Markov decision processes for control of a sensor network-based health monitoring system
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
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We discuss a novel control methodology for power management in heterogeneous distributed sensor networks. Many algorithms for resource management in sensor networks require complete knowledge of the external environment and the sensor network system, and are rule-based; this restricts their use in dynamic environments. We present an event based control optimization formulation of the resource management problem and discuss a method to adaptively change desired system performance of the sensor network in response to events. This functionality is critical in field-deployable sensor networks where continuous operation is expensive and system adaptation is critical for extended operation in the face of dynamic external events. We show results on various synthetic heterogeneous sensor networks where only partially accurate information about the sensing system is available and illustrate the efficacy of the control algorithm in handling such incorrect models with a negligible increase in transmission of the optimal control settings. We show that the run-time performance of the control algorithm scales quadratically with increasing number of sensors.