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IPML-ANP: An integrated polynomial manifold learning model and anchor node placement for wireless sensor node localization

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2025年第2期18卷 1-15页

作者： Peter, K. John Kumar, S. P. Predeep Padmalal, S. Kingsly, C. Sahaya Dhanalakshmi Srinivasan Coll Engn & Technol Dept Comp Sci & Engn Chennai 603104 Tamilnadu India Mohandas Coll Engn & Technol Dept Comp Sci & Engn Trivandrum Kerala India Mangalam Coll Engn Dept Comp Sci & Engn Kottayam 686631 Kerala India

In Wireless Sensor Network (WSN), the geographical location of the sensor nodes is determined with localization techniques. The conflict between anchor node location, localization accuracy, and coverage must be resolved. In this article, the novel localization approach based on the location selection strategy of static anchor nodes is proposed. It combines the Polynomial manifold learning (PML) model with the anchor node placement approach, which derives the topology map from the distribution map of WSN sensor nodes. An ultra-fast Top-k Closeness Centrality (UF-TKCC) algorithm is introduced to choose the placement of anchor nodes. Each node's proximity centrality value is calculated using UF-TKCC, and the results are sorted to choose the first anchor node. To find the remaining anchor nodes, the centrality of closeness values are traversed at equal intervals. The physical coordinates of the unknown nodes are estimated using the pair-wise geodesic distance. The inherent geometrical feature is maintained using these information coordinates, which are also employed to build the weight matrix. After that, the proposed model will compute the polynomial matrix and the symmetric positive-definite (SPD) matrix using the supplied polynomial parameters. Experimental outcomes show that the IPML-ANP approach is more efficient than the traditional approaches with respect to localization accuracy.

关键词： node deployment Signal strength Topology graph Anchor node selection Ultra-fast top-k closeness centrality node localization Polynomial manifold learning

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Distributed spectral conjugate gradient algorithm for node localization in wireless sensor networks

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DIGITAL SIGNAL PROCESSING 2025年 162卷

作者： Jiang, Junzheng Liu, Xinyi Zhou, Fang Xidian Univ Hangzhou Inst Technol Hangzhou 311231 Peoples R China Xidian Univ Sch Elect Engn Xian 710071 Peoples R China Guilin Univ Elect Technol Sch Informat & Commun Guilin 541004 Peoples R China China Jiliang Univ Sch Informat Engn Hangzhou 310018 Peoples R China

node localization is a key problem in wireless sensor networks (WSNs). Most existing centralized algorithms require processing data from the entire graph at each operation, leading to high computational load and making scalability difficult as the graph size increases. In this paper, a novel distributed spectral conjugate gradient (DSCG) algorithm is proposed to solve the original optimization problem directly, in which the gradient vector and step-size are approximately calculated via a distributed manner in each iteration. The approximation calculation is based on decomposition of graph capturing the WSNs structure. The proposed algorithm can improve scalability while maintaining good localization accuracy. Experimental results verify the effectiveness of the proposed algorithm.

关键词： Wireless sensor networks node localization Distributed spectral conjugate gradient Non-convex optimization Scalability

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EMGODV-Hop: an efficient range-free-based WSN node localization using an enhanced mountain gazelle optimizer

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JOURNAL OF SUPERCOMPUTING 2025年第1期81卷 1-46页

作者： Mostafa, Reham R. Hashim, Fatma A. Khedr, Ahmed M. AL Aghbari, Zaher Afyouni, Imad Kamel, Ibrahim Ahmed, Naveed Univ Sharjah Res Inst Sci & Engn RISE Ctr Data Analyt & Cybersecur CDAC Big Data Min & Multimedia Res Grp Sharjah 27272 U Arab Emirates Mansoura Univ Fac Comp & Informat Sci Dept Informat Syst Mansoura 35516 Egypt Helwan Univ Fac Engn Helwan Egypt Jadara Univ Res Ctr Irbid Jordan Univ Sharjah Dept Comp Sci Sharjah 27272 U Arab Emirates Univ Sharjah Dept Comp Engn Sharjah 27272 U Arab Emirates

