Research Area:  Software Defined Networks

Abstract:

In recent years, Industrial Wireless Sensor Network (IWSN) is gaining more popularity due to many applications in industries like fire detection, hazardous gas leakage detection, temperature monitoring, localization of sensors, etc. However, faulty sensors in the network may degrade the performance of the applications. In this paper, a software defined network (SDN) based fault detection method is proposed for IWSN. In this method, SDN plays an important role for controlling the whole system by setting a fault detection algorithm at the cluster heads (CHs). The CH periodically receives the monitoring data from the sensors and follows the fault detection algorithm set by the SDN to detect the faulty sensors in the network. The fault detection algorithm uses a statistical trimean method to detect the faulty sensors. Simulation results show that our proposed method performs better than Ji-s fault detection method in terms of detection accuracy (DA) and false alarm rate (FAR). A IWSN prototype is also designed to evaluate the performance of the proposed method.

Keywords:  
Software Defined Network
Fault Detection
Industrial Wireless Sensor Networks
cluster heads
detection accuracy

Author(s) Name:  Sourav Kumar Bhoi; Mohammad S. Obaidat; Deepak Puthal; Munesh Singh; Kuei-Fang Hsiao

Publisher name:  IEEE

DOI:  10.1109/GLOCOM.2018.8647321

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/8647321