Maximizing capacity in wireless sensor networks by optimal placement of clusterheads

A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the limited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads (CHs) and then the clusterheads communicate the aggregated information to the processing center, may save energy. In this paper, we propose a new clustering algorithm in which the placement of clusterheads and cluster membership are such that the total capacity of sensor network is maximized. We also extend the algorithm to investigate the stability of the network with time. Our results show that, for a wide range of system parameters, the optimally placed CHs can significantly increase the network throughput capacity, while the network is stable. Moreover, we study how the number of CHs, transmission power and path loss exponent affect the optimal CH placement and expected throughput capacity of the network.