A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks

Power consumption and data redundancy of wireless sensor networks (WSN) are widely considered for a distributed state monitoring network. For reducing the energy consumption and data amount, we propose a topology optimisation and an iterative parameter identification method for estimating the common model factors in WSN. The former method optimises the decentralised topology such that all the leaf nodes in a community connect to the head node directly. A circle topology is built to enable the remote leaf nodes to link to the head node through two adjoining relay nodes to reduce the whole communication distance and power consumption. Based on the optimised topology, an iterative identification method is proposed to minimise the information capacity by transmitting the processed results instead of raw data to reduce the data amount for calculation and storage. Then, we prove the consensus and convergence of the proposed identification method. Finally, two simulations verify the effectiveness of the proposed method and the comparative results present the data reduction for the on-board calculation, communication, and storage in the practical use of WSN.

Automated summary

The paper proposes a topology optimization and iterative parameter identification method to reduce energy consumption and data volume in wireless sensor networks. The consensus and convergence of the identification method are proven, and two simulations demonstrate the effectiveness of the proposed method in practical applications of WSN. The comparative results highlight the importance of data reduction in on-board calculation, communication, and storage.