Redundancy Optimization Based on Compressive Sensing for Industrial Wireless Sensor Networks

ABSTRACT

A routing algorithm, based on a dual cluster head redundant mechanism combined with compressive sensing data fusion algorithm, is proposed to improve reliability and reduce data redundancy of the industrial wireless sensor networks. The dual cluster head alternation mechanism is adopted to balance the energy consumption of cluster head nodes, and it helps to eliminate redundancy through the compressive sensing data fusion technology, and improve the network throughput of the sensor network effectively. The simulation results show that the proposed algorithm is able to enhance the networks performance, especially in reducing the number of lost packets, and prolonging the network’s lifetime.

Keywords:

Compressed sensing, Data fusion, Double cluster head alternation, Network load balance, Wireless Sensor Networks (WSNs).