The complexity of computer networks has been rising over the last decades. Increasing interconnectivity between multiple devices, growing complexity of performed tasks and a strong collaboration between nodes are drivers for this phenomenon. An example is represented by Internet-of-Things devices, whose relevance has been rising in recent years. The increasing number of devices requiring updates and supervision makes maintenance more difficult. Human interaction, in this case, is costly and requires a lot of time. To overcome this, self-adaptive software systems (SAS) can be used. SAS are a subset of autonomous systems which can monitor themselves and their environment to adapt to changes without human interaction. In the literature, different approaches for engineering SAS were proposed, including techniques for executing adaptations on multiple devices based on generated plans for reacting to changes. Among those solutions, also decentralised approaches can be found. To the best of our knowledge, no approach for engineering a SAS exists which tolerates errors during the execution of adaptation in a decentralised setting. While some approaches for role-based execution reset the application in case of a single failure during the adaptation process, others do not make assumptions about errors or do not consider an erroneous environment. In a real-world environment, errors will likely occur during run-time, and the adaptation process could be disturbed. This work aims to perform adaptations in a decentralised way on role-based systems with a relaxed consistency constraint, i.e., errors during the adaptation phase are tolerated. This increases the availability of nodes since no rollbacks are required in case of a failure. Moreover, a subset of applications, such as drone swarms, would benefit from an approach with a relaxed consistency model since parts of the system that adapted successfully can already operate in an adapted configuration instead of waiting for other peers to apply the changes in a later iteration. Moreover, if we eliminate the need for an atomic adaptation execution, asynchronous execution of adaptation would be possible. In that case, we can supervise the adaptation process for a long time and ensure that every peer takes the planned actions as soon as the internal task execution allows it. To allow for a relaxed consistent way of adaptation execution, we develop a decentralised adaptation execution protocol, which supports the notion of eventual consistency. As soon as devices reconnect after network congestion or restore their internal state after local failures, our protocol can coordinate the recovery process among multiple devices to attempt recovery of a globally consistent state after errors occur. By superseding the need for a central instance, every peer who received information about failing peers can start the recovery process. The developed approach can restore a consistent global configuration if almost all peers fail. Moreover, the approach supports asynchronous adaptations, i.e., the peers can execute planned adaptations as soon as they are ready, which increases overall availability in case of delayed adaptation of single nodes. The developed protocol is evaluated with the help of a proof-of-concept implementation. The approach was run in five different experiments with thousands of iterations to show the applicability and reliability of this novel approach. The time for execution of the protocol and the number of exchanged messages has been measured to compare the protocol for different error cases and system sizes, as well as to show the scalability of the approach. The developed solution has been compared to a blocking approach to show the feasibility compared to an atomic approach. The applicability in a real-world scenario has been described in an empirical study using an example of a fire-extinguishing drone swarm. The results show that an optimistic approach to adaptation is suitable and specific scenarios can benefit from the improved availability since no rollbacks are required. Systems can continue their work regardless of the failures of participating nodes in large-scale systems.:Abstract VI 1. Introduction 1 1.1. Motivational Use-Case 2 1.2. Problem Definition 3 1.3. Objectives 4 1.4. Research Questions 5 1.5. Contributions 5 1.6. Outline 6 2. Foundation 7 2.1. Role Concept 7 2.2. Self-Adaptive Software Systems 13 2.3. Terminology for Role-Based Self-Adaptation 15 2.4. Consistency Preservation and Consistency Models 17 2.5. Summary 20 3. Related Work 21 3.1. Role-Based Approaches 22 3.2. Actor Model of Computation and Akka 23 3.3. Adaptation Execution in Self-Adaptive Software Systems 24 3.4. Change Consistency in Distributed Systems 33 3.5. Comparison of the Evaluated Approaches 40 4. The Decentralised Consistency Compensation Protocol 43 4.1. System and Error Model 43 4.2. Requirements to the Concept 44 4.3. The Usage of Roles in Adaptations 45 4.4. Protocol Overview 47 4.5. Protocol Description 51 4.6. Protocol Corner- and Error Cases 64 4.7. Summary 66 5. Prototypical Implementation 67 5.1. Technology Overview 67 5.2. Reused Artifacts 68 5.3. Implementation Details 70 5.4. Setup of the Prototypical Implementation 76 5.5. Summary 77 6. Evaluation 79 6.1. Evaluation Methodology 79 6.2. Evaluation Setup 80 6.3. Experiment Overview 81 6.4. Default Case: Successful Adaptation 84 6.5. Compensation on Disconnection of Peers 85 6.6. Recovery from Failed Adaptation 88 6.7. Impact of Early Activation of Adaptations 91 6.8. Comparison with a Blocking Approach 92 6.9. Empirical Study: Fire Extinguishing Drones 95 6.10. Summary 97 7. Conclusion and Future Work 99 7.1. Recap of the Research Questions 99 7.2. Discussion 101 7.3. Future Work 101 A. Protocol Buffer Definition 103 Acronyms 108 Bibliography 109

