Energy-Efficient Abnormal Nodes Detection and Handlings in Wireless Sensor Networks

This paper focuses on the abnormal nodes detection of poisonous gas in wireless sensor networks, namely, finding these nodes whose concentrations are higher than the threshold. In order to detect abnormal nodes, we had better collect sensory data from all nodes. However, this strategy requires much more energy consumption, so we should try to wake up these nodes near the abnormal filed. Based on this observation, we propose a novel energy-efficient method to wake them up. The main idea is to let abnormal nodes send out control packets to activate their one-hop neighbor nodes; then, neighbor nodes continue detecting, and finally, all abnormal nodes send information to the sink node through the shortest paths. Thereafter, we further propose to handle these information in the sink node, including extracting boundary nodes, drawing isolines, and estimating the location of leakage source. To extract boundary nodes, we divide all abnormal nodes into different intervals in an ascending or descending order, and then find two nodes with minimum and maximum in each interval, so these nodes are regarded as boundary nodes. As to the second point, we reuse the wide-adopted interpolation methods to draw isolines, such as cubic, nearest, and invdist. Besides, we use interpolation to find the coordinate of the peak, and then, it is deemed to be the leakage source. The experimental results show that our proposed method is feasible.