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Das stochastische Denken, die Bernoullische Stochastik und dessen informationstechnologische Umsetzung, namens Stochastikon stellen die Grundlage für das Verständnis und die erfolgreiche Nutzung einer stochastischen Wissenschaft dar. Im Rahmen dieser Arbeit erfolgt eine Klärung des Begriffs des stochastischen Denkens, eine anschauliche Darstellung der von Elart von Collani entwickelten Bernoullischen Stochastik und eine Beschreibung von Stochastikon. Dabei werden sowohl das Gesamtkonzept von Stochastikon, sowie die Ziele, Aufgaben und die Realisierung der beiden Teilsysteme namens Mentor und Encyclopedia vorgestellt. Das stochastische Denken erlaubt eine realitätsnahe Sichtweise der Dinge, d.h. eine Sichtweise, die mit den menschlichen Beobachtungen und Erfahrungen im Einklang steht und somit die Unsicherheit über zukünftige Entwicklungen berücksichtigt. Der in diesem Kontext verwendete Begriff der Unsicherheit bezieht sich ausschließlich auf zukünftige Entwicklungen und äußert sich in Variabilität. Quellen der Unsicherheit sind einerseits die menschliche Ignoranz und andererseits der Zufall. Unter Ignoranz wird hierbei die Unwissenheit des Menschen über die unbekannten, aber feststehenden Fakten verstanden, die die Anfangsbedingungen der zukünftigen Entwicklung repräsentieren. Die Bernoullische Stochastik liefert ein Regelwerk und ermöglicht die Entwicklung eines quantitativen Modells zur Beschreibung der Unsicherheit und expliziter Einbeziehung der beiden Quellen Ignoranz und Zufall. Das Modell trägt den Namen Bernoulli-Raum und bildet die Grundlage für die Herleitung quantitativer Verfahren, um zuverlässige und genaue Aussagen sowohl über die nicht-existente zufällige Zukunft (Vorhersageverfahren), als auch über die unbekannte feststehende Vergangenheit (Messverfahren). Das Softwaresystem Stochastikon implementiert die Bernoullische Stochastik in Form einer Reihe autarker, miteinander kommunizierender Teilsysteme. Ziel des Teilsystems Encyclopedia ist die Bereitstellung und Bewertung stochastischen Wissens. Das Teilsystem Mentor dient der Unterstützung des Anwenders bei der Problemlösungsfindung durch Identifikation eines richtigen Modells bzw. eines korrekten Bernoulli-Raums. Der Lösungsfindungsprozess selber enthält keinerlei Unsicherheit. Die ganze Unsicherheit steckt in der Lösung, d.h. im Bernoulli-Raum, der explizit die vorhandene Unwissenheit (Ignoranz) und den vorliegenden Zufall abdeckend enthält.
No abstract available
Data mining has proved its significance in various domains and applications. As an important subfield of the general data mining task, subgroup mining can be used, e.g., for marketing purposes in business domains, or for quality profiling and analysis in medical domains. The goal is to efficiently discover novel, potentially useful and ultimately interesting knowledge. However, in real-world situations these requirements often cannot be fulfilled, e.g., if the applied methods do not scale for large data sets, if too many results are presented to the user, or if many of the discovered patterns are already known to the user. This thesis proposes a combination of several techniques in order to cope with the sketched problems: We discuss automatic methods, including heuristic and exhaustive approaches, and especially present the novel SD-Map algorithm for exhaustive subgroup discovery that is fast and effective. For an interactive approach we describe techniques for subgroup introspection and analysis, and we present advanced visualization methods, e.g., the zoomtable that directly shows the most important parameters of a subgroup and that can be used for optimization and exploration. We also describe various visualizations for subgroup comparison and evaluation in order to support the user during these essential steps. Furthermore, we propose to include possibly available background knowledge that is easy to formalize into the mining process. We can utilize the knowledge in many ways: To focus the search process, to restrict the search space, and ultimately to increase the efficiency of the discovery method. We especially present background knowledge to be applied for filtering the elements of the problem domain, for constructing abstractions, for aggregating values of attributes, and for the post-processing of the discovered set of patterns. Finally, the techniques are combined into a knowledge-intensive process supporting both automatic and interactive methods for subgroup mining. The practical significance of the proposed approach strongly depends on the available tools. We introduce the VIKAMINE system as a highly-integrated environment for knowledge-intensive active subgroup mining. Also, we present an evaluation consisting of two parts: With respect to objective evaluation criteria, i.e., comparing the efficiency and the effectiveness of the subgroup discovery methods, we provide an experimental evaluation using generated data. For that task we present a novel data generator that allows a simple and intuitive specification of the data characteristics. The results of the experimental evaluation indicate that the novel SD-Map method outperforms the other described algorithms using data sets similar to the intended application concerning the efficiency, and also with respect to precision and recall for the heuristic methods. Subjective evaluation criteria include the user acceptance, the benefit of the approach, and the interestingness of the results. We present five case studies utilizing the presented techniques: The approach has been successfully implemented in medical and technical applications using real-world data sets. The method was very well accepted by the users that were able to discover novel, useful, and interesting knowledge.