Entnommen aus: „Ludz, Ursula: Zu dieser Veröffentlichung” (S.9): „Mit der vorliegenden Veröffentlichung wird also eine Rückblende auf die „Ursprünge“ von Hannah Arendts Totalitarismusanalyse vorgeschlagen. Beide, die selbst entfernten Textstücke aus der ersten Auflage des Totalitarismusbuches und die Antwort an Eric Voegelin, sind aufschlußreiche Dokumente, um Arendts Totalitarismustheorie und deren Entwicklung genauer kennenzulernen und zu beurteilen...”

Die wachsende Anzahl an Robotikanwendungen, in denen mehrere Roboter ein gemeinsames Ziel verfolgen, erfordert eine gesonderte Betrachtung der Interaktion zwischen diesen Robotern mit Bezug auf den damit entstehenden Datenaustausch. Dieser muss hierbei effizient betrieben werden und die Sicherheit des gesamt Systems gewährleisten. Diese Masterarbeit stellt eine Simulationsumgebung vor, welche anhand von Testszenarien und Austauschstrategien Roboterkonstellationen prüft und Messergebnisse ausliefert. Zu Beginn der Arbeit werden drei Datenaustauschverfahren betrachtet und anschließend Publikationen vorgestellt, in denen Datenaustausch betrieben wird und Simulatoren für die Nutzbarkeit der Simulationsumgebung untersucht. Die anschließenden Kapitel behandeln das Konzept und die Implementierung der Testumgebung erläutert, wobei Roboter aus einer Menge von Hardware Komponenten und Zielen beschrieben werden. Der Aufbau des Experiments umfasst die verschiedenen Umgebungen, Testszenarien und Roboterkonfiguration. Der Aufbau beschreibt die Grundlage für die Auswertung der Testergebnisse.

Meiotic nuclear oscillations in the fission yeast Schizosaccharomyces pombe are crucial for proper chromosome pairing and recombination. We report a mechanism of these oscillations on the basis of collective behavior of dynein motors linking the cell cortex and dynamic microtubules that extend from the spindle pole body in opposite directions. By combining quantitative live cell imaging and laser ablation with a theoretical description, we show that dynein dynamically redistributes in the cell in response to load forces, resulting in more dynein attached to the leading than to the trailing microtubules. The redistribution of motors introduces an asymmetry of motor forces pulling in opposite directions, leading to the generation of oscillations. Our work provides the first direct in vivo observation of self-organized dynamic dynein distributions, which, owing to the intrinsic motor properties, generate regular large-scale movements in the cell.

Modeling complex gene interacting systems as Boolean networks lead to a significant simplification of computational investigation. This can be achieved by discretization of the expression level to ON or OFF states and classifying the interactions to inhibitory and activating. In this respect, Boolean functions are responsible for the evolution of the binary elements of the Boolean networks. In this thesis, we investigate the mostly used Boolean functions in modeling gene regulatory networks. Moreover, we introduce a new type of function with strong inhibitory namely the veto function. Our computational and analytic studies on the verity of the networks capable of constructing the same State Transition Graph lead to define a new concept namely the “degeneracy” of Boolean functions. We further derive analytically the sensitivity of the Boolean functions to perturbations. It turns out that the veto function forms the most robust dynamics. Furthermore, we verify the applicability of veto function to model the yeast cell cycle networks. In particular, we show that in an intracellular signal transduction network [Helikar et al, PNAS (2008)], the functions with veto are over-represented by a factor exceeding the over-representation of threshold functions and canalyzing functions in the same system. The statistics of the connections of the functional networks are studied in detail. Finally, we look at a different scale of biological phenomena using a binary model. We propose a simple correlation-based model to describe the pattern formation of Fly eye. Specifically, we model two different procedures of Fly eye formation, and provide a generic approach for Fly eye simulation.

