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Sensors 2007, 7(9), 1766-1792; doi:10.3390/s7091766

Time Series Forecasting Energy-efficient Organization of Wireless Sensor Networks

* ,
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing 100084, P. R. China
* Author to whom correspondence should be addressed.
Received: 9 August 2007 / Accepted: 4 September 2007 / Published: 5 September 2007
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Due to their wide potential applications, wireless sensor networks have recentlyreceived tremendous attention. The strict energy constraints of sensor nodes result in thegreat challenges for energy efficiency. This paper investigates the energy efficiency problemand proposes an energy-efficient organization method with time series forecasting. Theorganization of wireless sensor networks is formulated for target tracking. Target model,multi-sensor model and energy model are defined accordingly. For the target trackingapplication, target localization is achieved by collaborative sensing with multi-sensor fusion.The historical localization results are utilized for adaptive target trajectory forecasting.Empirical mode decomposition is implemented to extract the inherent variation modes in thetime series of a target trajectory. Future target position is derived from autoregressivemoving average (ARMA) models, which forecast the decomposition components,respectively. Moreover, the energy-efficient organization method is presented to enhance theenergy efficiency of wireless sensor networks. The sensor nodes implement sensing tasksaccording to the probability awakening in a distributed manner. When the sensor nodestransfer their observations to achieve data fusion, the routing scheme is obtained by antcolony optimization. Thus, both the operation and communication energy consumption canbe minimized. Experimental results verify that the combination of the ARMA model andempirical mode decomposition can estimate the target position efficiently and energy savingis achieved by the proposed organization method in wireless sensor networks.
Keywords: Wireless sensor networks; energy efficiency; time series analysis; ant colony optimization. Wireless sensor networks; energy efficiency; time series analysis; ant colony optimization.
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Wang, X.; Ma, J.-J.; Wang, S.; Bi, D.-W. Time Series Forecasting Energy-efficient Organization of Wireless Sensor Networks. Sensors 2007, 7, 1766-1792.

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