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Energy-efficient Organization of Wireless Sensor Networks with Adaptive Forecasting
Xue Wang1, Sheng Wang2, Jun-Jie Ma3
1State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instruments, Tsinghua University, Beijing 100084, P. R. China. wangxue@mail.tsinghua.edu.cn.
Sensors (Basel, Switzerland)
|November 24, 2016
Summary
This study introduces an energy-efficient method for wireless sensor networks (WSNs) that improves target tracking. By combining advanced forecasting models and distributed sensing, it significantly reduces energy consumption in WSNs.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Wireless sensor networks (WSNs) face significant energy constraints, challenging their operational efficiency.
- Effective target tracking in WSNs requires robust localization and energy-aware organization.
Purpose of the Study:
- To propose an energy-efficient organization method for wireless sensor networks tailored for target tracking.
- To enhance the energy efficiency and localization accuracy of WSNs.
Main Methods:
- Utilized multi-sensor fusion for collaborative target localization and historical data for trajectory forecasting.
- Combined Autoregressive Moving Average (ARMA) model and Radial Basis Function Networks (RBFNs) for robust target position forecasting.
- Implemented a distributed sensing approach with ant colony optimization for energy-efficient routing.
Main Results:
- Demonstrated efficient target position estimation using the ARMA-RBFN combination.
- Achieved significant energy savings through the proposed distributed organization and routing methods in WSNs.
- Verified enhanced energy efficiency in wireless sensor network operations.
Conclusions:
- The proposed energy-efficient organization method effectively enhances WSN performance for target tracking.
- The integration of ARMA and RBFN models provides accurate and robust target localization.
- This approach offers a viable solution for energy conservation in WSNs while maintaining tracking efficiency.