The focus of this work is the theoretical and experimentell descreption of so-called Reactive Multilayer Systems (RMS). The RMS consist of at least two mostly metallic materials, which can exothermic response with each other. Using magnetron sputter deposition (MSD) several hundred to thousands alternating layers are produced. The periodic thickness varies between 10-150 nm and the total thickness between 10-100 µ m . The exotermic reaction is effected by an activation energy, e.g. with an electric spark. In this case a phase transition of the RMS materials, which are in a metastable equilibrium, will take place. This released energy in the shape of heat, which actvates the reaction in the neighboring areas. It forms a self-sustaining thermal wave through the RMS foil. In this case the amount of energy is present, that a solder on the RMS or the joining samples or even the material itself can be melted. Therefore the RMS can be used as a heat source for joining two components. The major advantage of this technology is the very low heat input in the bonding components, due to the milliseconds of the reaction. Thus the components are heated only superfical and there is no structural damage. Thus a very low-stress joining is possible. Furthermore is guaranteed, because of the metallic materials, a very high electrical and thermal conductivity. For the theoretical characterization of the physical and chemical processes within the RMS FEM-Simulations of the absolut temperature and the propagation velocity are preformed. In order to calculate the tmeperature ditribution in the components a new method will presented. It is thus possible to calculate the temperature penetration of the components to determine potential thermal barrier layer-thickness and the meltig time. Thus parameters for the specific joint problem such as period thickness, etc. of the RMS are derived. Modelling the heat transport after joining with RMS it is possible to derive a corralation between the thermal conductivity and shear strength. To quantify the theoretical results and to require certain parameters for the calculations experiments were preformed. The RMS will be investigated experimentally in terms of their enthalpy H , propagation velocity v , nascent temperature, melting time t schmelz , interdiffusion zone w , phase transition and its use as inovative heat source for joining components. The experimental results are compared with the theortical and complet this work.

Im Rahmen des 180jährigen Jubiläums der technischen Universität Chemnitz fand am 28. April 2016 das zweite Studierendensymposium der Fakultät Informatik statt. Das Studierendensymposium Informatik richtete sich inhaltlich an alle Themen rund um die Informatik und ihre Anwendungen: Ob Hardware oder Software, ob technische Lösungen oder Anwenderstudien, ob Programmierung oder Verwendung, ob Hardcore-Technik oder gesellschaftliche Fragestellungen – alles, was mit informatischen Lösungen zu tun hat, war willkommen. Das Studierendensymposium Informatik war dabei weder auf die Fakultät Informatik noch auf die TU Chemnitz begrenzt. Es wurden explizit Einreichungen aus thematisch angrenzenden Fächern beworben und Hochschulen der Region in die Planung und Organisation eingebunden. Der Tagungsband enthält die 21 Beitrage, die auf dem Symposium vorgestellt wurden. / In the course of the 180 year anniversary of the Technische Universität Chemnitz the Department of Computer Science held the second Students Symposium on April 18, 2016. The symposium addressed topics related to computer science and its applications: Whether hardware or software, whether technical solutions or user studies, whether programming or use, whether hardcore technology or social issues - everything concerned with computational solutions was welcomed. The Students Symposium included explicitly submissions from thematically adjacent departments and involved universities in the region in planning and organization. The proceedings contain the 21 papers (full and short), which were presented at the symposium.

