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Context-aware reconfiguration of autonomic managers in real-time control applications

Published: 07 June 2010 Publication History

Abstract

We consider autonomic applications to systems for which continuous perfect monitoring of state is not possible. We use Exact-State Observers (ESO) to provide enhanced information about the system state. To achieve optimal configuration of the autonomic controller itself, over a wide range of environmental operating conditions, and across a wide range of unique application domains, we implement a new architecture for dynamic supervision and control systems in which a policy-based autonomic engine automatically selects both its monitoring and actuator components to suit ambient operating conditions.
By using a suite of ESOs tuned for different tradeoffs between real-time responsiveness and extent of system disturbance tolerated, and a policy mechanism to contextually select the most appropriate observer at any given time, we achieve self-configuring and self-optimising behaviours whilst keeping the complexity, resource-requirements and adaptation latency low.

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D. J. Simon. Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. John Wiley and Sons, 2006.
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Zhao y., Tan, Y., Gong Z., Gu, X., Wamboldt, M., Self-Correlating Predictive Information Tracking for Large-Scale production Systems, proc. ACM/IEEE Intl. Conf. Automatic Computing, Barcelona, Spain, pp 33--42, 2009.
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Byrski W., Optimal State Observers with Moving and Expanding Observation Window, Proc. IASTED, XII Intl. Conf. Modelling & Simulation, Innsbruck, Austria, 1993, p.68
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Anthony R, Policy-centric integration and dynamic composition of autonomic computing techniques, 4th Intl. Conf. Autonomic Computing (ICAC), FL, USA, June 2007, IEEE Computer Society.
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  • (2022)Targeting uncertainty in smart CPS by confidence-based logicJournal of Systems and Software10.1016/j.jss.2021.111065181:COnline publication date: 22-Apr-2022
  • (2020)HAFLoopFuture Generation Computer Systems10.1016/j.future.2019.12.026105:C(607-630)Online publication date: 1-Apr-2020
  • (2017)An expert system for pre-diagnostics screening using neurofeedback signals2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)10.1109/MMAR.2017.8046902(636-641)Online publication date: Aug-2017
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    cover image ACM Conferences
    ICAC '10: Proceedings of the 7th international conference on Autonomic computing
    June 2010
    246 pages
    ISBN:9781450300742
    DOI:10.1145/1809049

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    • IEEE
    • University of Arizona: University of Arizona

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 June 2010

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    Author Tags

    1. autonomics
    2. exact-state observers
    3. policy-based computing

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    View all
    • (2022)Targeting uncertainty in smart CPS by confidence-based logicJournal of Systems and Software10.1016/j.jss.2021.111065181:COnline publication date: 22-Apr-2022
    • (2020)HAFLoopFuture Generation Computer Systems10.1016/j.future.2019.12.026105:C(607-630)Online publication date: 1-Apr-2020
    • (2017)An expert system for pre-diagnostics screening using neurofeedback signals2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)10.1109/MMAR.2017.8046902(636-641)Online publication date: Aug-2017
    • (2011)Context-aware device self-configuration using self-organizing mapsProceedings of the 2011 workshop on Organic computing10.1145/1998642.1998647(13-22)Online publication date: 18-Jun-2011

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