An adaptive energy-efficient MAC protocol for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
MoteLab: a wireless sensor network testbed
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Accurate prediction of power consumption in sensor networks
EmNets '05 Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors
Software-based on-line energy estimation for sensor nodes
Proceedings of the 4th workshop on Embedded networked sensors
Distributed energy measurements in wireless sensor networks
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Crankshaft: an energy-efficient MAC-protocol for dense wireless sensor networks
EWSN'07 Proceedings of the 4th European conference on Wireless sensor networks
Improving sensornet performance by separating system configuration from system logic
EWSN'10 Proceedings of the 7th European conference on Wireless Sensor Networks
Making sensornet MAC protocols robust against interference
EWSN'10 Proceedings of the 7th European conference on Wireless Sensor Networks
Realistic simulation of energy consumption in wireless sensor networks
EWSN'12 Proceedings of the 9th European conference on Wireless Sensor Networks
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This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today's most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today's widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.