The Open Automation and Control Systems Journal

2015, 7 : 1936-1942
Published online 2015 October 20. DOI: 10.2174/1874444301507011936
Publisher ID: TOAUTOCJ-7-1936

Redundancy Optimization Based on Compressive Sensing for Industrial Wireless Sensor Networks

Ju Yun , Chen Quanhe and Mazin Yousif
School of Control and Computer Engineering, North China Electric Power University, 102206, China.

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).