Statistically Bounding Detection Latency in Low-Duty-Cycled Sensor Networks

Detecting abnormal events represents an important family of applications for wireless sensor networks. To achieve high performance of event detection, a sensor network should stay active most of the time, which is energy inefficient for battery driven sensor networks. This paper studies the fundamental problem of bounding detection delays when the sensor network is low duty cycled. We propose a novel approach for statistically bounding detection latency for event detection in sensor networks. The key issue is the wakeup scheduling of sensor nodes and minimization of wakeup activity. We propose a lightweight distributed algorithm for coordinating the wakeup scheduling of the sensor nodes. A distinctive feature of this algorithm is that it ensures that the detection delay of any event occurring anywhere in the sensing field is statistically bounded. In addition, the algorithm exposes a convenient interface for users to define the requirement on detection latency, thereby tuning the intrinsic tradeoff between energy efficiency and event detection performance. Extensive simulations have been conducted and results demonstrate that this algorithm can successfully meet delay bound and significantly reduce energy consumption.