Overhearing-Based Efficient Boundary Detection in Dense Mobile Wireless Sensor Networks

In dense mobile wireless sensor networks, it is desirable to gather sensor data with as low traffic as possible. When an application requires geographical boundaries of sensor readings, it is able to satisfy the requirement while reducing traffic by gathering sensor data only from nodes located close to the boundaries. In order to do so, it is necessary to detect nodes located close to the boundaries (boundary detection). Until now, many boundary detection methods have been proposed, assuming networks constructed by fixed nodes. In these methods, each node preliminarily recognizes locations of itself and all its neighboring nodes. When applying this approach to a dense and mobile environment, it takes a large amount of traffic for exchanging information on locations of nodes. In this paper, we propose an efficient boundary detection method in dense mobile wireless sensor networks, which makes use of overhearing sensor data. In our proposed method, each node determines whether it exists close to a boundary or not based on sensor data overheard from its neighboring nodes. When a node determines that it dose not exist close to the boundary, it stops transmitting its own sensor data. By doing so, traffic for boundary detection can be reduced. We confirmed the effectiveness of our proposed method through simulation experiments.