Data-Aware Clustering Hierarchy For Wireless Sensor Network

In recent years,the wireless sensor network(WSN) is employed awide range of applications.In order to minimize the energy consumption and maximize the life span of the network,clustering techniques based on data fusion have been proposed.But existing communication protocols for WSN ignore the characteristics of collected data and set routes only according to the mutual distance and residual energy of sensors.In this paper we propose a Data-Aware Clustering Hierarchy(DACH),which organizes the sensors based on both distance information and data distribution in the network.Based on DACH,we also present a multi-granularity query processing method based on DACH,which can estimate the query result more efficiently.Furthermore,we proposed a automatic correction method for wireless sensor network with communication error.Our empirical study shows that DACH has higher energy efficiency than Low-Energy Adaptive Clustering Hierarchy(LEACH),and the multi-granularity query processing method based on DACH brings more accurate results than a random access system using same cost of energy.