Experimental Assessment of the Battery Lifetime in WSN Based on the Duty-Cycle Current Average Method

Abstract

A great amount of work addressed methods for predicting the battery lifetime in wireless sensor systems. In spite of these efforts, the reported experimental results demonstrate that the duty-cycle current average method, which is widely used to this aim, fails in accurately estimating the battery life time of most of the presented wireless sensor system applications. The aim of this paper is to experimentally assess the duty-cycle current average method in order to give more effective insight on the effectiveness of the method. An electronic metering system, based on a dedicated PCB, has been designed and developed to experimentally measure node current consumption profiles and charge extracted from the battery in two selected case studies. A battery lifetime measurement (during 30 days) has been carried out. Experimental results have been assessed and compared with estimations given by using the duty-cycle current average method. Based on the measurement results, we show that the assumptions on which the method is based do not hold in real operating cases. The rationality of the duty-cycle current average method needs reconsidering.

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Barboni, L. and Valle, M. (2014) Experimental Assessment of the Battery Lifetime in WSN Based on the Duty-Cycle Current Average Method. Wireless Sensor Network, 6, 212-220. doi: 10.4236/wsn.2014.610021.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Lu, B. and Gungor, V.C. (2009) Online and Remote Motor Energy Monitoring and Fault Diagnostics Using Wireless Sensor Networks. IEEE Transactions on Industrial Electronics, 56, 4651-4659.
http://dx.doi.org/10.1109/TIE.2009.2028349
[2] Gungor, V.C. and Gerhard, P.H. (2009) Industrial Wireless Sensor Networks: Challenges, Design Principles, and Technical Approaches. IEEE Transactions on Industrial Electronics, 56, 4258-4265.
http://dx.doi.org/10.1109/TIE.2009.2015754
[3] Dondi, D., et al. (2008) Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks. IEEE Transactions on Industrial Electronics, 55, 2759-2766.
http://dx.doi.org/10.1109/TIE.2008.924449
[4] Agha, K.A., et al. (2009) Which Wireless Technology for Industrial Wireless Sensor Networks? The Development of OCARI Technology. IEEE Transactions on Industrial Electronics, 56, 4266-4278.
http://dx.doi.org/10.1109/TIE.2009.2027253
[5] Ahn, H.-S. and Ko, K.H. (2009) Simple Pedestrian Localization Algorithms Based on Distributed Wireless Sensor Networks. IEEE Transactions on Industrial Electronics, 56, 4296.
http://dx.doi.org/10.1109/TIE.2009.2017097
[6] Pierce, F.J. and Elliott, T.V. (2008) Regional and On-Farm Wireless Sensor Networks for Agricultural Systems in Eastern Washington. Computers and Electronics in Agriculture, 61, 32-43.
http://dx.doi.org/10.1016/j.compag.2007.05.007
[7] Lopez, J.A., et al. (2009) Development of a Sensor Node for Precision Horticulture. Sensors, 9, 3240-3255.
http://dx.doi.org/10.3390/s90503240
[8] Torvmark, K.H. Low Power Systems Using the CC1010. Chipcon Application Note AN017.
[9] Baleri, G. Guidelines for WSN Design and Deployment.
[10] The Battery Life Estimator. A Web-Based Calculator to Help Optimize Low-Power Applications.
http://www.silabs.com/support/pages/batterylifeestimator.aspx
[11] Yang, O. and Heinzelman, W.B. (2012) Modeling and Performance Analysis for Duty-Cycled MAC Protocols with Applications to S-MAC and X-MAC. IEEE Transactions on Mobile Computing, 11, 905-921.
http://dx.doi.org/10.1109/TMC.2011.121
