Feature Selection and Energy Management for Wireless Sensor Networks
Energy efficiency is a key issue in wireless sensor networks where the energy sources and battery capacity are very limited. In this paper, the authors propose a novel pattern recognition based formulation for minimizing the energy consumption in wireless sensor networks. The proposed scheme involves an algorithm to rank and select the sensors from the most significant to the least, and followed by a na?ve Bayes classification. Assuming that each feature represents a sensor in the wireless sensor network, various data sets with multiple features are considered to show that feature ranking and selection could play a key role for the energy management.