Method for Distributed Node Metric Measurement in Wireless Sensor Networks Based on Multiple Attributes

Abstract

Traditional sensors require large power inputs and accuracy cannot be guaranteed. In this study, we introduce a revolutionary technique to enhance the accuracy of node measurements in Wi-Fi sensor networks (WSNs) while minimizing power consumption. Our approach focuses on a mixture of key attributes, including overall strength performance, landmark strength, and node geolocation. We have set quantitative measures for these attributes, which is the foundation of our sizing method. The basic framework for evaluating node allocation indicators is superior, mainly based on the multifaceted attributes of individual nodes and adjacent nodes, promoting selection in data transmission and processing. This framework has a powerful statistical collection mechanism that can accumulate every intrinsic attribute, including external attributes such as overall power performance, signal energy, and geographic region. Using these collected records, our techniques include selecting methods for metric calculations. It is worth noting that we have merged a set of adaptive strategies that can dynamically adjust measurement parameters based on discovered community conditions. The adaptability of this strategy ensures normal operational performance in various community states, achieving a balance between measurement accuracy and energy conservation. This method ensures a significant improvement in the operational performance of wireless sensor networks and has broad applicability in the field of reliable high-intensity sensor networks.