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Sensor networks (SN) are rapidly becoming the tool of choice for monitoring. Their versatility makes them useful in numerous and diverse application domains. However, most SN deployments assume that the area and events to monitor/control are well known/understood at design time. Thus, sensors' configurations can be defined prior to their deployment. Nevertheless, when the purpose of an SN is to monitor the events of an uncharted environment, where the distribution and nature of events is uncertain, it is rather intricate to configure its sensors at design time. Instead, sensors should be able to self-configure at run time. In this paper, we propose a low-cost (in terms of energy and computation) collective approach that allows the sensors in an SN to collaboratively search for their most appropriate configurations only using their local knowledge. We empirically show that our approach can help sensors efficiently monitor environments where various dynamic events exist.
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