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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.
This work deals with teams in teleoperation scenarios, where one human team partner (supervisor) guides and controls multiple remote entities (either robotic or human) and coordinates their tasks. Such a team needs an appropriate infrastructure for sharing information and commands. The robots need to have a level of autonomy, which matches the assigned task. The humans in the team have to be provided with autonomous support, e.g. for information integration. Design and capabilities of the human-robot interfaces will strongly influence the performance of the team as well as the subjective feeling of the human team partners. Here, it is important to elaborate the information demand as well as how information is presented. Such human-robot systems need to allow the supervisor to gain an understanding of what is going on in the remote environment (situation awareness) by providing the necessary information. This includes achieving fast assessment of the robot´s or remote human´s state. Processing, integration and organization of data as well as suitable autonomous functions support decision making and task allocation and help to decrease the workload in this multi-entity teleoperation task. Interaction between humans and robots is improved by a common world model and a responsive system and robots. The remote human profits from a simplified user interface providing exactly the information needed for the actual task at hand. The topic of this thesis is the investigation of such teleoperation interfaces in human-robot teams, especially for high-risk, time-critical, and dangerous tasks. The aim is to provide a suitable human-robot team structure as well as analyze the demands on the user interfaces. On one side, it will be looked on the theoretical background (model, interactions, and information demand). On the other side, real implementations for system, robots, and user interfaces are presented and evaluated as testbeds for the claimed requirements. Rescue operations, more precisely fire-fighting, was chosen as an exemplary application scenario for this work. The challenges in such scenarios are high (highly dynamic environments, high risk, time criticality etc.) and it can be expected that results can be transferred to other applications, which have less strict requirements. The present work contributes to the introduction of human-robot teams in task-oriented scenarios, such as working in high risk domains, e.g. fire-fighting. It covers the theoretical background of the required system, the analysis of related human factors concepts, as well as discussions on implementation. An emphasis is placed on user interfaces, their design, requirements and user testing, as well as on the used techniques (three-dimensional sensor data representation, mixed reality, and user interface design guidelines). Further, the potential integration of 3D sensor data as well as the visualization on stereo visualization systems is introduced.
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.
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.
The Internet sees an ongoing transformation process from a single best-effort service network into a multi-service network. In addition to traditional applications like e-mail,WWW-traffic, or file transfer, future generation networks (FGNs) will carry services with real-time constraints and stringent availability and reliability requirements like Voice over IP (VoIP), video conferencing, virtual private networks (VPNs) for finance, other real-time business applications, tele-medicine, or tele-robotics. Hence, quality of service (QoS) guarantees and resilience to failures are crucial characteristics of an FGN architecture. At the same time, network operations must be efficient. This necessitates sophisticated mechanisms for the provisioning and the control of future communication infrastructures. In this work we investigate such echanisms for resilient FGNs. There are many aspects of the provisioning and control of resilient FGNs such as traffic matrix estimation, traffic characterization, traffic forecasting, mechanisms for QoS enforcement also during failure cases, resilient routing, or calability concerns for future routing and addressing mechanisms. In this work we focus on three important aspects for which performance analysis can deliver substantial insights: load balancing for multipath Internet routing, fast resilience concepts, and advanced dimensioning techniques for resilient networks. Routing in modern communication networks is often based on multipath structures, e.g., equal-cost multipath routing (ECMP) in IP networks, to facilitate traffic engineering and resiliency. When multipath routing is applied, load balancing algorithms distribute the traffic over available paths towards the destination according to pre-configured distribution values. State-of-the-art load balancing algorithms operate either on the packet or the flow level. Packet level mechanisms achieve highly accurate traffic distributions, but are known to have negative effects on the performance of transport protocols and should not be applied. Flow level mechanisms avoid performance degradations, but at the expense of reduced accuracy. These inaccuracies may have unpredictable effects on link capacity requirements and complicate resource management. Thus, it is important to exactly understand the accuracy and dynamics of load balancing algorithms in order to be able to exercise better network control. Knowing about their weaknesses, it is also important to look for alternatives and to assess their applicability in different networking scenarios. This is the first aspect of this work. Component failures are inevitable during the operation of communication networks and lead to routing disruptions if no special precautions are taken. In case of a failure, the robust shortest-path routing of the Internet reconverges after some time to a state where all nodes are again reachable – provided physical connectivity still exists. But stringent availability and reliability criteria of new services make a fast reaction to failures obligatory for resilient FGNs. This led to the development of fast reroute (FRR) concepts for MPLS and IP routing. The operations of MPLS-FRR have already been standardized. Still, the standards leave some degrees of freedom for the resilient path layout and it is important to understand the tradeoffs between different options for the path layout to efficiently provision resilient FGNs. In contrast, the standardization for IP-FRR is an ongoing process. The applicability and possible combinations of different concepts still are open issues. IP-FRR also facilitates a comprehensive resilience framework for IP routing covering all steps of the failure recovery cycle. These points constitute another aspect of this work. Finally, communication networks are usually over-provisioned, i.e., they have much more capacity installed than actually required during normal operation. This is a precaution for various challenges such as network element failures. An alternative to this capacity overprovisioning (CO) approach is admission control (AC). AC blocks new flows in case of imminent overload due to unanticipated events to protect the QoS for already admitted flows. On the one hand, CO is generally viewed as a simple mechanism, AC as a more complex mechanism that complicates the network control plane and raises interoperability issues. On the other hand, AC appears more cost-efficient than CO. To obtain advanced provisioning methods for resilient FGNs, it is important to find suitable models for irregular events, such as failures and different sources of overload, and to incorporate them into capacity dimensioning methods. This allows for a fair comparison between CO and AC in various situations and yields a better understanding of the strengths and weaknesses of both concepts. Such an advanced capacity dimensioning method for resilient FGNs represents the third aspect of this work.
Parametric weighted finite automata (PWFA) are a multi-dimensional generalization of weighted finite automata. The expressiveness of PWFA contains the expressiveness of weighted finite automata as well as the expressiveness of affine iterated function system. The thesis discusses theory and applications of PWFA. The properties of PWFA definable sets are studied and it is shown that some fractal generator systems can be simulated using PWFA and that various real and complex functions can be represented by PWFA. Furthermore, the decoding of PWFA and the interpretation of PWFA definable sets is discussed.
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.
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.
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.
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.