Accurate node localization is essential in wireless sensor networks (WSNs) for effective data analysis and the successful operation of applications like environmental monitoring and disaster management. Range-free methods like the distance vector-hop (DV-hop) algorithm are often used due to hardware and cost constraints, but they face challenges in accuracy and stability. The NP-hard nature of the localization problem has led to the integration of metaheuristic algorithms in previous studies to enhance performance. This paper presents EMGODV-Hop, a novel approach for node localization in multi-hop networks that combines the DV-Hop algorithm with the mountain gazelle optimization (MGO) algorithm to enhance localization precision. The EMGODV-Hop method operates in two phases: First, it uses an improved variant of the DV-Hop algorithm to more accurately estimate distances between unknown and anchor nodes by incorporating a correction factor. Next, it employs an enhanced version of MGO algorithm, referred to as EMGO, to determine the positions of WSN nodes. The improved DV-Hop version enhances accuracy by incorporating a correction factor for better estimation of hop distances, while the EMGO algorithm addresses the limitations of the original MGO algorithm and improves its search capabilities. Extensive simulations assessed the effectiveness of the proposed method across various factors, including anchor node ratios, total node count, and communication ranges. The results demonstrate significant accuracy improvements with the proposed algorithm, showing enhancements of 48.69%, 26.22%, 19.33%, 28.21%, and 40.47% compared to DV-Hop, MGODV-Hop, PSODV-Hop, WSODV-Hop, and SSADV-Hop, respectively.

关键词： Wireless sensor networks (WSNs) node localization Metaheuristics DV-Hop algorithm Mountain gazelle optimizer (MGO)

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node localization Based on Unsupervised Approach and Secure Routing for Healthcare Management in Delay-Tolerant Network

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2025年第5期38卷

作者： Ragesh, G. K. Kumar, Ajay Indian Inst Informat Technol Dept CSE Cyber Secur Kottayam Kerala India Adi Shankara Inst Engn & Technol Dept ECE Kalady Kerala India

The ability of the current global healthcare system to continue providing high-quality medical care has been questioned. By using delay-tolerant networks (DTNs) in healthcare management, people that spend a lot of time treating illnesses are exposed to more people while also putting their lives in danger. Unsupervised approach-based node localization and secure routing in DTNs are developed in the proposed method. The proposed adaptive density-based localization algorithm is constructed in two modules. The entire network is clustered depending on density utilizing density-based spatial clustering of applications with noise (DBSCAN). An RSA-based location estimation algorithm is employed to identify the unlocalized node within each cluster. After finding the location of each node, routing mechanism is carried out. An adaptive spray and wait routing strategy is utilized in the proposed method. When a node only has one copy of a message, the spray and wait, routing mechanism moves the relay node while it waits for the destination to be countered. Then modified DNA encryption algorithm is applied for secure data transmission. It is used for encrypting the information before storing it in the network. The trusted center will generate the private key needed for encrypting the data based on the sensitivity level of the information. This proposed algorithm is tested with several metrics which attain better performance, like 94% localization accuracy, 6% localization error, average residual energy of 93%, 5.7 Mbps throughput, 18% encryption time, and 14% decryption time. Thus, the techniques used in the proposed approach are the best choice for node localization, energy efficiency, and secure data transmission in DTN.

关键词： adaptive spray and wait (ASW) delay-tolerant network (DTN) DNA node localization reptile search algorithm (RSA)

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A Two-Stage Approach for Secure node localization and Optimal Route Selection for Enhanced Performance in Wireless Sensor Networks

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2025年第5期34卷

作者： Kumar, T. P. Mohan Ramesh, D. Sri Siddhartha Acad Higher Educ Dept Master Comp Applicat Tumakuru Karnataka India

In Wireless Sensor Network (WSN), node localization is a crucial need for precise data gathering and effective communication. However, high energy requirements, long inter-node distances and unpredictable limitations create problems for traditional localization techniques. This study proposes an innovative two-stage approach to improve localization accuracy and maximize route selection in WSNs. In the first stage, the Self-Adaptive Binary Waterwheel Plant Optimization (SA-BWP) algorithm is used to evaluate a node's trustworthiness to achieve accurate localization. In the second stage, the Gazelle-Enhanced Binary Waterwheel Plant Optimization (G-BWP) method is employed to determine the most effective data transfer path between sensor nodes and the sink. To create effective routes, the G-BWP algorithm takes into account variables like energy consumption, shortest distance, delay and trust. The goal of the proposed approach is to optimize WSN performance through precise localization and effective routing. MATLAB is used for both implementation and evaluation of the model, which shows improved performance over current methods in terms of throughput, delivery ratio, network lifetime, energy efficiency, delay reduction and localization accuracy in terms of various number of nodes and rounds. The proposed model achieves highest delivery ratio of 0.97, less delay of 5.39, less energy of 23.3 across various nodes and rounds.

