Iwara Ikpi Arikpo, University of Calabar, Nigeria

Fault detection is essential in the realm of wireless sensor networks, primarily due to the frequent occurrence of node failures, which can disrupt the network's functionality. A significant challenge in this context is the development of a detection algorithm that not only effectively identifies faults but also maintains high energy efficiency to prolong the network's operational life. In this paper, we introduce an innovative fault detection algorithm that leverages the principles of numerical taxonomy. Our approach begins by categorizing all sensor nodes into distinct clusters based on their geographical distribution. This strategic clustering facilitates more efficient monitoring and management of the nodes. Furthermore, the sink node—acting as the main hub of communication—employs numerical taxonomy to analyze the incoming measurements from the various nodes. Through this analysis, the algorithm can accurately detect which nodes are malfunctioning or faulty. The simulation results we present provide compelling evidence that our proposed algorithm outperforms the existing NDHN algorithm while simultaneously consuming less energy. This improvement not only enhances the reliability of fault detection in wireless sensor networks but also contributes to the sustainability of energy resources within the system.

APA:
Arikpo, I. I. (2021). An Innovative and Energy-efficient Fault Detection Algorithm Specifically designed for Wireless Sensor Networks. Journal of Science and Engineering Management, 2(2), 23-34. https://doi.org/10.33832/jsem.2021.2.2.03