Overlay networks establish logical connections between users on top of the physical network. While randomly connected overlay networks provide only a best effort service, a new generation of structured overlay systems based on Distributed Hash Tables (DHTs) was proposed by the research community. However, there is still a lack of understanding the performance of such DHTs. Additionally, those architectures are highly distributed and therefore appear as a black box to the operator. Yet an operator does not want to lose control over his system and needs to be able to continuously observe and examine its current state at runtime. This work addresses both problems and shows how the solutions can be combined into a more self-organizing overlay concept. At first, we evaluate the performance of structured overlay networks under different aspects and thereby illuminate in how far such architectures are able to support carrier-grade applications. Secondly, to enable operators to monitor and understand their deployed system in more detail, we introduce both active as well as passive methods to gather information about the current state of the overlay network.
Verteilte dynamische Systeme unter lokalen und globalen Gesichtspunkten zu optimieren ist eine schwierige Aufgabe. Zwar sind grundsätzliche Auswirkungen einzelner Maßnahmen häufig bekannt, durch widerstrebende Ziele, Wechselwirkungen zwischen Prozessen und Nebenwirkungen von Maßnahmen ist ein analytisches Vorgehen bei der Optimierung nicht möglich. Besonders schwierig wird es, wenn lokale Einheiten einerseits ihre Ziele und Autonomie behalten sollen, aber durch zentrale Vorgaben bzw. Anreize so gesteuert werden sollen, dass ein übergeordnetes Ziel erreicht wird. Ein praktisches Beispiel dieses allgemeinen Optimierungsproblems findet sich im Gesundheitswesen. Das Management von modernen Kliniken ist stets mit dem Problem konfrontiert, die Qualität der Pflege zu gewährleisten und gleichzeitig kosteneffizient zu arbeiten. Hier gilt es unter gegeben Rahmenbedingungen und bei Respektierung der Autonomie der Funktionseinheiten, Optimierungsmaßnahmen zu finden und durchzuführen. Vorhandene Werkzeuge zur Simulation und Modellierung bieten für diese Aufgabe keine ausreichend guten Vorgehensmodelle und Modellierungsmechanismen. Die agentenbasierte Simulation ermöglicht die Abbildung solcher Systeme und die Durchführung von Simulationsexperimenten zur Bewertung einzelner Maßnahmen. Es werden Lösungswege und Werkzeuge vorgestellt und evaluiert, die den Benutzer bei der Formalisierung des Wissens und der Modellierung solch komplexer Szenarien unterstützen und ein systematisches Vorgehen zur Optimierung ermöglichen.
Performance Evaluation of Efficient Resource Management Concepts for Next Generation IP Networks
(2007)
Next generation networks (NGNs) must integrate the services of current circuit-switched telephone networks and packet-switched data networks. This convergence towards a unified communication infrastructure necessitates from the high capital expenditures (CAPEX) and operational expenditures (OPEX) due to the coexistence of separate networks for voice and data. In the end, NGNs must offer the same services as these legacy networks and, therefore, they must provide a low-cost packet-switched solution with real-time transport capabilities for telephony and multimedia applications. In addition, NGNs must be fault-tolerant to guarantee user satisfaction and to support business-critical processes also in case of network failures. A key technology for the operation of NGNs is the Internet Protocol (IP) which evolved to a common and well accepted standard for networking in the Internet during the last 25 years. There are two basically different approaches to achieve QoS in IP networks. With capacity overprovisioning (CO), an IP network is equipped with sufficient bandwidth such that network congestion becomes very unlikely and QoS is maintained most of the time. The second option to achieve QoS in IP networks is admission control (AC). AC represents a network-inherent intelligence that admits real-time traffic flows to a single link or an entire network only if enough resources are available such that the requirements on packet loss and delay can be met. Otherwise, the request of a new flow is blocked. This work focuses on resource management and control mechanisms for NGNs, in particular on AC and associated bandwidth allocation methods. The first contribution consists of a new link-oriented AC method called experience-based admission control (EBAC) which is a hybrid approach dealing with the problems inherent to conventional AC mechanisms like parameter-based or measurement-based AC (PBAC/MBAC). PBAC provides good QoS but suffers from poor resource utilization and, vice versa, MBAC uses resources efficiently but is susceptible to QoS violations. Hence, EBAC aims at increasing the resource efficiency while maintaining the QoS which increases the revenues of ISPs and postpones their CAPEX for infrastructure upgrades. To show the advantages of EBAC, we first review today’s AC approaches and then develop the concept of EBAC. EBAC is a simple mechanism that safely overbooks the capacity of a single link to increase its resource utilization. We evaluate the performance of EBAC by its simulation under various traffic conditions. The second contribution concerns dynamic resource allocation in transport networks which implement a specific network admission control (NAC) architecture. In general, the performance of different NAC systems may be evaluated by conventional methods such as call blocking analysis which has often been applied in the context of multi-service asynchronous transfer mode (ATM) networks. However, to yield more practical results than abstract blocking probabilities, we propose a new method to compare different AC approaches by their respective bandwidth requirements. To present our new method for comparing different AC systems, we first give an overview of network resource management (NRM) in general. Then we present the concept of adaptive bandwidth allocation (ABA) in capacity tunnels and illustrate the analytical performance evaluation framework to compare different AC systems by their capacity requirements. Different network characteristics influence the performance of ABA. Therefore, the impact of various traffic demand models and tunnel implementations, and the influence of resilience requirements is investigated. In conclusion, the resources in NGNs must be exclusively dedicated to admitted traffic to guarantee QoS. For that purpose, robust and efficient concepts for NRM are required to control the requested bandwidth with regard to the available transmission capacity. Sophisticated AC will be a key function for NRM in NGNs and, therefore, efficient resource management concepts like experience-based admission control and adaptive bandwidth allocation for admission-controlled capacity tunnels, as presented in this work are appealing for NGN solutions.
