A Decision-Theoretic Planner with Dynamic Component Reconfiguration for Distributed Real-Time Applications

Distributed real-time embedded (DRE) systems perform sequences of coordination and heterogeneous data manipulation tasks in dynamic environments to meet specified goals. Autonomous operation of DRE systems can benefit from the integrated operation of (1) a decision-theoretic spreading activation partial order planner (SA-POP) that combines task planning and scheduling in uncertain environments with (2) a resource allocation and control engine (RACE) middleware framework that integrates multiple resource management algorithms for (re)deploying and (re)configuring task sequence components in these systems. This paper demonstrates the effectiveness of SA-POP and RACE in managing and executing mission goals for a multisatellite application. Our results show that combining planning, scheduling and resource constraints dynamically is the key to implementing autonomy in DRE systems

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