Easwaran, Arvind
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Publication Compositional Feasibility Analysis for Conditional Real-Time Task Models(2008-05-05) Anand, Madhukar; Easwaran, Arvind; Fischmeister, Sebastian; Lee, InsupConditional real-time task models, which are generalizations of periodic, sporadic, and multi-frame tasks, represent real world applications more accurately. These models can be classified based on a tradeoff in two dimensions – expressivity and hardness of schedulability analysis. In this work, we introduce a class of conditional task models and derive efficient schedulability analysis techniques for them. These models are more expressive than existing models for which efficient analysis techniques are known. In this work, we also lay the groundwork for schedulability analysis of hierarchical scheduling frameworks with conditional task models. We propose techniques that abstract timing requirements of conditional task models, and support compositional analysis using these abstractions.Publication Steering of Discrete Event Systems: Control Theory Approach(2005-07-12) Easwaran, Arvind; Kannan, Sampath; Sokolsky, OlegRuntime verification involves monitoring the system at runtime to check for conformance of the execution trace to user defined safety properties. Typically, run-time verifiers do not assume a system model and hence cannot predict violations until they occur. This limits the practical applicability of runtime verification. Steering is the process of predicting the occurrence of violations and preventing them by controlling system execution. Steerers can achieve this using a limited knowledge of the system model even in situations where it is infeasible to store the entire model. In this paper, we explore a control-theoretic view of steering for discrete event systems. We introduce an architecture for steering and also describe different steering paradigms.