International Journal of Communication Systems最新文献

{"title":"Improving the Performance of Wireless Signal Recognition Using Dimensionality Reduction–Based Classifiers for Low SNR Signals","authors":"Neema M.,&nbsp;E. S. Gopi,&nbsp;Manavapati Govardhan Reddy","doi":"10.1002/dac.70029","DOIUrl":"https://doi.org/10.1002/dac.70029","url":null,"abstract":"<div>\u0000 \u0000 <p>Future communication networks face the predicament of scarce spectrum resources in order to accommodate the exponential proliferation of heterogeneous wireless devices. The significance of wireless signal recognition (WSR) is steadily growing, especially concerning spectrum monitoring, spectrum management, and secure communications, among other crucial domains. Numerous techniques for conducting WSR were presented in the literature; however, the majority of them demonstrate limited efficacy in low SNR scenarios. This work proposes a dimensionality reduction (DR)–based machine learning classifier (DR-MLC) that simultaneously performs modulation and signal classification in heterogenous waveform scenarios. Additionally, the model employs a projection technique (PT) for noise removal in input data. The proposed framework is the first of its kind in the wireless signal processing domain and its performance is extensively evaluated in low SNR conditions using DR techniques including principal component analysis (PCA), linear discriminant analysis (LDA), and kernel LDA (KLDA) in combination with various machine learning techniques such as support vector machine (SVM), <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>K</mi>\u0000 </mrow>\u0000 <annotation>$$ K $$</annotation>\u0000 </semantics></math>-nearest neighbor (KNN), and nearest mean (NM) methods. The publicly available RadComDynamic dataset is utilized for the experiment. The paper demonstrates the improvement in classification accuracy of the proposed model over the reference architectures taken, specifically in low SNR scenarios for both single and dual classification tasks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiport MIMO Antenna System With Diverse Radiation Pattern for Sub-6 GHz Wireless Communications","authors":"Gouri Shankar Sharma,&nbsp;Anshul Gupta,&nbsp;Ravi Kumar Gangwar,&nbsp;Amit Kr Pandey","doi":"10.1002/dac.70013","DOIUrl":"https://doi.org/10.1002/dac.70013","url":null,"abstract":"<div>\u0000 \u0000 <p>The design and implementation of a six-port MIMO dielectric resonator (DR) antenna (DRA) featuring diverse radiation patterns for wireless applications has been rendered in this article. The antenna structure is organized as a coplanar waveguide (CPW), fed three cylindrical DRs installed on the upper and lower sides of the substrate to achieve diverse radiation patterns. The proclaimed MIMO antenna exhibits a measured working frequency spectrum from 5.16 to 6.04 GHz (fractional bandwidth = 15.74%) with an isolation exceeding −27 dB at the resonance frequency. The antenna is characterized by its high isolation due to the spatial positioning of DRs at each side on the modified ground plane of the FR-4 substrate and pattern diversity, which allows the antenna to maintain its MIMO performance parameters like envelope correlation coefficient (ECC), diversity gain (DG), total active reflection coefficient (TARC), and channel capacity loss (CCL) necessary for the MIMO antenna system within optimal limits. The closeness between simulated and experimental results makes the proclaimed antenna suitable for sub-6 GHz WLAN (5.15–5.925GHz), 5G (n46), and wireless fidelity (Wi-Fi) supported IoT applications.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Sensing and Communication in Next-Generation Wireless Networks: Insights and Trends","authors":"Shatakshi Singh,&nbsp;Umashankar Samal","doi":"10.1002/dac.70014","DOIUrl":"https://doi.org/10.1002/dac.70014","url":null,"abstract":"<div>\u0000 \u0000 <p>Integrated sensing and communication (ISAC), wherein sensing and communication share the same frequency band and hardware, has emerged as a pivotal technology in future wireless systems. A thorough study is required for researchers because ISAC has attracted a lot of interest and attention from academia and industry. In this paper, we present a bibliometric review that seeks to map the current state of ISAC research by addressing three crucial aspects. The aspects are (1) locating key journals, and significant authors, and creating network maps within ISAC; (2) defining theme-based clusters based on keyword co-occurrence analysis; and (3) developing a strong research framework to direct future ISAC investigations. This study provides profound insights and a structured foundation for researchers, enhancing the understanding and development of ISAC technologies. By highlighting significant advancements and research trends, this review aims to foster further innovation and academic discourse in the field of ISAC.