Analysis of Multiple Data Fusion Techniques for Performance Computation of Wireless Sensor Network

Abstract

Wireless Sensor Networks (WSNs) have become more popular and common in today’s technical era because it is simple to operate, affordable to set up, and convenient to administer.  Any cluster of the multiple sensor nodes which have sensing as well as computation capabilities is to be deployed within the coverage network. The difficulty of such nodes having enough energy arises whenever they are placed in faraway locations. Since the sensing nodes run on batteries, power is indeed a valuable asset that needs to be used wisely. As a result, clustering the network while using datasets fusion methods to communicate information is the greatest effective way to address this problem. Dataset fusion is indeed a technology that allows for the collection of information from multiple sensing nodes to produce a unified picture and decrease redundant dataset that uses a significant amount of power. Designing applications, as well as methods for WSNs, must include handling mistakes and uncertainty in detecting datasets while optimizing network lifespan. In this article, the authors discussed and analysed multiple data fusion techniques for the performance computation of wireless sensor networks. Furthermore, recent trends and major future challenges of data fusion schemes implementation in the WSNs have indeed been explored and discussed for the future research direction in this domain for the researcher.