This thesis is devoted to the study of computational complexity theory, a branch of theoretical computer science. Computational complexity theory investigates the inherent difficulty in designing efficient algorithms for computational problems. By doing so, it analyses the scalability of computational problems and algorithms and places practical limits on what computers can actually accomplish. Computational problems are categorised into complexity classes. Among the most important complexity classes are the class NP and the subclass of NP-complete problems, which comprises many important optimisation problems in the field of operations research. Moreover, with the P-NP-problem, the class NP represents the most important unsolved question in computer science. The first part of this thesis is devoted to the study of NP-complete-, and more generally, NP-hard problems. It aims at improving our understanding of this important complexity class by systematically studying how altering NP-hard sets affects their NP-hardness. This research is related to longstanding open questions concerning the complexity of unions of disjoint NP-complete sets, and the existence of sparse NP-hard sets. The second part of the thesis is also dedicated to complexity classes but takes a different perspective: In a sense, after investigating the interior of complexity classes in the first part, the focus shifts to the description of complexity classes and thereby to the exterior in the second part. It deals with the description of complexity classes through leaf languages, a uniform framework which allows us to characterise a great variety of important complexity classes. The known concepts are complemented by a new leaf-language model. To a certain extent, this new approach combines the advantages of the known models. The presented results give evidence that the connection between the theory of formal languages and computational complexity theory might be closer than formerly known.
This thesis deals with the management and analysis of source code, which is represented in XML. Using the elementary methods of the XML repository, the XML source code representation is accessed, changed, updated, and saved. We reason about the source code, refactor source code and we visualize dependency graphs for call analysis. The visualized dependencies between files, modules, or packages are used to structure the source code in order to get a system, which is easily to comprehend, to modify and to complete. Sophisticated methods have been developed to slice the source code in order to obtain a working package of a large system, containing only a specific functionality. The basic methods, on which the visualizations and analyses are built on can be changed like changing a plug-in. The visualization methods can be reused in order to handle arbitrary source code representations, e.g., JAML, PHPML, PROLOGML. Dependencies of other context can be visualized, too, e.g., ER diagrams, or website references. The tool SCAV supports source code visualization and analyzing methods.
No abstract available
Mobile telecommunication systems of the 3.5th generation (3.5G) constitute a first step towards the requirements of an all-IP world. As the denotation suggests, 3.5G systems are not completely new designed from scratch. Instead, they are evolved from existing 3G systems like UMTS or cdma2000. 3.5G systems are primarily designed and optimized for packet-switched best-effort traffic, but they are also intended to increase system capacity by exploiting available radio resources more efficiently. Systems based on cdma2000 are enhanced with 1xEV-DO (EV-DO: evolution, data-optimized). In the UMTS domain, the 3G partnership project (3GPP) specified the High Speed Packet Access (HSPA) family, consisting of High Speed Downlink Packet Access (HSDPA) and its counterpart High Speed Uplink Packet Access (HSUPA) or Enhanced Uplink. The focus of this monograph is on HSPA systems, although the operation principles of other 3.5G systems are similar. One of the main contributions of our work are performance models which allow a holistic view on the system. The models consider user traffic on flow-level, such that only on significant changes of the system state a recalculation of parameters like bandwidth is necessary. The impact of lower layers is captured by stochastic models. This approach combines accurate modeling and the ability to cope with computational complexity. Adopting this approach to HSDPA, we develop a new physical layer abstraction model that takes radio resources, scheduling discipline, radio propagation and mobile device capabilities into account. Together with models for the calculation of network-wide interference and transmit powers, a discrete-event simulation and an analytical model based on a queuing-theoretical approach are proposed. For the Enhanced Uplink, we develop analytical models considering independent and correlated other-cell interference.