Energy-Efficient Clustering Using Correlation and Random Update Based on Data Change Rate for Wireless Sensor Networks

 Energy-Efficient Clustering Using Correlation and Random Update Based on Data Change Rate for Wireless Sensor Networks

 An energy-efficient clustering method using random update (EECRU) for wireless sensor networks. We divide the network into preliminary clusters depending on the temporal and spatial correlation of sensor data. These clusters are then updated by applying a dynamic update policy and a cluster head rotation scheme, where the change of sensor data and the energy residue of sensors are taken into consideration to achieve high energy efficiency and balance.