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Reactive Systems
"... Mobile devices like smartphones are getting increasingly im-portant in our daily lifes. They are used in various en-vironments and have to dynamically adapt themselves ac-cordingly in order to provide an optimal runtime behavior. Naturally, adapting to continuously changing environmental conditions ..."
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Mobile devices like smartphones are getting increasingly im-portant in our daily lifes. They are used in various en-vironments and have to dynamically adapt themselves ac-cordingly in order to provide an optimal runtime behavior. Naturally, adapting to continuously changing environmental conditions is a challenging task because mobile devices are always limited in their resources and have to adapt in real-time. In this paper, we introduce an approach that enables resource limited devices to adapt to changing conditions us-ing dynamic software product lines techniques. Therefore, feature models are reduced to a specific hardware context before installing the adaptive mobile application on the de-vice. This reduces the amount of possible configurations that are compatible with the device and, thereby, minimizes the costs and the duration of an adaptation during runtime.
User-centric Adaptation Analysis of Multi-tenant Services
, 2015
"... Multi-tenancy is a key pillar of cloud services. It allows different users to share computing and virtual re-sources transparently, meanwhile guaranteeing substantial cost savings. Due to the trade-off between scala-bility and customisation, one of the major drawbacks of multi-tenancy is limited con ..."
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Multi-tenancy is a key pillar of cloud services. It allows different users to share computing and virtual re-sources transparently, meanwhile guaranteeing substantial cost savings. Due to the trade-off between scala-bility and customisation, one of the major drawbacks of multi-tenancy is limited configurability. Since users may often have conflicting configuration preferences, offering the best user experience is an open challenge for the service providers. Besides, the users, their preferences and the operational environment may change during the service operation, jeopardising the satisfaction of user preferences. In this paper we present an approach to support user-centric adaptation of multi-tenant services. We describe how to engineer the ac-tivities of the MAPE (Monitoring, Analysis, Planning, Execution) loop to support user-centric adaptation, and focus on the adaptation analysis. Our analysis computes a service configuration that optimises user satisfaction, complies with infrastructural constraints, and minimises reconfiguration obtrusiveness when user or service related changes take place. To support our analysis, we model multi-tenant services and user preferences by using feature and preference models, respectively. We illustrate our approach by utilising different cases of virtual desktops. Our results demonstrate the effectiveness of the analysis in improving user preferences satisfaction in a negligible time.
Dynamic Adaptation of Service Compositions with Variability Models
"... Web services run in complex contexts where arising events may compromise the quality of the whole system. Thus, it is desirable to count on autonomic mechanisms to guide the self-adaptation of service compositions according to changes in the computing infrastructure. One way to achieve this goal is ..."
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Web services run in complex contexts where arising events may compromise the quality of the whole system. Thus, it is desirable to count on autonomic mechanisms to guide the self-adaptation of service compositions according to changes in the computing infrastructure. One way to achieve this goal is by im-plementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone. In this paper, we propose a solution based on a semantically rich variability model to support the dynamic adaptation of service compositions. When a problematic event arises in the context, this model is leveraged for decision-making. The activation and deactivation of features in the variability model result in changes in a composi-tion model that abstracts the underlying service composition. These changes are reflected into the service composition by adding or removing fragments of Busi-ness Process Execution Language (WS-BPEL) code, which can be deployed at runtime. In order to reach optimum adaptations, the variability model and its possible configurations are verified at design time using Constraint Program-ming. An evaluation demonstrates several benefits of our approach, both at design time and at runtime.
iMinds-Distrinet, KU Leuven
"... Dynamic software product lines (DSPLs) combine the ad-vantages of traditional SPLs, such as an explicit variabil-ity model connected to an integrated repository of reusable code artefacts, with the ability to exploit a system’s vari-ability at runtime. When a system needs to adapt, for ex-ample to c ..."
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Dynamic software product lines (DSPLs) combine the ad-vantages of traditional SPLs, such as an explicit variabil-ity model connected to an integrated repository of reusable code artefacts, with the ability to exploit a system’s vari-ability at runtime. When a system needs to adapt, for ex-ample to changes in operational environment or functional requirements, DSPL systems are capable of adapting their behaviour dynamically, thus avoiding the need to halt, re-compile and redeploy. The field of DSPL engineering is still in formation and general-purpose DSPL development languages and tools are rare. In this paper we introduce a language and execution environment for developing and running dynamic SPLs. Our work builds on ABS, a lan-guage and integrated development environment with dedi-cated support for implementing static software product lines. Our ABS extension advances the scope of ABS to dynamic SPL engineering. Systems developed using ABS are com-piled to Java, and are thus executable on a wide range of platforms.
Dynamic Adaptation with Distributed Control in Paradigm
"... Adaptation of a component-based system can be achieved in the coordination modeling language Paradigm through the special component McPal. McPal regulates the propagation of new behaviour and guides the changes in the components and in their coordination. Here we show how McPal may delegate part of ..."
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Adaptation of a component-based system can be achieved in the coordination modeling language Paradigm through the special component McPal. McPal regulates the propagation of new behaviour and guides the changes in the components and in their coordination. Here we show how McPal may delegate part of its control to local adaptation managers, created on-the-fly, allowing for distribution of the adaptation indeed. We illustrate the approach for the well-known example of the dining philosophers problem, by modeling migration from a deadlock-prone solution to a deadlock-free and starvation-free solution without any system quiescence. The system migration goes through various stages, exhibiting a shift of control among McPal and its helpers, and changing degrees of orchestrated and choreographic collaboration. The distributed system adaptation is formally verified using the mCRL2 model checker. Key words: component-based systems, dynamic system adaptation, distributed control, formal verification 1.
Executable Modelling of Dynamic Software Product Lines in the ABS Language
"... N.B. When citing this work, cite the original published paper. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-212399 ..."
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N.B. When citing this work, cite the original published paper. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-212399
Adaptive Model-Driven User Interface Development Systems
"... and other research outputs Adaptive model-driven user interface development sys-tems Journal Article ..."
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and other research outputs Adaptive model-driven user interface development sys-tems Journal Article
darmstadt.de
"... Reducing feature models to improve runtime adaptivity on resource limited devices ..."
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Reducing feature models to improve runtime adaptivity on resource limited devices
