Modeling power in multi-functionality sensor network applications
Martínez-Català, Rafael V.
With the migration of a Wireless Sensor Network (WSN) over various evolving applications, power estimation and profiling during the design cycle become critical issues and present hurdles in reducing the design time. Furthermore, with a growing size of the network, simulating the behavior of each sensor node is not feasible. It is important to devise an approach that provides a network-wide picture of power consumption and of variations in power usage under changes in the network and/or node application in the network. In this paper, we present a modular power estimation technique which simplifies the power modeling of any sensor network application. In particular, we are interested in analyzing the behavior of power consumption if one or more modules of the WSN platform in the application are changed during the design cycle or after the deployment. The proposed technique is susceptible to applications changes on the fly and is particularly beneficial in networks with large number of nodes. We perform experiments modifying parameters of a ZigBee based sensor network application such as packet size, sampling rate, functionality (encryption) and sensor types. We present the results, demonstrating an error less than 3% in all the experiments performed, and insights into the results.
Rachit Agarwal, Rafael V. Martinez-Catala, Sean Harte, Cedric Segard, Brendan O'Flynn, "Modeling Power in Multi-functionality Sensor Network Applications," sensorcomm, pp.507-512, 2008 Proceedings of the Second International Conference on Sensor Technologies and Applications, August 25-August 31 2008, Cap Esterel, France
Power , Sensor Networks , Functionality , Modular
Agarwal, R., Martinez-Catala, R.V., Harte, S., Segard, C., O'Flynn, B. 2008. Modeling Power in Multi-functionality Sensor Network Applications. In: IEEE Proceedings of the Second International Conference on Sensor Technologies and Applications. Cap Esterel, France 25-31 August 25 2008.
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