Neuro-computational models allow to study the brain mechanisms involved in intelligent behavior and extract essential computational principles which can be implemented in cognitive systems. They are a promising solution to achieve a brain-like artificial intelligence that can compete with natural intelligence on realistic behaviors. A crucial property of intelligent behavior is motivation, defined as the incentive to interact with the world in order to achieve specific goals, either extrinsic (obtaining rewards such as food or money, or avoiding pain) or intrinsic (satisfying one’s curiosity, fun). In the human brain, motivated or goal-directed behavior depends on a network of different structures, including the prefrontal cortex, the basal ganglia and the limbic system. Dopamine, a neurotransmitter associated with reward processing, plays a central role in coordinating the activity of this network. It structures processing in high-level cognitive areas along a limbic-associative-motor gradient and impacts the learning capabilities of the whole system. In this habilitation thesis, I present biologically-constrained neuro-computational models which investigate the role of dopamine in visual object categorization and memory retrieval (Vitay and Hamker, 2008), reinforcement learning and action selection (Vitay and Hamker, 2010), the updating, learning and maintenance of working memory (Schroll et al., 2012) and timing processes (Vitay and Hamker, 2014). These models outline the many mechanisms by which the dopaminergic system regulates cognitive and emotional behavior: bistable processing modes in the cerebral cortex, modulation of synaptic transmission and plasticity, allocation of cognitive resources and signaling of relevant events. Finally, I present a neural simulator able to simulate a variety of neuro-computational models efficiently on parallel architectures (Vitay et al., 2015). / Neuronale Modelle nach dem Vorbild des Gehirns bieten die Möglichkeit intelligente, kognitive Prozesse nicht nur besser zu verstehen, sondern sie stellen auch eine vielversprechende Lösung dar, um eine Gehirn-ähnliche künstliche Intelligenz für Wahrnehmung und Verhaltensweisen zu erreichen, die mit natürlicher Intelligenz konkurrieren kann. Eine entscheidende Eigenschaft von intelligentem Verhalten ist Motivation, definiert als der Anreiz mit der Welt zu interagieren, um bestimmte Ziele zu erreichen, sei es extrinsisch (Belohnungen wie Nahrung oder Geld zu erhalten oder die Vermeidung von Schmerzen) oder intrinsisch (die Neugier zu befriedigen, Spaß zu haben). Im menschlichen Gehirn basiert motiviertes oder zielgerichtetes Verhalten auf einem Netzwerk von verschiedenen Strukturen, einschließlich des präfrontalen Cortex, der Basalganglien und des limbischen Systems. Dopamin, ein Neurotransmitter, welcher der Belohnungsverarbeitung zugeordnet wird, spielt eine zentrale Rolle bei der Koordination der Aktivität in diesem Netzwerk. Es strukturiert die Verarbeitung in High-Level-kognitiven Bereichen entlang eines limbischen-assoziativ-motor Gradienten und beinflusst die Lernfähigkeit des gesamten Systems. In dieser Habilitation, präsentiere ich biologisch motivierte neuronale Modelle, die die Rolle von Dopamin in der visuellen Objektkategorisierung und Gedächtnisabruf (Vitay and Hamker, 2008), Reinforcement Lernen und Aktionsauswahl (Vitay and Hamker, 2010), Aktualisierung, Lernen und Aufrechterhaltung von Arbeitsgedächtnis (Schroll et al., 2012) und Timing Prozessen (Vitay and Hamker, 2014) untersuchen. Diese Modelle beschreiben Mechanismen, durch die das dopaminerge System kognitives und emotionales Verhalten reguliert: bistabile Verarbeitungsmodi in der Hirnrinde, Plastizität und Modulation der synaptischen Übertragung, Zuweisung von kognitiven Ressourcen und Signalisierung von relevanten Ereignissen. Schließlich beschreibe ich einen neuronalen Simulator, der in in der Lage ist, eine Vielzahl von neuronalen Modellen effizient auf parallelen Architekturen zu simulieren (Vitay et al., 2015).

