177 research outputs found

    Flexible modeling and execution of choreographies

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    Approaches to address domain specific problems often share overlapping requirements but typically satisfy them in a unique manner for example using service-oriented concepts. The notion of Collaborative, Dynamic & Complex (CDC) systems has been proposed in literature to address the requirements of application domains such as eScience and Collective Adaptive Systems in a unified, generic manner. CDC systems are characterized by dealing with potentially large amounts of data and/or participating applications which engage in complex interactions specified by some collaboration protocol. Furthermore, the need for adaptation mechanisms is a common requirement and users from these application domains are typically no IT experts. The choreography concept originally known from collaborations in the business domain captures the interaction between independent parties from a global perspective. Each party is denoted as a choreography participant, which is implemented by a workflow or a service. This concept provides a way to model and execute for example complex eScience experiments involving multiple scientific fields, scientific methods, and time and/or length scales as a set of coupled workflows. However, typical choreography concepts as described in literature do not provide the desired level of flexibility and ease of use in both modeling and execution to address the requirements of users in CDC system application domains such as eScience. Thus, existing choreography concepts have to be considerably extended by introducing the Model-as-you-go for Choreographies approach in this thesis as a central notion providing capabilities for the flexible modeling and execution of choreographies. In the context of this approach, we provide a concept for fostering reuse in choreography modeling in the form of so-called choreography fragments. Such fragments can be extracted from existing and inserted into new choreography models in order to save time as well as reuse established and approved logic by inexperienced modelers in a less error-prone manner. Furthermore, we provide support for the user-driven control of the complete choreography life cycle. This effectively allows users to automatically deploy the workflow models implementing a choreography as well as starting, pausing, resuming, and terminating a choreography instance, which is formed through the collective execution of workflow instances. Most importantly, the underlying complexity of managing a set of coupled workflow instances is completely hidden from the users. Additional flexibility is given by a concept that allows to re-run already executed choreography logic in order to enforce the convergence of a calculation towards a particular result or to react to errors with parameter changes. The proposed concepts are implemented in a message-based system, the ChorSystem, which is able to handle the challenges of choreography life cycle management from deployment, to run time control and the re-run of logic. Furthermore, the modeling and run time monitoring are integrated into one graphical tool supporting the seamless transition from modeling to execution of choreographies. The concepts, their supporting algorithms, and the prototypical ChorSystem are validated by a set of case studies from different CDC system application domains and evaluated by performance measurements showing the practical applicability

    Reversible Computation: Extending Horizons of Computing

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    This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

    CHOReOS Middleware Specification (D3.1)

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    This deliverable specifies the main concepts of the CHOReOS middleware architecture. Starting from the Future Internet (FI) challenges for scalability, heterogeneity, mobility, awareness, and adaptation that have been investigated in prior work done in WP1, we introduce the aforementioned concepts to deal with the requirements derived from the FI challenges. In particular, we propose an extensible and scalable service discovery approach for the organization and discovery of services that relies on multiple service discovery protocols. Moreover, we introduce an extensible and scalable approach, based on the service bus paradigm, for service access that features the integration and adaptation of multiple interaction protocols. Furthermore, we propose solutions that enable the execution of FI service compositions that range from compositions of choreographed services, developed according to the CHOReOS development process, to massive compositions of things. Finally, we detail the Cloud & Grid middleware facilities that support the overall middleware and the choreographies that are built on it, via a unified API that provides access to multiple cloud infrastructures (e.g., Amazon EC2, HP Open Cirrus, private clouds)

    Concepts for handling heterogeneous data transformation logic and their integration with TraDE middleware

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    The concept of programming-in-the-Large became a substantial part of modern computerbased scientific research with an advent of web services and the concept of orchestration languages. While the notions of workflows and service choreographies help to reduce the complexity by providing means to support the communication between involved participants, the process still remains generally complex. The TraDE Middleware and underlying concepts were introduced in order to provide means for performing the modeled data exchange across choreography participants in a transparent and automated fashion. However, in order to achieve both transparency and automation, the TraDE Middleware must be capable of transforming the data along its path. The data transformation’s transparency can be difficult to achieve due to various factors including the diversity of required execution environments and complicated configuration processes as well as the heterogeneity of data transformation software which results in tedious integration processes often involving the manual wrapping of software. Having a method of handling data transformation applications in a standardized manner can help to simplify the process of modeling and executing scientific service choreographies with the TraDE concepts applied. In this master thesis we analyze various aspects of this problem and conceptualize an extensible framework for handling the data transformation applications. The resulting prototypical implementation of the presented framework provides means to address data transformation applications in a standardized manner

    Interdisciplinary Machine Learning Methods for Particle Physics

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    Following the discovery of a Higgs boson-like particle in the summer of 2012 at the Large Hadron Collider (LHC) at CERN, the high-energy particle physics community has prioritized its thorough study. As part of a comprehensive plan to investigate the many combinations of production and decay of the Standard Model Higgs boson, this thesis describes a continued search for this particle produced in association with a leptonically-decaying vector boson (i.e. a W or Z boson) and decaying into a pair of tau leptons. In Run 1 at the LHC, ATLAS researchers were able to set an upper constraint on the signal strength of this process at μ = σ/σ_SM \u3c 5.6 with 95% confidence using 20.3 fb^-1 of collision data collected at a center-of-mass energy of √s = 8 TeV. My thesis work, which builds upon and extends the Run 1 analysis structure, takes advantage of an increased center-of-mass energy in Run 2 of the LHC of √s = 13 TeV as well as 139 fb^-1 of data, approximately seven times the amount used for the Run 1 analysis. While the higher center-of-mass energy in Run 2 yields a higher expected cross-section for this process, the analysis faces the additional challenges of two newly-considered final states, a higher number of simultaneous interactions per event, and a novel neural network-based background estimation technique. I also describe advanced machine learning techniques I have developed to support tau identification in the ATLAS High-Level Trigger as well as predicting and analyzing the dynamics of many-body systems such as 3D motion capture data of choreography

    Reversible Computation: Extending Horizons of Computing

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    This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

    Modellierung und Ausführung einer gekoppelten Festkörpersimulation mit Workflow-Choreographien

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    Im wissenschaftlichen Umfeld wird vermehrt die Workflow-Technologie eingesetzt, um Simulationen oder Berechnungen computergesteuert auszuführen. Die vorliegende Arbeit beschäftigt sich mit der Modellierung einer gekoppelten Festkörpersimulation als Workflow-Choreographie nach dem Top-Down-Ansatz. Auftauchende Herausforderungen werden identifiziert und mögliche Lösungsansätze beschrieben. Aufbauend auf dem Modellierungsergebnis werden die für die Ausführung der gekoppelten Festkörpersimulation benötigten Prozesse implementiert und vorgestellt. Die fertige Modellierung wird im Vergleich mit den Anforderungen beurteilt. Die Modellierung kann als Basis für zukünftige Arbeiten dienen und bietet Ansätze für aufbauende Untersuchungen. Dadurch wird eine Verfeinerung für zukünftige Workflowmodellierungen auf Basis einer Choreographie ermöglicht
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