[12] Jiang, X., Taneja, J., Ortiz, J., Tavakoli, A., Dutta, P., Jeong, J., et al. (2007) An Architecture for Energy Management in Wireless Sensor Networks. Special Issue on the Workshop on Wireless Sensor Network Architecture, 4, 31-36.
[13] Technical Data MPR-MIB Users Manual Revision B, June 2006 PN: 7430-0021-07. Technical Data MTS/MDA Sensor Board Users Manual Revision A, June 2007 PN: 7430-0020-05.
http://www.xbow.com/
[14] Gay, P., Welsh, M., Levis, P., Brewer, E., Von Behren, R. and Culler, D. (2003) The nesC Language: A Holistic Approach to Networked Embedded Systems. Proceedings of the ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation, San Diego, 9-11 June 2003.
[15] http://tinyos.stanford.edu/tinyos-wiki/index.php/TinyOS_Documentation_Wiki
[16] MoteWork Crossbow—Platform for the Development of Wireless Sensor Network from Crossbow. www.willow.co.uk/MoteWorks_OEM_Edition.pdf
[17] CC2420 2.4 GHz IEEE 802.15.4 ZigBee-Ready RF Transceiver Chipcon, Product from Texas Instruments.
http://focus.ti.com/docs/prod/folders/print/cc2420.html
[18] Kan, B., Cai, L., Zhao, L. and Xu, Y. (2007) Energy Efficient Design of WSN Based on an Accurate Power Consumption Model. Proceedings of the Wireless Communications, Networking and Mobile Computing (WiCom 2007), Shanghai, 21-25 September 2007, 2751-2754.
[19] Barberis, A., Barboni, L. and Valle, M. (2007) Evaluating Energy Consumption in Wireless Sensor Networks Applications. Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools, Lubeck, 29-31 August 2007, 455-462.
http://dx.doi.org/10.1109/DSD.2007.4341509
[20] Holger, K. and Willig, A. (2005) Protocols and Architectures for Wireless Sensor Networks. John Wiley & Sons, Hoboken.
[21] Bougard, B., Daly, D.C., Chandrakasan, A. and Dehaene, W. (2005) Energy Efficiency of the IEEE 802.15.4 Standard in Dense Wireless Microsensor Networks: Modeling and Improvement Perspectives. Proceedings of the Conference on Design, Automation and Test, 1, 196-201.
[22] Rao, R., Vrudhula, S. and Rakhmatov, D. (2003) Battery Modeling for Energy-Aware System Design. IEEE Computer Society, 36, 77-87.
http://dx.doi.org/10.1145/860176.860179
[23] Rakhmatov, D. and Vrudhula, S. (2003) Energy Management for Battery-Powered Embedded Systems. ACM Transactions on Embedded Computing Systems, 2, 277-324.
http://dx.doi.org/10.1145/860176.860179
[24] Rao, R., Vrudhula, S. and Chang, N. (2005) Battery Optimization vs Energy Optimization: Which to Choose and When? Proceedings of Conference on Computer-Aided Design, ICCAD IEEE/ACM, San Jose, 6-10 November 2005, 439-445.
[25] Panigrahi, D., Chiasserini, C., Dey, S., Rao, R., Raghunathan, A. and Lahiri, K. (2001) Battery Life Estimation of Mobile Embedded Systems. Proceedings of 14th International Conference on VLSI Design (VLSID 01), Bangalore, 3-7 January 2001, 57-63.
[26] Expected Battery Life vs. System Current Usage and Duty Cycle, PowerManagement.xls. Excel Worksheet from Crossbow Technology.
http://www-db.ics.uci.edu/pages/research/quasar/PowerManagement.xls
[27] Kyaw, Z.T. and Sen, C. (2008) Using the CC2430 and TIMAC for Low-Power Wireless Sensor Applications: A Power Consumption Study.
http://focus.ti.com.cn/cn/lit/an/slyt295/slyt295.pdf
[28] Application Note AN053 Measuring Power Consumption with CC2430 and Z-Stack.
http://focus.ti.com/lit/an/swra144/swra144.pdf
[29] Product Datasheet Energizer E91, Alkaline Battery AA. Energizer Holdings, Inc. Form No. EBC-1202M.
http://www.energizer.com/
[30] High-Side Measurement Current Shut Monitor INA 139, Datasheet Burr-Brown Products from Texas Instruments.
http://focus.ti.com/
[31] Coulomb Counter—Battery Gas Gauge LTC4150. Linear Technologies IC Product.
http://www.linear.com/

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