Adaptive data collection strategies for lifetime-constrained wireless sensor networks

Communication is a primary source of energy consumption in wireless sensor networks. Due to resource constraints, the sensor nodes may not have enough energy to report every reading to the base station over a required network lifetime. This paper investigates data collection strategies in lifetime-constrained wireless sensor networks. Our objective is to maximize the accuracy of data collected by the base station over the network lifetime. Instead of sending sensor readings periodically, we propose to consider their relative importance. The key idea is to let the sensor nodes send data updates to the base station when the new readings differ more substantially from the previous ones. We analyze the optimal update strategy and develop adaptive update strategies for both individual and aggregate data collections. We also present two methods to cope with message losses in wireless transmission. Experimental results using real data traces show that, compared with periodic data collection, adaptive data collection significantly improves the accuracy of data collected by the base station.