Energy efficient data fusion algorithm base on clustered wireless sensor networks

Abstract

The energy of wireless sensor network is limited and the network is vulnerable to the environment. To improve the energy efficiency and data reliability of wireless sensor networks, an energy efficient data fusion algorithm based on clustered wireless sensor networks (EEDFA) is proposed. EEDFA runs in the clustered network, in which the process of data collection and transmission is divided into several periods. Sensors collect data in time slots of the period and form a data vector whose dimension will be reduced to reduce the transmission load. At the same time, the interval type-2 fuzzy system is used to generate data reliability factors considering environmental interference to ensure the reliability of data. Each cluster head receives and distributed processing the data from their member nodes. After removing redundant data by the similarity function, the fused data is sent to the next hop cluster head or base station. Simulation results verify that EEDFA has lower bandwidth occupancy, lower energy consumption, and higher data accuracy than PFF, REDA, and SCDRE.