96 research outputs found

    Policy-based autonomic control service

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    Recently, there has been a considerable interest in policy-based, goal-oriented service management and autonomic computing. Much work is still required to investigate designs and policy models and associate meta-reasoning systems for policy-based autonomic systems. In this paper we outline a proposed autonomic middleware control service used to orchestrate selfhealing of distributed applications. Policies are used to adjust the systems autonomy and define self-healing strategies to stabilize/correct a given system in the event of failures

    A deliberative model for self-adaptation middleware using architectural dependency

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    A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an architectural model, which provides a reference point for externalized adaptation. In this paper, it is described how dependencies are used as a basis to systems' self-understanding and subsequent architectural reconfigurations. The approach is based on the combination of: instrumentation services, a dependency meta-model and a system controller. In particular, the latter uses self-healing repair rules (or conflict resolution strategies), based on extensible beliefs, desires and intention (EBDI) model, to reflect reconfiguration changes back to a target application under examination

    Model-Based Self-Managing Systems Engineering

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    Towards a systemic approach to autonomic systems engineering

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    EXPERIMENTING WITH ANOMALY DETECTION BY MINING LARGE-SCALE INFORMATION NETWORKS

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    Social networks have formed the basis of many studies into large networks analysis. Whilst much is already known regarding efficient algorithms for large networks analysis, data mining, knowledge diffusion, anomaly detection, viral marketing, to mention. More recent research is focussing on new classes of efficient approximate algorithms that can scale to billion nodes and edges. To this end, this paper presents an extension of an algorithm developed originally to analyse large scale-free autonomic networks called the Global Observer Model. In this paper, the algorithm is studied in the context of monitoring large-scale information networks. Hence, taking into account the size of such networks, the proposed algorithm starts by partitioning the graph using structural network metrics. This is followed by a calculation of the graph nodes ’ metrics, which are used in the selection from the original graph a subset of nodes to be monitored. The paper is organised as follows: it will outline the problem definition and algorithm, then will proceed to a brief description of an event and signature based model used to instrument monitored nodes. Finally, the paper will conclude with an evaluation using an infection detection scenario, which will be followed by a general discussion and proposed further work

    A Service-Based Architecture for In-Vehicle Telematics Systems

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    The growing needs to access information in remote, mobile environments have sparked interests in so-called InVehicle Telematics Systems (IVTS) [1]. These relatively new systems have the potential to deliver computing facilitates to road vehicles, which may include in-vehicle infotainment, route-guidance and navigation and the provision of vital information resources used by fleet haulage companies and emergency services (police, fire and ambulance). This paper describes the EmergeITS project, which is concerned with the use of IVTS for emergency fire service applications. In particular, the paper describes a distributed service-based architecture, based on the Jini middleware technology, which can be used to provide fault tolerant application services to remote in-vehicle computers and mobile devices such as Palm devices and WAP phones
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