Precision Constraint Data Aggregation for Dynamic Cluster-Based Wireless Sensor Networks

This paper studies the precision-constraint data aggregation problem for dynamic cluster-based wireless sensor networks. The goal is to extend the network lifetime while keeping reasonable data quality. To achieve the target, we propose the dynamical precision allocation algorithm, which splits the application error bound which users can tolerate into individual local error bounds. We differentiate the sensor nodes in clustering architecture to cluster-heads and leaf nodes, arrange the error bounds to the nodes that can really reduce their transmitting messages. In order to reduce the overhead, our algorithm is merged to the cluster-head reelection process. Experimental results show that our scheme significantly improves the network lifetime compared to the existing methods.