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Data Communication in SIoT: Hybrid Channel Attention Recurrent Transformer-Based Adaptive Marine Predator Algorithm for Reduced Energy Consumption","authors":"Sekar Sellappan,&nbsp;Ravikumar Sethuraman,&nbsp;Surendran Subbaraj,&nbsp;Jeyalakshmi Shunmugiah","doi":"10.1002/dac.70022","DOIUrl":"https://doi.org/10.1002/dac.70022","url":null,"abstract":"<div>\u0000 \u0000 <p>The rapid development of technologies has attracted significant attention, with the social web and big data becoming key drivers of modern innovation. Although big data in the Social Internet of Things presents various energy-saving merits, problems such as network congestion and data communication reliability occur. In this article, a hybrid channel attention recurrent transformer-based adaptive marine predator algorithm is introduced to solve these problems. The main purpose of this approach is to improve the robustness and performance of SIoT systems. The hybrid channel attention recurrent transformer-based adaptive marine predator algorithm combines a hybrid recurrent neural network, a channel attention mechanism, and a transformer classifier. In this work, four datasets, including the water treatment plant, GPS trajectories, hepatitis dataset, and Twitter for sentiment analysis in Arabic are employed in validating the performance of a proposed model. The Savitzky–Golay filter is applied to reduce noise and eliminate unnecessary or irrelevant data. After data pre-processing, the hybrid channel attention recurrent transformer-based adaptive marine predator was introduced for classification, and this model is fine-tuned by the adaptive marine predator algorithm. In addition, the proposed model demonstrates strong scalability and applicability in real-world applications, making it an ideal solution for future Social Internet of Things systems.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized Efficient Predefined Time Adaptive Neural Network for Identifying Parameters in Quantum Bit Error Rate","authors":"D. Ilakkiaselvan,&nbsp;R. J. Kavitha","doi":"10.1002/dac.70009","DOIUrl":"https://doi.org/10.1002/dac.70009","url":null,"abstract":"<div>\u0000 \u0000 <p>An Optimized Efficient Predefined Time Adaptive Neural Network for Identifying Parameters in Quantum Bit Error Rate (EPTANN-IP-QBER) is proposed in this manuscript. Here, the input signals are gathered from 6G wireless networks that face obstacles channel. To execute this, the High-Level Target Navigation Pigeon-Inspired Optimization (HLTNPIO) is used to extend the maximum transmission distances and improve the secret key rates of input signals. Then, improved secret key rates input signals are fed to EPTANN for effectively identifying the parameters such as laser linewidth, channel dispersion, decoy states, error correction rate, privacy amplification efficiency, eavesdropping detection, scalability, and photon encoding optimization in quantum bit error rates (QBERs). Generally, EPTANN does not adapt any optimization approaches to determine optimal parameters to identify the parameters in QBER. Hence, the Snow Avalanches Algorithm (SAA) is employed to optimize the EPTANN, which accurately identifies the parameter in QBER reduction. The proposed EPTANN-IP-QBER is implemented in Python. The performance metrics, like accuracy, precision, secure key rate, QBER, transmission distance, and computational time, are analyzed. The performance of the EPTANN-IP-QBER approach attains 20.25%, 18.36%, and 23.28% lower QBER; 29.56%, 19.42%, and 27.74% higher accuracy; and 16.21%, 20.26%, and 26.96% higher precision when analyzed to the existing methods: Millimeter-Waves to Terahertz SISO along MIMO Continuous-Variable Quantum Key Distribution (TSISO-MIMO-VQKD), MIMO Terahertz QKD utilizing Restricted Eavesdropping (MIMO-QKD-URE), and single-emitter quantum key distribution more than 175 km of fiber by optimized finite key rates (SEQKD-FKR) methods, respectively.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metamaterial-Based AMC Antenna With Reduced RCS and Increased Bandwidth for Wireless X-Band Applications","authors":"Barun Dhabal,&nbsp;Akhilesh Kumar,&nbsp;Arnab Nandi,&nbsp;Banani Basu","doi":"10.1002/dac.70019","DOIUrl":"https://doi.org/10.1002/dac.70019","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;This paper presents a method to enhance antenna bandwidth, reduce radar cross section (RCS), and increase antenna gain by using a metamaterial-based artificial magnetic conductor (AMC) structure for the applications of X-band. In the suggested antenna, we provide a coaxial probe-fed with 50&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;Ω&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ varOmega $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; impedance matching circuit. Furthermore, in the presented work, two AMC unit cells are designed to achieve a 180° reflection phase difference across a wide frequency range, and these unit cells are employed to construct a chessboard-like metamaterial surface (CLMS) for low RCS. The AMC structures