Ressourcen Optimierung von SOA-Technologien in eingebetteten Netzwerken

Embedded networks are fundamental infrastructures of many different kinds of domains, such as home or industrial automation, the automotive industry, and future smart grids. Yet they can be very heterogeneous, containing wired and wireless nodes with different kinds of resources and service capabilities, such as sensing, acting, and processing. Driven by new opportunities and business models, embedded networks will play an ever more important role in the future, interconnecting more and more devices, even from other network domains. Realizing applications for such types of networks, however, is a highly challenging task, since various aspects have to be considered, including communication between a diverse assortment of resource-constrained nodes, such as microcontrollers, as well as flexible node infrastructure. Service Oriented Architecture (SOA) with Web services would perfectly meet these unique characteristics of embedded networks and ease the development of applications. Standardized Web services, however, are based on plain-text XML, which is not suitable for microcontroller-based devices with their very limited resources due to XML's verbosity, its memory and bandwidth usage, as well as its associated significant processing overhead. This thesis presents methods and strategies for realizing efficient XML-based Web service communication in embedded networks by means of binary XML using EXI format. We present a code generation approach to create optimized and dedicated service applications in resource-constrained embedded networks. In so doing, we demonstrate how EXI grammar can be optimally constructed and applied to the Web service and service requester context. In addition, so as to realize an optimized service interaction in embedded networks, we design and develop an optimized filter-enabled service data dissemination that takes into account the individual resource capabilities of the nodes and the connection quality within embedded networks. We show different approaches for efficiently evaluating binary XML data and applying it to resource constrained devices, such as microcontrollers. Furthermore, we will present the effectful placement of binary XML filters in embedded networks with the aim of reducing both, the computational load of constrained nodes and the network traffic. Various evaluation results of V2G applications prove the efficiency of our approach as compared to existing solutions and they also prove the seamless and successful applicability of SOA-based technologies in the microcontroller-based environment

A policy language definition for provenance in pervasive computing

Recent advances in computing technology have led to the paradigm of pervasive computing, which provides a means of simplifying daily life by integrating information processing into the everyday physical world. Pervasive computing draws its power from knowing the surroundings and creates an environment which combines computing and communication capabilities. Sensors that provide high-resolution spatial and instant measurement are most commonly used for forecasting, monitoring and real-time environmental modelling. Sensor data generated by a sensor network depends on several influences, such as the configuration and location of the sensors or the processing performed on the raw measurements. Storing sufficient metadata that gives meaning to the recorded observation is important in order to draw accurate conclusions or to enhance the reliability of the result dataset that uses this automatically collected data. This kind of metadata is called provenance data, as the origin of the data and the process by which it arrived from its origin are recorded. Provenance is still an exploratory field in pervasive computing and many open research questions are yet to emerge. The context information and the different characteristics of the pervasive environment call for different approaches to a provenance support system. This work implements a policy language definition that specifies the collecting model for provenance management systems and addresses the challenges that arise with stream data and sensor environments. The structure graph of the proposed model is mapped to the Open Provenance Model in order to facilitating the sharing of provenance data and interoperability with other systems. As provenance security has been recognized as one of the most important components in any provenance system, an access control language has been developed that is tailored to support the special requirements of provenance: fine-grained polices, privacy policies and preferences. Experimental evaluation findings show a reasonable overhead for provenance collecting and a reasonable time for provenance query performance, while a numerical analysis was used to evaluate the storage overhead

Robust Complex Event Pattern Detection over Streams

Event stream processing (ESP) has become increasingly important in modern applications. In this dissertation, I focus on providing a robust ESP solution by meeting three major research challenges regarding the robustness of ESP systems: (1) while event constraint of the input stream is available, applying such semantic information in the event processing; (2) handling event streams with out-of-order data arrival and (3) handling event streams with interval-based temporal semantics. The following are the three corresponding research tasks completed by the dissertation: Task I - Constraint-Aware Complex Event Pattern Detection over Streams. In this task, a framework for constraint-aware pattern detection over event streams is designed, which on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism and adjusts the processing strategy dynamically by producing early feedback, releasing unnecessary system resources and terminating corresponding pattern monitor. Task II - Complex Event Pattern Detection over Streams with Out-of-Order Data Arrival. In this task, a mechanism to address the problem of processing event queries specified over streams that may contain out-of-order data is studied, which provides new physical implementation strategies for the core stream algebra operators such as sequence scan, pattern construction and negation filtering. Task III - Complex Event Pattern Detection over Streams with Interval-Based Temporal Semantics. In this task, an expressive language to represent the required temporal patterns among streaming interval events is introduced and the corresponding temporal operator ISEQ is designed

