Energy-Efficient Cluster-based Distributed Estimation in Wireless Sensor Networks
In this paper, we consider the cluster-based distributed estimation in wireless sensor networks where energy is a constrained resource. First, we present a hybrid cluster-based estimator and show its potential to save energy while keep the estimation performance. Next the optimal tradeoff between the cluster size and the number of clusters is analyzed for a special network ring network. Then, we propose two greedy algorithms to cluster the general sensor networks to minimize the total energy cost of cluster-based estimation scheme by modelling the network as a directed or undirected graph. Simulation results not only show that the energy cost is reduced by cluster-based estimation scheme compared with the parallel estimation scheme while keeping the estimation performance, but also show that more energy is saved by our proposed clustering methods compared with the k-mean clustering method