provide an adequate bandwidth in the desired frequency by adjusting the phase. A 3 &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;×&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ times $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; 3 periodic AMC structure with a defected ground structure (DGS) configuration is proposed and experimentally demonstrated to enhance antenna bandwidth and gain. The antenna's overall size is significantly reduced to (1.35&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;λ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {lambda}_0 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;×&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ times $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; 1.35&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;λ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {lambda}_0 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) with a thickness of (0.025&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;λ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {lambda}_0 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;); here, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;λ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 ","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143424113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Energy-Efficient Information Aggregation Protocol With Optimized Trilevel K-Means Clustering for IoT-Based WSN Framework: A Case Study on Smart Agriculture","authors":"Vijay Nandal,&nbsp;Sunita Dahiya","doi":"10.1002/dac.70020","DOIUrl":"https://doi.org/10.1002/dac.70020","url":null,"abstract":"<div>\u0000 \u0000 <p>In agriculture production, Internet of Things–based wireless sensor network (IoT-based WSN) technology is used to observe yield conditions and automatic precision agriculture through different sensors. As a part of intelligent farming decisions, sensors are used in the agricultural field to collect information regarding plants, crops, measurements, temperature, humidity, and irrigation systems. IoT-based WSNs are proposed for smart agriculture that have different levels of design. Initially, significant information is captured by agricultural sensors. Then, an optimized trilevel <i>K</i>-means clustering (KMA) is introduced to cluster the agriculture data. The trilevel KMA is effectively used to extract knowledge in the agriculture field. After that, the cluster head is selected using the arithmetic optimization algorithm (AOA) by considering the general factors, including energy, delay, and distance, improving the lifetime of the nodes. This method proposes a new chain-based routing method for optimizing information transmission in IoT-based WSN frameworks. A comparison between the proposed and existing methods is performed to prove their effectiveness. The experimental results show that the proposed protocol outperforms the other existing methods in terms of throughput (96 kbps), packet delivery ratio (37%), network latency (0.028 ms), and average energy consumption (0.52 J).</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nature-Inspired Meta-Heuristic Algorithms for Resource Allocation in the Internet of Things","authors":"Fatemeh Amirghafouri,&nbsp;Ali Akbar Neghabi,&nbsp;Hassan Shakeri,&nbsp;Yasser Elmi Sola","doi":"10.1002/dac.6141","DOIUrl":"https://doi.org/10.1002/dac.6141","url":null,"abstract":"<div>\u0000 \u0000 <p>The Internet of Things (IoT) is a paradigm-shifting concept that helps realize an acquisition, processing, and analytical global network, digitizing tangible entities to enhance efficiency and safety in various smart cities, healthcare, and Industry 4.0 domains. However, whereas IoT scales, with several heterogeneous devices and diverse, varied capabilities with service demands, cloud resource management in IoT usually faces the challenge of intricate complexity in efficiently allocating resources despite the demand for varied quality of service (QoS). Hence, this paper systematically reviews nature-inspired metaheuristic algorithm applications in IoT resource allocation for solving NP-hard problems. We summarize recent advances in metaheuristic methods, including comparisons against traditional methods. We also discuss practical feasibility and scaling issues in real-world IoT scenarios. Further, we have highlighted a few gaps in the current literature and provided recommendations on specific topics for future research, thereby indicating how to develop scalable, efficient resource allocation solutions to meet IoT's ever-evolving demands.