Congestion control based on data-aggregation for Wireless Sensor Networks

In-network processing and data-aggregation are key features of Wireless Sensor Networks. In fact, they allow the data to be processed and aggregated as they go through the network. In this work, we propose an innovative congestion control algorithm for wireless sensor networks based on data aggregation, which will be referred to as Data-Aggregation Congestion Control (DACC). The algorithm has been designed by exploiting linear discrete time control theory. It can be applied in a fully distributed way. Using our approach, each node periodically evaluates the amount of data to aggregate in order to control the level of its transmission queue. The aggregation process involves only linear operations and allows the sink node to estimate the confidence level of received data. The effectiveness of DACC has been evaluated with reference to a temperature monitoring problem in a fire detection scenario, using the Castalia simulator. Results have shown that DACC is able to significantly improve the estimation accuracy.