Performance analysis of fault detection techniques in internet of things enabled wireless sensor networks

Abstract

In today s world, the Internet of Things (IoT) has progressed in its newlinepervasiveness across the globe for diverse applications. Wireless Sensor newlineNetwork (WSN) is one of the prominent technologies employed in IoT newlineenvironments where multiple tiny sensor nodes are distributed to sense real newlinetime observations about unforeseeable areas for control and managerial newlinepurposes. Owing to the presence of sensors in inaccessible regions and their newlinebattery restrictions, different types of faults occur in IoT-enabled WSNs newline(IWSNs). These faults are hardware, software, and communication link faults. newlineIt creates uncertainty in data reading which causes serious damage to the newlinesensor network. newlineNumerous existing fault detection methodologies burdened the newlineresources of the sensor nodes while computing the fault status in the IWSN newlineenvironment. This kind of burden might create redundant delays and newlineinfluence the appropriateness of the sensed information. Furthermore, the newlineexisting models made use of additional energy in order to diagnose and newlinecategorize the different faults which engendered the premature death of the newlinesensors in the network. If energy efficiency and fault detection are not newlinehandled properly in IWSN, various critical concerns can impact the newlineendurance, security, and performance of the network. These include rapid newlinebattery energy dissipation, shorter network lifetime, and poor decision newlinemaking from inaccurate data. Hence, the IWSN necessitates an effective fault newlinedetection methodology with lesser energy consumption to attain accurate and newlinecontinuous data transmission. newline