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trust-Aware Routing Protocol Using Hierarchical Manta Ray Foraging Optimization Algorithm With Selfish Node Detection in MANET","authors":"Suresh Jeganathan,&nbsp;Gunasekaran Kulandaivelu,&nbsp;Dhurgadevi Muthusamy,&nbsp;Kishore Verma Samraj","doi":"10.1002/dac.70011","DOIUrl":"https://doi.org/10.1002/dac.70011","url":null,"abstract":"<div>\u0000 \u0000 <p>Mobile ad hoc networks (MANETs) are fast, self-organizing, infrastructure-less wireless networks; it is highly suitable for use in emergencies, natural catastrophes, and between places without infrastructure. However, this approach fails to focus on the selfish nodes. To address this, a trust-aware routing protocol using the Hierarchical Manta Ray Foraging Optimization Algorithm (HMRFOA) with selfish node detection in MANET (SND-MSWGCN-TRP-MANET) is proposed in this manuscript. Initially, clustering is processed using Localized Sparse Incomplete Multiview Clustering (LSIMVC). The node is clustered by merging or combining two maximum comparable cluster nodes; then, the clustered node is assigned to the Mud Ring Optimization Algorithm (MROA), where the cluster head is selected using the parameters, such as energy (E), distance (Dist), delay (D), and quality of service (QoS). The selected cluster head is fed to the Multiscale Superpixel-Guided Weighted Graph Convolutional Network (MSWGCN) for effectively detecting the selfish node to ensure secure and efficient data routing in MANET. Finally, trust-aware routing is performed using the HMRFOA, where it selects the optimal path. Then, the proposed SND-MSWGCN-TRP-MANET is implemented, and the performance metrics like energy consumption, time consumption, end-to-end delay, throughput, average delay, packet delivery ratio (PDR), and packet loss ratio (PLR) are examined. The performance of the SND-MSWGCN-TRP-MANET approach attains 14.82%, 21.63%, and 31.57% lower energy consumption and 16.23%, 24.19%, and 31.82% higher throughput when analyzed to the existing techniques, like selfish node trust aware along optimized clustering for dependable routing protocol (SNTA-CRRP-NANET), trust-aware safe energy-efficient hybrid protocol in MANET (TASEP-MANET), and cluster with angular base energy efficient trusted routing protocol in MANET (EPTRP-MANET).</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Efficient Fuzzy Logic With Barnacle Mating Optimization-Based Clustering and Hybrid Optimized Cross-Layer Routing in Wireless Sensor Network","authors":"A. Renaldo Maximus,&nbsp;S. Balaji","doi":"10.1002/dac.6132","DOIUrl":"https://doi.org/10.1002/dac.6132","url":null,"abstract":"<div>\u0000 \u0000 <p>Recent advancements in information technology have led to the widespread adoption of the Internet of Things (IoT) across various applications. Wireless sensor networks (WSNs), consisting of low-cost, compact sensors, are crucial for IoT systems, enabling data collection for tasks like surveillance and tracking. A major challenge in WSNs is achieving energy efficiency while extending network lifetime (NLT), necessitating effective clustering and routing strategies. Numerous existing methodologies for energy-efficient clustering and routing exhibit potential; however, they are hindered by constraints including inadequate adaptability to fluctuating network conditions, suboptimal selection of s cluster heads (CHs), and uneven energy consumption, resulting in diminished network longevity and efficacy. These issues require novel strategies to improve overall performance. To tackle this issues, this research presents a novel hybrid technique combining fuzzy logic with barnacles mating optimization (FL-BMO) to identify the most optimal CHs by evaluating critical criteria like average sink distance, average intracluster distance, residual energy, and CH balance factor. The FL-BMO methodology utilizes fuzzy logic to address uncertainties in sensor data, and the BMO algorithm, modeled after barnacle mating patterns, offers a resilient and adaptable optimization process, markedly enhancing energy efficiency and network longevity. In addition, an innovative natural-inspired hybrid cross-layer sunflower optimization routing (NiHCLR-SFO) technique has been introduced that entails optimal routing path selection. This approach balances exploration and exploitation during a route selection process, integrating multiple layers of the network functionality which eventually results in improved routing efficiency and network throughput. Such a hybrid approach has been implemented in MATLAB. The proposed method is compared with fuzzy reinforcement learning based data gathering (FRLDG), neuro-fuzzy-emperor penguin optimization (NF-EPO), bio-inspired cross-layer routing (BiHCLR), and fuzzy rule-based energy-efficient clustering and immune-inspired routing (FEEC-IIR) protocols. From these comparisons, it was observed that the method propagates definite NLT gains reaching 39.74%, 32.92%, 15.95%, and 4.8076%, respectively. The proposed method outperforms the existing approaches (FRLDG, NF-EPO, FEEC-IIR, and BiHCLR) across several performance parameters: 99% packet delivery ratio (PDR), 2.8 ms of end-to-end delay time (E2ED), 1 Mbps of throughput, 30 mJ of energy consumption, 6000 rounds NLT, 2% bit error rate (BER), 1.25 buffer occupancy ratio, and 0.5% of packet loss ratio (PLR).</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}