关键词： WSN energy consumption BWP path optimization node localization routing security delivery ratio energy lifetime

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A Robust Approach for Energy-Aware node localization in Wireless Sensor Network Using Fitness-Based Hybrid Heuristic Algorithms

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2025年第2期38卷

作者： Racharla, Sathya Prakash Jeyaraj, Kalaivani SRM Inst Sci & Technol Coll Engn & Technol Dept Comp Technol Chennai Tamil Nadu India

In wireless sensor network (WSN) applications, the Received Signal Strength Indicator (RSSI) value from the original signal is determined for computing the distance between the unidentified and beacon nodes in the WSN. However, several factors including noise, diffraction, scattering, and some obstructions affect the precision of the localization techniques. This paper aims to implement a smart node localization scheme in WSNs by estimating the shortest distance between beacon nodes and unknown nodes using the RSSI factor. Initially, the beacon node is positioned at a known position, and the exact location of the unknown node is computed by the hybrid optimization concept. The objective of the proposed node localization method is to reduce the average localization error, and it is derived for assigning the unknown nodes to each beacon nodes. Optimization plays a vital role in providing clear communication among sensor nodes without any hindrance. The hybridized algorithm named as Fitness-aware Hybrid One-to-One with Archery Optimizer (FHOOAO) is used for the positioning of the unknown nodes to each beacon node. After assigning unknown nodes, their best positions are identified by considering the maximum number of hops. Finally, the experimentation is done in three different forms of node positioning in WSN such as S-shape, H-shape, and. C-shape. The simulation experiments demonstrate superior outcomes of the proposed model compared to alternative methods, and it also enhances communication efficiency among sensor nodes.

关键词： beacon nodes Fitness-aware Hybrid One-to-One with Archery Optimizer node localization Received Signal Strength Indicator unknown nodes wireless sensor network

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An efficient hybrid bat sand cat swarm optimization-based node localization for data quality improvement in wireless sensor networks

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2025年第2期38卷

作者： Soundari, Dasappagounden Pudur Velusamy Chenniappan, Poongodi Sri Krishna Coll Engn & Technol Dept Elect & Commun Engn Coimbatore 641008 Tamil Nadu India Bannari Amman Inst Technol Dept Elect & Commun Engn Sathyamangalam Tamil Nadu India

node localization in wireless sensor networks (WSNs) ensures that the collected data is contextually accurate, enabling effective monitoring and management of various applications. Recently, there has been a surge in research focused on addressing node localization within WSNs. Emerging trends in this field involve the application of metaheuristic optimization techniques to refine node location determination accuracy. However, existing techniques often struggle with balancing accuracy, energy consumption, network lifetime, and computational efficiency, particularly in challenging WSN environments. Therefore, this research introduces a novel approach called efficient hybrid bat sand cat swarm optimization (EHBSCSO) to address node localization within WSNs. The hybrid method leverages the exploration capabilities of the bat optimization algorithm and the exploitation strengths of the sand cat swarm optimization algorithm. This combination allows for efficient determination of node positions, significantly improving localization accuracy while minimizing energy consumption. The EHBSCSO utilizes the received signal strength indicator (RSSI) and time of flight (ToF) approaches to assess distances among nodes accurately. Accurate node localization directly improves data quality by ensuring spatially precise data collection, reducing communication overhead, and enhancing the overall reliability of the collected data. Compared to conventional methods, the proposed EHBSCSO algorithm demonstrates superior performance, with a mean localization error of 0.18%, energy consumption of 7.2 J, computational time of 8.9 s, and localization time of 0.19 s. These metrics underscore its efficiency and precision. The research indicates that EHBSCSO not only optimizes localization accuracy but also contributes to energy efficiency and faster computational times, addressing key challenges in WSN node localization. image

关键词： bat optimization node localization sand cat swarm optimization time of flight wireless sensor networks

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node localization Algorithm for Irregular Regions Based on Particle Swarm Optimization Algorithm and Reliable Anchor node Pairs

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IEEE ACCESS 2024年 12卷 37470-37482页

作者： Li, Nana Liu, Lei Zou, Dongyao Liu, Xing Zhengzhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou 450000 Peoples R China

