Wake-up Control for Energy-Efficient Anomaly Detection in Wireless Sensor Networks

In this paper, we focus on anomaly detection in on-demand wireless sensor networks (WSNs), where a wake-up receiver operating with ultra-low power consumption is applied to each sensor node. In order to achieve high accuracy for anomaly detection while reducing power consumption, we need to selectively collect sensing data contributing to the improvement of detection accuracy. To this end, we exploit content-based wake- up (CoWu), where sensor nodes can be selectively woken up based on their observations and the condition set by a data collection node. We propose anomaly region based wake-up (ARWu) that estimates the region of the normal/anomaly data and selectively wakes up nodes that are expected to store anomaly data by employing CoWu. With computer simulations, we show that the proposed wake-up control achieves smaller energy consumption and delay to satisfy a given accuracy of anomaly detection than the conventional wake-up control.