A security concept for distributed data processing systems

Today, the amount of raw data available is abundant. As only a small part of this data is in a form fit for further processing, there is many data left to analyze and process. At the same time, cloud services are ubiquitous and allow even small businesses to perform large tasks of distributed data processing without the significant costs required for a suitable computational infrastructure. However, as more and more users transfer their data into the cloud for processing and storage, concerns about data security arise. An extensive review of data security research in today's cloud solutions confirms these concerns to be justified. The existing strategies for securing one's data are not adequate for many use cases. Therefore, this work proposes a holistic security concept for distributed data processing in the cloud. For the purpose of providing security in heterogeneous cloud environments, it statically analyzes a data flow prior to execution and determines the optimal security measurements. Without imposing strict requirements on the cloud services involved, it can be deployed in a broad range of scenarios. The concept's generic design can be adopted by existing data rocessing tools. An exemplary implementation is provided for the mashup tool FlexMash. Requirements, such as data confidentiality, integrity, access control, and scalability were evaluated to be met.Die heutige Menge an vorhandenen Daten ist enorm. Viele davon müssen zunächst verarbeitet und analysiert werden, da nur ein geringer Teil dieser Daten für die weitere Verarbeitung geeignet ist. Cloud-basierte Dienste sind allgegenwärtig und erlauben es auch kleineren Unternehmen Datenverarbeitung durchzuführen, ohne die Kosten von notwendiger Infrastruktur tragen zu müssen. Mit einer zunehmenden Zahl an Nutzern von Clouds wachsen jedoch auch Bedenken der Sicherheit. Eine ausführliche Durchsicht der aktuellen Forschung zu diesem Thema bestätigt diese Bedenken und existierende Strategien zur Sicherung der eigenen Daten berücksichtigen viele Fälle nicht. Daher stellt diese Arbeit ein ganzheitliches Sicherheitskonzept für die verteilte Datenverarbeitung in der Cloud vor. Damit Sicherheit in heterogenen Cloudumgebungen gewährleistet werden kann, wird ein Datenfluss vor der Ausführung statisch analysiert und es werden die für diesen Fluss optimalen Sicherheitsmaßnahmen festgelegt. Das Konzept besitzt einen breiten Anwendungsbereich, da keine straffen Anforderungen an die genutzten Dienste gestellt werden. Das generische Design des Konzepts ermöglicht eine einfache Integration in bereits existierende Datenverarbeitungsanwendungen, wie beispielhaft an FlexMash gezeigt wird. Anforderungen, wie die Vertraulichkeit von Daten, deren Integrität, Zugriffskontrolle und Skalierbarkeit des Systems konnten erreicht werden

Methoden und Beschreibungssprachen zur Modellierung und Verifikation vonSchaltungen und Systemen: MBMV 2015 - Tagungsband, Chemnitz, 03. - 04. März 2015

Der Workshop Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV 2015) findet nun schon zum 18. mal statt. Ausrichter sind in diesem Jahr die Professur Schaltkreis- und Systementwurf der Technischen Universität Chemnitz und das Steinbeis-Forschungszentrum Systementwurf und Test. Der Workshop hat es sich zum Ziel gesetzt, neueste Trends, Ergebnisse und aktuelle Probleme auf dem Gebiet der Methoden zur Modellierung und Verifikation sowie der Beschreibungssprachen digitaler, analoger und Mixed-Signal-Schaltungen zu diskutieren. Er soll somit ein Forum zum Ideenaustausch sein. Weiterhin bietet der Workshop eine Plattform für den Austausch zwischen Forschung und Industrie sowie zur Pflege bestehender und zur Knüpfung neuer Kontakte. Jungen Wissenschaftlern erlaubt er, ihre Ideen und Ansätze einem breiten Publikum aus Wissenschaft und Wirtschaft zu präsentieren und im Rahmen der Veranstaltung auch fundiert zu diskutieren. Sein langjähriges Bestehen hat ihn zu einer festen Größe in vielen Veranstaltungskalendern gemacht. Traditionell sind auch die Treffen der ITGFachgruppen an den Workshop angegliedert. In diesem Jahr nutzen zwei im Rahmen der InnoProfile-Transfer-Initiative durch das Bundesministerium für Bildung und Forschung geförderte Projekte den Workshop, um in zwei eigenen Tracks ihre Forschungsergebnisse einem breiten Publikum zu präsentieren. Vertreter der Projekte Generische Plattform für Systemzuverlässigkeit und Verifikation (GPZV) und GINKO - Generische Infrastruktur zur nahtlosen energetischen Kopplung von Elektrofahrzeugen stellen Teile ihrer gegenwärtigen Arbeiten vor. Dies bereichert denWorkshop durch zusätzliche Themenschwerpunkte und bietet eine wertvolle Ergänzung zu den Beiträgen der Autoren. [... aus dem Vorwort

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC