2014 · 18 citations · 19 references
ComputingComputer ScienceComputer SystemsComputer ArchitectureDistributed SystemsSystems ArchitectureDistributed CoordinationDynamic ReconfigurationHierarchical DesignModular OrganizationReconfiguration StrategiesAutonomic ComputingComponent-based ArchitecturesDiscrete ControlModular CoordinationMulti-tier ArchitecturePerformance DegradationState Space ExplorationSystem Reconfiguration
Complex computing systems are increasingly self-adaptive, with an autonomic computing approach for their administration. Real systems require the co-existence of multiple autonomic management loops, each complex to design. However their uncoordinated co-existence leads to performance degradation and possibly to inconsistency. There is a need for methodological supports facilitating the coordination of multiple autonomic managers. In this paper we propose a method focusing on the discrete control of the interactions of managers. We follow a component-based approach and explore modular discrete control, allowing to break down the combinatorial complexity inherent to the state-space exploration technique. This improves scalability of the approach and allows constructing a hierarchical control. It also allows re-using complex managers in different contexts without modifying their control specifications. We build a component-based coordination of managers, with introspection, adaptivity and reconfiguration. We validate our method on a multiple-loop multi-tier system.
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The vision of autonomic computing
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The FRACTAL component model and its support in Java
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