各向异性无线传感器网络中基于模糊距离贾亚算法的节点定位

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2024-08-16 DOI:10.1109/TNSE.2024.3444589

Shilpi;Arvind Kumar

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引用次数: 0

摘要

无线传感器网络（WSN）的许多应用都依赖于位置信息。每个 WSN 都有锚节点或已知位置节点和目标节点或未知节点。由于多种各向异性因素，解决各向异性 WSN（AWSN）中的节点定位问题更具挑战性。本研究采用软计算方法解决 AWSN 中的节点定位问题。使用模糊逻辑模型估算距离，以避免锚节点接收信号强度指标（RSSI）值的不规则性。马姆达尼模糊推理系统（FIS）采用三角形成员函数来优化锚节点和目标节点之间的距离。Jaya 算法的简单性启发我们用它来寻找 AWSN 中的目标节点位置坐标。通过在带有模糊逻辑工具箱的 MATLAB 软件上进行仿真分析，从定位误差和计算时间两个方面衡量了所提算法的性能。计算了不同节点密度、锚节点和不规则度（$doi$）值下的定位误差。所提出的算法将性能指标与现有的 AWSN 定位算法进行了比较，并提供了更好的位置估计。

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Fuzzy Distance Jaya Algorithm Based Node Localization in Anisotropic Wireless Sensor Networks

Many applications of Wireless Sensor Networks (WSNs) depend on location information. Every WSN has anchor nodes or known location-based nodes and target or unknown nodes. Due to several anisotropic factors, solving the node localization problem in Anisotropic WSNs (AWSNs) is more challenging. This work solves the node localization issue in AWSNs using soft-computing approaches. Distance is estimated using a fuzzy logic model to avoid irregularities in anchor nodes' Received Signal Strength Indicator (RSSI) value. The Mamdani Fuzzy Inference System (FIS) employs a triangular membership function to optimize the distance between the anchor and target nodes. The simplicity of the Jaya algorithm inspires us to use it to find the target node location coordinates in AWSNs. The performance of the proposed algorithm is measured in terms of localization error and computation time through simulation analysis on MATLAB software with the fuzzy logic toolbox. The localization error is calculated for different node densities, anchor nodes, and Degree of Irregularity (

$doi$

) values. The proposed algorithm compares the performance metrics with existing localization algorithms for AWSNs and provides better location estimation.

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.