Characterizing robustness in dynamic real-time systems

Authors:
Dazhang Gu;Lonnie Welch;Frank Drews;Klaus Ecker
Affiliations:
Center for Intelligent, Distributed, and Dependable Systems, School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio 45701, USA;Center for Intelligent, Distributed, and Dependable Systems, School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio 45701, USA;Center for Intelligent, Distributed, and Dependable Systems, School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio 45701, USA;Center for Intelligent, Distributed, and Dependable Systems, School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio 45701, USA
Venue:
Journal of Systems and Software
Year:
2007

Citing 6
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Abstract

The problem of robust task allocation is motivated by the need to deploy real-time systems in dynamic operational environments. Existing robust allocation approaches employ coarse robustness metrics, which can result in poor allocations. This paper proposes a metric that accurately characterizes a system's robustness within feasible allocation regions. An allocation algorithm is provided to find allocations that are both feasible and robust; the robustness as measured by the metric is shown to have theoretical bounds. Experiments demonstrate that the algorithm produces good and scalable performance compared with several heuristic algorithms.