2,121 research outputs found

    Role-based Adaptation of Business Reference Models to Application Models: An Enterprise Modeling Methodology for Software Construction

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    Large software systems are in need of a construction plan to determine and define every concept and element used in order to not end up in complex, unusable, and cost-intensive systems. Different modeling languages, like UML, support the development of these construction plans and visualize them for the system’s stakeholders. Reference models are a specific kind of construction plan, used as templates for information systems and already capture business domain knowledge for reuse and tailoring. By adaptation, reference models are tailored to enterprise-specific application models, which can be used for software construction and maintenance. However, current adaptation methods suffer from the limitations of pure object-oriented development (e.g., identity issues, large inheritance trees, and inflexibility). In this thesis, the usage of roles as the sole adaptation mechanism is proposed to solve these challenges. With the help of conceptual roles, it is possible to create rich model variations and adaptations from existing (industry standard) reference models, and it is simpler to react to model evolution and changing business logic. Adaptations can be specified with more precision by maintaining or even increasing the model’s expressiveness. As a consequence, the role-enriched final application model can be used to describe software systems in more detail, with different perspectives, and, if available, can be implemented with a role supporting programming language. However, even without this step, the application model itself will provide valuable insights into the overall construction plan of a software system by the combination of structure and behavior and a clear separation of relatively stable domain knowledge from its use case specific adaptation

    makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

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    A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language—also directly usable by WSN developers—and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype—including the complete tool-chain and underlying system support—sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions

    Web Engineering for Workflow-based Applications: Models, Systems and Methodologies

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    This dissertation presents novel solutions for the construction of Workflow-based Web applications: The Web Engineering DSL Framework, a stakeholder-oriented Web Engineering methodology based on Domain-Specific Languages; the Workflow DSL for the efficient engineering of Web-based Workflows with strong stakeholder involvement; the Dialog DSL for the usability-oriented development of advanced Web-based dialogs; the Web Engineering Reuse Sphere enabling holistic, stakeholder-oriented reuse

    A Service-Oriented Approach for Network-Centric Data Integration and Its Application to Maritime Surveillance

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    Maritime-surveillance operators still demand for an integrated maritime picture better supporting international coordination for their operations, as looked for in the European area. In this area, many data-integration efforts have been interpreted in the past as the problem of designing, building and maintaining huge centralized repositories. Current research activities are instead leveraging service-oriented principles to achieve more flexible and network-centric solutions to systems and data integration. In this direction, this article reports on the design of a SOA platform, the Service and Application Integration (SAI) system, targeting novel approaches for legacy data and systems integration in the maritime surveillance domain. We have developed a proof-of-concept of the main system capabilities to assess feasibility of our approach and to evaluate how the SAI middleware architecture can fit application requirements for dynamic data search, aggregation and delivery in the distributed maritime domain

    Adaptive Middleware for Resource-Constrained Mobile Ad Hoc and Wireless Sensor Networks

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    Mobile ad hoc networks: MANETs) and wireless sensor networks: WSNs) are two recently-developed technologies that uniquely function without fixed infrastructure support, and sense at scales, resolutions, and durations previously not possible. While both offer great potential in many applications, developing software for these types of networks is extremely difficult, preventing their wide-spread use. Three primary challenges are: 1) the high level of dynamics within the network in terms of changing wireless links and node hardware configurations,: 2) the wide variety of hardware present in these networks, and: 3) the extremely limited computational and energy resources available. Until now, the burden of handling these issues was put on the software application developer. This dissertation presents three novel programming models and middleware systems that address these challenges: Limone, Agilla, and Servilla. Limone reliably handles high levels of dynamics within MANETs. It does this through lightweight coordination primitives that make minimal assumptions about network connectivity. Agilla enables self-adaptive WSN applications via the integration of mobile agent and tuple space programming models, which is critical given the continuously changing network. It is the first system to successfully demonstrate the feasibility of using mobile agents and tuple spaces within WSNs. Servilla addresses the challenges that arise from WSN hardware heterogeneity using principles of Service-Oriented Computing: SOC). It is the first system to successfully implement the entire SOC model within WSNs and uniquely tailors it to the WSN domain by making it energy-aware and adaptive. The efficacies of the above three systems are demonstrated through implementation, micro-benchmarks, and the evaluation of several real-world applications including Universal Remote, Fire Detection and Tracking, Structural Health Monitoring, and Medical Patient Monitoring

    GoalD: A Goal-Driven Deployment Framework for Dynamic and Heterogeneous Computing Environments

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    Context: Emerging paradigms like Internet of Things and Smart Cities utilize advanced sensing and communication infrastructures, where heterogeneity is an inherited feature. Applications targeting such environments require adaptability and context-sensitivity to uncertain availability and failures in resources and their ad-hoc networks. Such heterogeneity is often hard to predict, making the deployment process a challenging task. Objective: This paper proposes GoalD as a goal-driven framework to support autonomous deployment of heterogeneous computational resources to fulfill requirements, seen as goals, and their correlated components on one hand, and the variability space of the hosting computing and sensing environment on the other hand. Method: GoalD comprises an offline and an online stage to fulfill autonomous deployment by leveraging the use of goals. Deployment configuration strategies arise from the variability structure of the Contextual Goal Model as an underlying structure to guide autonomous planning by selecting available as well as suitable resources at runtime. Results: We evaluate GoalD on an existing exemplar from the selfadaptive systems community – the Tele Assistance Service provided by Weyns and Calinescu [1]. Furthermore, we evaluate the scalability of GoalD on a repository consisting of 430,500 artifacts. The evaluation results demonstrate the usefulness and scalability of GoalD in planning the deployment of a system with thousands of components in a few milliseconds

    Riding the (brain) waves! Using neural oscillations to inform bilingualism research

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    The study of the brains’ oscillatory activity has been a standard technique to gain insights into human neurocognition for a relatively long time. However, as a complementary analysis to ERPs, only very recently has it been utilized to study bilingualism and its neural underpinnings. Here, we provide a theoretical and methodological starter for scientists in the (psycho)linguistics and neurocognition of bilingualism field(s) to understand the bases and applications of this analytical tool. Towards this goal, we provide a description of the characteristics of the human neural (and its oscillatory) signal, followed by an in-depth description of various types of EEG oscillatory analyses, supplemented by figures and relevant examples. We then utilize the scant, yet emergent, literature on neural oscillations and bilingualism to highlight the potential of how analyzing neural oscillations can advance our understanding of the (psycho)linguistic and neurocognitive understanding of bilingualism

    Modelling Event-Based Interactions in Component-Based Architectures for Quantitative System Evaluation

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    This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques
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