A careful planning of sleeping activities is essential for guaranteeinglong operational time to energy constrained IoT devices, giventhe extremely low energy consumption required during the sleepingmode. Neighbor discovery instead requires nodes to continuously listento the radio channel to detect potential and unpredictable messagescoming from the arrival of new nodes. These two contrasting needsraise a fundamental question: should a node be active and listen to thechannel or sleep and save energy? Hardware manufacturers introduceddedicated low-power circuitry to allow an energy efficient fast duty cycle(Wake-on Radio) or designed to wake up the main processor whenspecial packets are received (Wake-up Radio). In this work we proposea novel analytic model optimizing the number of discovered peers for agiven energy budget. Our theoretical study demonstrates the existenceof an optimum duty cycle in a wide range of operating environments.We designed an adaptive algorithm that dynamically tracks the optimumeven in non-stationary conditions, only using local device estimations,therefore allowing nodes to optimize their own duty cycle. Nodes globallyconverge to a system-wide optimum of a minimal network discoveryenergy cost.
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