1,573 research outputs found

    Achieving Adaptation Through Live Virtual Machine Migration in Two-Tier Clouds

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    This thesis presents a model-driven approach for application deployment and management in two-tier heterogeneous cloud environments. For application deployment, we introduce the architecture, the services and the domain specific language that abstract common features of multi-cloud deployments. By leveraging the architecture and the language, application deployers author a deployment model that captures the high-level structure of the application. The deployment model is then translated into deployment workflows on specific clouds. As a use case, we introduce a live VM migration framework that maintains the application quality of services through VM migrations across two tier-clouds. The proposed framework can monitor the performance of the applications and their underlying infrastructure and plan and executes VM migrations to eliminate hotspots in a datacenter. We evaluate both the application deployment architecture and the live migration on public clouds

    HPC Application Cloudification: The StreamFlow Toolkit

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    Context-aware management of multi-device services in the home

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    MPhilMore and more functionally complex digital consumer devices are becoming embedded or scattered throughout the home, networked in a piecemeal fashion and supporting more ubiquitous device services. For example, activities such as watching a home video may require video to be streamed throughout the home and for multiple devices to be orchestrated and coordinated, involving multiple user interactions via multiple remote controls. The main aim of this project is to research and develop a service-oriented multidevice framework to support user activities in the home, easing the operation and management of multi-device services though reducing explicit user interaction. To do this, user contexts i.e., when and where a user activity takes place, and device orchestration using pre-defined rules, are being utilised. A service-oriented device framework has been designed in four phases. First, a simple framework is designed to utilise OSGi and UPnP functionality in order to orchestrate simple device operation involving device discovery and device interoperability. Second, the framework is enhanced by adding a dynamic user interface portal to access virtual orchestrated services generated through combining multiple devices. Third the framework supports context-based device interaction and context-based task initiation. Context-aware functionality combines information received from several sources such as from sensors that can sense the physical and user environment, from user-device interaction and from user contexts derived from calendars. Finally, the framework supports a smart home SOA lifecycle using pre-defined rules, a rule engine and workflows

    Adaptive Composition in Dynamic Service Environments

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    Due to distribution, participant autonomy and lack of local control, service-based systems operate in highly dynamic and uncertain environments. In the face of such dynamism and volatility, the ability to manage service changes and exceptions during composite service execution is a vital requirement. Most current adaptive composition approaches, however, fail to address service changes without causing undesirable disruptions in execution or considerably degrading the quality of the composite application. In response, this paper presents a novel adaptive execution approach, which efficiently handles service changes occurring at execution time, for both repair and optimisation purposes. The adaptation is performed as soon as possible and in parallel with the execution process, thus reducing interruption time, increasing the chance of a successful recovery, and producing the most optimal solution according to the current environment state. The effectiveness of the proposed approach is demonstrated both analytically and empirically through a case study evaluation applied in the framework of learning object composition. In particular, the results show that, even with frequent changes (e.g. 20 changes per service execution), or in the cases where interference with execution is non-preventable (e.g., when an executed service delivers unanticipated quality values), our approach manages to recover from the situation with minimal interruption
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