In wireless sensor networks (WSN), node localization is a key function, and only by knowing the coordinate positions of the nodes can correct decisions be made. In certain applications, such as smart cities, environmental monitoring, or industrial automation, irregular areas can be complex and affected by environmental complexity and inhomogeneity. Coverage gaps may exist between the nodes to be located and the anchor nodes, and communication paths between the nodes may deviate significantly from the ideal straight line, resulting in a large error between the final positioning result of the algorithm and the actual position. In order to solve this problem, this paper proposes a non-ranging node localization method (RANP-PSO) for irregular regions based on PSO algorithm and anchor node pair selection. The way firstly selects anchor node pairs with higher reliability parameters for the nodes to be located by introducing the hop count constraint mechanism for distance estimation;then uses the regularized least squares method for further constraints on the estimated distances;Finally, the PSO algorithm is utilized to optimize the coordinates of the target node, so as to solve to obtain the position of the node. When the proportion of anchor nodes is 20%, the communication radius of nodes is 30m, and the distribution density of nodes is 0.008, the proposed algorithm reduces the root mean square error by approximately 11.94% compared to AEML and LRAQS algorithms, 7.26% compared to the BDMCL algorithm, and 0.69% compared to the MSVR-DV-Hop algorithm. This demonstrates the advantage of the proposed algorithm in terms of localisation accuracy.

关键词： Non-ranging irregular regions particle optimization algorithm node localization

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node localization through physical layer network coding: Bootstrap, security, and accuracy

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AD HOC NETWORKS 2012年第7期10卷 1267-1277页

作者： Li, Zhiwei Wang, Weichao UNC Charlotte Dept SIS Charlotte NC 28223 USA

Previous research on physical layer network coding (PNC) focuses on the improvements in bandwidth usage efficiency. Its capability to assist wireless nodes in localization was first discussed in [1]. In that paper, however, the authors discussed only the basic idea to detect and separate the interfered signals for calculating the node positions. Many important issues to turn the idea into a practical approach are not extensively studied. In this paper, we plan to investigate these problems. Specifically, our research focuses on the bootstrap procedures, security, and localization accuracy of the PNC based mechanism. We first study the required node density to bootstrap the localization procedure in both infrastructure-based and self-organized networks. With this question answered, researchers can recognize the network scenarios to which PNC based localization can be applied. We design mechanisms to protect integrity of the exchanged information and defend against node impersonation attacks so that the localization procedures will be robust against malicious activities. For localization accuracy, we study the negative impacts of the position errors of the anchor nodes. We design two mechanisms to reduce the localization inaccuracy for both individual nodes and cumulative procedures through excluding the anchor nodes with positioning errors and introducing multiple bootstrap areas. Both simulation and theoretical analysis are used to support our investigation. This research shows that PNC based node localization can satisfy the security and accuracy requirements of different types of wireless networks and it can be widely deployed. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Physical layer network coding node localization Wireless networks

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node localization algorithm for wireless sensor networks based on static anchor node location selection strategy

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COMPUTER COMMUNICATIONS 2022年 192卷 289-298页

作者： Liu, Wenyan Luo, Xiangyang Wei, Guo Liu, Huaixing Zhengzhou Inst Informat Sci & Technol Zhengzhou 450001 Peoples R China State Key Lab Math Engn & Adv Comp Zhengzhou 450001 Peoples R China Henan Prov Key Lab Cyberspace Situat Awareness Zhengzhou 450001 Peoples R China

To better solve the contradiction between the localization accuracy, localization coverage, and the location of anchor nodes in wireless sensor networks, a node localization algorithm for wireless sensor networks based on static anchor node location selection strategy is proposed in this paper. Firstly, collect the signal strength between wireless sensor network nodes, judge whether there is a connection between nodes according to the set signal strength threshold, and convert the node distribution diagram into the node connection relationship diagram, that is, the topology diagram. Then, the closeness centrality value of each node is calculated by using the closeness centrality algorithm, and the obtained closeness centrality values are sorted in descending order, the node with the largest closeness centrality value is the first anchor node, the closeness centrality values are traversed at equal intervals, and the optimal equal interval is selected by using the quick sort algorithm, and the selected nodes are used as the other anchor nodes. Finally, other unknown nodes in the network are located according to the location of anchor nodes. Simulation results show that the proposed algorithm is superior to the existing typical algorithms in localization accuracy and localization coverage.

关键词： Anchor node Closeness centrality Quick sort node localization Wireless sensor networks

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