need of an explicit correlation model. Predictions determine the future motion path of the HexaPOD in order to compensate for tumor motion. Several control schemes are developed to enable reference tracking for the HexaPOD. Based on linear and non-linear dynamic modelling of the HexaPOD with system identification methods, a first controller is derived in the form of a model predictive controller. A second controller is proposed based on an assumption of the working principle of the HexaPOD's internal controller. Finally, a third controller is derived as combination of the first and second one. For each of these controllers, comparative results with real hardware experiments and humans in the loop as well as choices of free parameters are presented and discussed. Apart from precise tracking, emphasis is placed on patient comfort which is of crucial importance for acceptance of the system. It is demonstrated that smooth trajectories can be realized by the controllers to guarantee that patients feel comfortable while their tumor motion is compensated at sub-millimeter accuracies. Overall errors of the system are analyzed by relating them to tracking and prediction errors. By exploiting the properties of different predictors, it is shown that the startup time until tracking is reached can be reduced to only a few seconds, even in the case of an initially at-rest HexaPOD and with no initial knowledge of tumor motion. This makes the system especially suitable for the relatively short-fractionated treatment sessions for lung tumors. The tumor motion compensation system has been developed solely based on standard clinical hardware, found in most treatment rooms. With a simple and flexible design, existing treatment can be updated in a cost-efficient way to introduce motion compensation capabilities. Simultaneously, the system does not impose any constraints on state-of-the-art treatment types such as intensity modulated radiotherapy or volumetric modulated arc therapy. Supporting different compensation modes, the system can be applied to any moving tumor whether its motion is predictable (lung tumors) or unpredictable (prostate tumors). By integration of adequate tumor position determination methods, the system can be easily extended to other tumors as well.