Issue No.07 - July (2010 vol.9)
Raja Jurdak , CSIRO ICT Centre
Antonio G. Ruzzelli , University College Dublin, Dublin
Gregory M.P. O'Hare , University College Dublin, Dublin
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2010.35
Energy efficiency is a central challenge in sensor networks, and the radio is a major contributor to overall energy node consumption. Current energy-efficient MAC protocols for sensor networks use a fixed low-power radio mode for putting the radio to sleep. Fixed low-power modes involve an inherent trade-off: deep sleep modes have low current draw and high energy cost and latency for switching the radio to active mode, while light sleep modes have quick and inexpensive switching to active mode with a higher current draw. This paper proposes adaptive radio low-power sleep modes based on current traffic conditions in the network. It first introduces a comprehensive node energy model, which includes energy components for radio switching, transmission, reception, listening, and sleeping, as well as the often disregarded microcontroller energy component for determining the optimal sleep mode and MAC protocol to use for given traffic scenarios. The model is then used for evaluating the energy-related performance of our recently proposed RFIDImpulse protocol enhanced with adaptive low-power modes, and comparing it against BMAC and IEEE 802.15.4, for both MicaZ and TelosB platforms under varying data rates. The comparative analysis confirms that RFIDImpulse with adaptive low-power modes provides up to 20 times lower energy consumption than IEEE 802.15.4 in low traffic scenario. The evaluation also yields the optimal settings of low-power modes on the basis of data rates for each node platform, and provides guidelines and a simple algorithm for the selection of appropriate MAC protocol, low-power mode, and node platform for a given set of traffic requirements of a sensor network application.
RFID, wake-up radio, sleep mode, adaptive, energy efficiency, MAC protocols, routing protocols, energy model, sensor networks.
Raja Jurdak, Antonio G. Ruzzelli, Gregory M.P. O'Hare, "Radio Sleep Mode Optimization in Wireless Sensor Networks", IEEE Transactions on Mobile Computing, vol.9, no. 7, pp. 955-968, July 2010, doi:10.1109/TMC.2010.35