392,712 research outputs found

    A Framework for Evaluating Model-Driven Self-adaptive Software Systems

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    In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

    Towards the predictive analysis of cloud systems with e-Motions

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    Current methods for the predictive analysis of software systems are not directly applicable on self-adaptive systems as cloud systems, mainly due to their complexity and dynamism. To tackle the difficulties to handle the dynamic changes in the systems and their environments, we propose using graph transformation to define an adaptive com- ponent model and analysis tools for it, what allows us to carry on such analyses on dynamic architectures. Specifically, we use the e-Motions system to define the Palladio component model, and simulation-based analysis tools for it. Adaptation mechanisms are then specified as generic adaptation rules. This setting will allow us to study different mechanisms for the management of dynamic systems and their adaptation mechanisms, and different QoS metrics to be considered in a dynamic environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Membrane-based design and management methodology for parallel dynamically reconfigurable embedded systems

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    International audiencePartial and dynamic reconfiguration provides a relevant new dimension to design efficient parallel embedded systems. However, due to the encasing complexity of such systems, ensuring the consistency and parallelism management at runtime is still a key challenge. So architecture models and design methodology are required to allow for efficient component reuse and hardware reconfiguration management.This paper presents a distributed persistence management model and its implementation for reconfigurable multiprocessor systems on dynamically reconfigurable circuits. The proposed approach is inspired from the well-known component based models used in software applications development. Our model is based on membranes wrapping the systems components. The objective is to improve design productivity and ensure consistency by managing context switching and storage using modular distributed hardware controllers. These membranes are distributed and optimized with the aim to design self-adaptive systems by allowing dynamic changes in parallelism degree and contexts migration. Simulation and synthesis results are given to show performances and effectiveness of our methodology

    Microservices and Machine Learning Algorithms for Adaptive Green Buildings

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    In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

    Modelling and validation of a single-storey flexible double-skin façade system with a building energy simulation tool

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    Double skin facades are adaptive envelopes designed to improve building energy use and comfort performance. Their adaptive principle relies on the dynamic management of the cavity's ventilation flow and, when available, of the shading device. They can also be integrated with the environmental systems for heating, cooling, and ventilation. However, in most cases, the possible exploitation of the ventilation airflow is not fully enabled, as the adoption of only one or two possible airpath limits the possibility that this facade architecture offers, meaning that flexible interaction with the environmental systems cannot be planned. This work aims to develop, using an existing software tool for building energy simulation, a numerical model of a flexible double-skin facade module capable of fully exploiting the adaptive features of such an envelope concept by switching between different cavity ventilation strategies. Leveraging the "Double Glass Facade" component available in IDA ICE, a new model for a flexible double-skin facade module was developed, and its performance in replicating the thermophysical behaviours of such a dynamic system was assessed by comparison with experimental data collected through a dedicated experimental activity using one the outdoor test cells of the TWINS facility in Torino (Italy). The accuracy of the predictions of the new model for a flexible double-skin facade was in line with that obtained by the conventional "Double Glass Facade" component to simulate traditional double-skin facades. The mean bias errors obtained were lower than 1.5 degrees C and 4 W/m2, for air and surface temperature values and for transmitted long-wave or short-wave heat flux values, respectively. By establishing a new archetype model to study the performance and optimal integration of a large class of double-skin facade modules, including fully flexible ones, this work demonstrates the possibility of modifying existing models in building energy simulation tools to study unconventional building envelope model solutions such as adaptive facade systems

    A Framework for Evaluating Model-Driven Self-adaptive Software Systems

    Get PDF
    In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers
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