L'obésité est depuis quelques années reconnue comme un des fléaux du XXIe siècle en affectant environ 10% de la population adulte mondiale. Le passage de l'obésité au stade de pandémie est le résultat de multiples facteurs dont une mauvaise hygiène alimentaire et une sédentarité croissante. La découverte récente de l'existence d'un état inflammatoire chronique au cours de l'obésité pouvant intervenir dans la physiopathologie de la maladie et de ses nombreuses complications fait aujourd'hui l'objet d'intenses investigations. Or, le tissu adipeux (TA) qui, parallèlement à son activité métabolique, possède également une activité sécrétoire intense, est un acteur majeur de ce syndrome inflammatoire. L'autotaxine (ATX), l'adiponectine et la résistine sont les médiateurs de l'inflammation sécrétés par le TA. Si le rôle de ces facteurs dans la régulation du métabolisme est bien établi, leurs effets sur d'autres organes ne sont pas toujours connus. Il est notamment intéressant d'étudier leurs effets dans le système nerveux central (SNC), les récepteurs de certains y étant présent. Dans ce contexte, nous avons dans un premier temps étudié l'effet de l'ATX sur le stress oxydant généré par le H2O2 (peroxyde d'hydrogène) et sur l'inflammation induit par le lipopolysaccharide (LPS) ou le trimethylétain (TMT) dans les cellules microgliales murines, cellules immunitaires résidentes du SNC. Nos résultats montrent pour la première fois, l'effet anti-oxydant et anti-inflammatoire de l'ATX sur les cellules microgliales. Chez la souris, le TMT affecte la région hippocampique du SNC et nous avons montré qu'il induit la production d'ATX après 5 jours d'une injection i.p. de TMT. Ce qui suggère un rôle important de l'ATX dans la régulation de l'homéostasie des microglies et du SNC ainsi que dans la neuroinflammation. L'effet du TMT sur l'inflammation produite par le TA a également été étudié et les résultats montrent que le TMT induit une réponse inflammatoire dans deux types cellulaires du TA : adipocytes et macrophages ainsi que dans le TA de souris obèse ob/ob. Ensuite, nous avons sous-cloné les ADNc de l'adiponectine et de la résistine dans des vecteurs d'expression eucaryote afin d'étudier leurs effets sur les cellules microgliales dans des conditions normales ou inflammatoires. Cette étude devrait permettre une meilleure compréhension de l'influence du TA sur le SNC et donc la relation entre l'obésité les maladies neurodégénérative afin de proposer de nouvelles approches thérapeutiques. / In the last years, Obesity has been considered a major health issue with around 10% of the world population affected. The causes of this pandemy are multiple, but include bad alimentary habits and an increasing settle way of life. The recent discovery that chronic inflammation during obesity was associated with this disease physiopathology and others complications is the center of many investigations. Adipose tissue (AT), in addition to its metabolic activity, has an intense secretory activity and is a main player in this inflammatory syndrome. Autotaxin (ATX), adiponectin and resistin are such mediators secreted by AT. These factors functions in metabolism regulation are well described, but their effects on others organs are not always known. As it has been shown that some of these factors receptors are present in the central nervous system (CNS), it is interesting to study their effects in this organ. In this context, we initially studied the effect of ATX on the oxidative stress generated by H2O2 (hydrogen peroxide) and inflammation induced by lipopolysaccharide (LPS) or trimethyltin (TMT) in murine microglial cells, resident immune cells of the CNS. Our results show for the first time, the anti-oxidant and anti-inflammatory effects of ATX in microglial cells. In mice, TMT affects hippocampal region of CNS and we showed that ATX RNA is up regulated in the hippocampus 5 days post TMT treatment. Our results suggest that ATX could be involved in the regulation of microglia homeostasis and in neuroinflammation. The effect of TMT on the inflammation produced by the AT has also been studied and the results show that TMT induces an inflammatory response in two cell types of AT: adipocytes and macrophages and in fat tissue from ob/ob mice.We then subcloned the cDNA of adiponectin and resistin in eukaryotic expression vectors to study their effects on microglial cells under normal or inflammatory conditions. This study should lead to better understanding of adipose tissue influence on the CNS and therefore the relationship between obesity and neurodegenerative diseases to develop new therapeutic approaches.

Nos sociétés sont de plus en plus préoccupées par l’impact très nocif des ressources énergétiques polluantes, essentiellement, le pétrole, le charbon et le gaz. Ainsi, l’intérêt dans l’utilisation des énergies renouvelables et propres est en constant augmentation et la conception de nouveaux systèmes énergétiques est devenue un challenge scientifique et technologique. Pour concevoir de nouvelles solutions énergétiques compétitives et efficaces, les fabricants de composants (panneaux solaires, pile à combustible, convertisseurs, etc.) et les secteurs industriels concernés sont confrontés à des problématiques d’optimisation, de contrôle et de durabilité. Par ailleurs, les sources d’énergie renouvelable sont dépendantes de plusieurs facteurs incontrôlables (lieu géographique, météorologie, etc.). Pour parer à ces facteurs, et donc au caractère aléatoire de disponibilité énergétique, l’hybridation des sources et la gestion énergétique peut s’avérer être une approche pertinente pour la conception de solutions énergétiques efficaces. Cette thèse est une contribution au problème de l’hybridation et de la gestion d’énergie. Plus précisément, nous considérons un système hybride composé de panneaux solaires photovoltaïques et d’une pile à combustible. Ce système est supposé être doté de convertisseurs et d’un système de stockage (batterie et super-condensateurs). / Our societies are increasingly concerned about the very harmful impact of clean energy resources, mainly oil, coal and gas. Thus, interest in the use of renewable and clean energy is constantly increasing and the development of new energy systems has become a scientific and technological challenge. To develop new competitive and efficient energy solutions, manufacturers of components (solar panels, fuel cells, inverters, etc.) and industrial sectors are facing problems of optimization, control and durability. In addition, renewable energy sources depend on several uncontrollable factors (geographical location, weather, etc.). To address these factors, and thus the randomness of energy availability, sources hybridization and energy management can prove to be an appropriate approach for the design of efficient energy solutions. This thesis is a contribution to the problem of hybridization and energy management. More precisely, we consider a hybrid system composed of photovoltaic solar panels and a fuel cell. This system is supposed to be equipped with converters and storage system (battery and supercapacitors). The goal is to develop control strategies to extract the maximum power available from the considered sources and to optimize the overall energy system to meet the load requirements. To do this, our approach is based on the tracking of the maximum power point and the use of compensators.