Internet Technology Letters最新文献

{"title":"Free Space Optics Transmission Enabled by PAM-4 Signals: Performance Evaluation Under Indian Weather Conditions","authors":"V. Vaithianathan,&nbsp;P. Raja,&nbsp;Sathya Selvaraj Sinnasamy,&nbsp;R. Gayathri,&nbsp;B. Vasudevan","doi":"10.1002/itl2.70004","DOIUrl":"https://doi.org/10.1002/itl2.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents a performance evaluation of Free Space Optics transmission systems using 4-level pulse amplitude modulation (PAM-4) signals under clear weather conditions and certain specific Indian weather conditions. The conditions at the selected locations, which represent diverse climatic environments, include Chennai, Chandigarh, Jodhpur, and Srinagar. This study provides an assessment of the impact of various conditions in the atmosphere that would affect signal degradation and the quality of transmission based on the bit error rate and eye diagrams of received signals for increasing transmission ranges. The results presented here are the results of the performance analysis of the FSO system with respect to BER as it varies with distance, hence showing the vulnerability of PAM-4 signals due to heavy attenuation by poor weather conditions—mostly fog and rain—under which the selected regions fall. Eye diagrams are also used for signal integrity and quality check and, further on, to gather information on the system under test. This comparative analysis, therefore, brings to light the areas in which the system remains resilient and identifies challenging atmospheric conditions that severely affect transmission. These results provide valuable information on how an FSO system can be optimized under different weather environments, as well as set up strategies through which the reliability and performance of the system can be enhanced for a region with varying atmospheric conditions. The proposed system's performance after performing experimental validation can be used for providing high-speed transmission required for 5G/beyond 5G data transmission networks.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Efficient Reliable Data Transmission Using Optimized Cyclone Foraging Strategy in 5G Wireless Sensor Networks","authors":"Sowmya Madhavan,&nbsp;Satti Sudha Mohan Reddy,&nbsp;T. Kavitha,&nbsp;Afshan kaleem,&nbsp;V. Shilpa","doi":"10.1002/itl2.643","DOIUrl":"https://doi.org/10.1002/itl2.643","url":null,"abstract":"<div>\u0000 \u0000 <p>As a fundamental supporting technology of 5th Generation (5G) systems, wireless sensor networks (WSN) are handling a new challenge to enhance its energy-efficient reliable transmission. However, energy usage and network lifetime are observed as challenging tasks because of limited battery capacity and open environments. The cyclone foraging strategy with beluga whale optimization (CFS-BWO) is proposed for energy-efficient reliable data transmission for 5G WSN. The CFS is applied for improving the exploitation phase of traditional BWO, where population transfers in spiral orientation among the best solutions. CFS-BWO optimizes the routing and data aggregation process, which minimizes the energy usage and enhances the network lifetime. The average delay, residual energy, communication cost, and distance are adopted as fitness functions for optimizing the best solution in both CH and route path selection. The performance was calculated by the metrics of residual energy, packet delivery ratio (PDR), and delay across 200, 400, 600, 800, and 1000 rounds. The CFS-BWO reaches residual energy of 0.87 J, PDR of 0.98, and delay of 15 ms for 1000 rounds when compared to optimal cluster-based routing (Optimal-CBR).</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"4D-BiTK: Beam Shifting Yagi–Uda Antenna Design for Dynamic 6G Applications","authors":"Vijayakumar Rajarathinam,&nbsp;Shakeel Ahmed,&nbsp;Sandeep Prabhu,&nbsp;C. R. Rathish,&nbsp;S. Gobhinath","doi":"10.1002/itl2.70008","DOIUrl":"https://doi.org/10.1002/itl2.70008","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid progress of 6G wireless communication, there is a new need for innovative antenna designs with the same set of demands about high-speed, low-latency, and energy-efficient connectivity. Traditional antennas fail to meet these demands by providing a limited number of prescribed beam-steering directions, having relatively low data rates, and suffering from significant interference. We developed a 4D-BiTK: BeamShift Yagi–Uda antenna to resolve these difficulties, offering a pattern reconfigurable antenna solution with exceptional flexibility using graphene technology at terahertz frequencies. The hybrid graphene-metal structure of the antenna is incorporated, which leads to real-time optimization of the direction of the beam, front-to-back (FEB) ratio, and the resonance frequency. In addition, we include a Bifurcated Temporal Convolutional Network with a Bimodal Kookaburra Optimization algorithm for further enhancing beam steering and pattern reconfigurability. The 4D-BiTK: BeamShift antenna has an 85% radiation efficiency, a 10-dB impedance bandwidth of 89%, a 16-dB FEB ratio, and a peak gain of 12.5 dB. Thus, these values transparently present its capability in terms of suitability for future 6G networks, such precision in beam steering, energy efficiency, and overall signal quality.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Traffic Safety Assessment Model for Mixed Urban Traffic Based on Driving Safety Field and ICVs","authors":"Renjie Wang,&nbsp;Jing Cheng","doi":"10.1002/itl2.653","DOIUrl":"https://doi.org/10.1002/itl2.653","url":null,"abstract":"<div>\u0000 \u0000 <p>To accurately assess the driving risks associated with mixed traffic scenarios in urban areas and align with the direction of Internet of Things (IoT) technologies. An intelligent connectivity traffic safety assessment model for mixed urban traffic based on the ICVs is proposed. First, this paper proposes the traffic safety assessment model based on the driving safety field, the model integrates potential, kinetic, and behavior fields. In the process of establishing the mode, we have incorporated the acceleration parameter to dynamically capture driving risk trends. Subsequently, we define a mixed traffic scenario and calculate the driving risks for road users under different driving states based on this algorithm. The results demonstrate that the model effectively captures the driving risks of road users in different states, and the evaluation outcomes align with real-world situations, thereby validating its effectiveness. The significance of this research lies in providing a theoretical foundation for the application of the Internet of Things (IoT) in complex traffic scenarios and supporting future route planning and driving safety decision-making in intelligent transportation systems. Additionally, this model presents new ideas and methods for the development and application of ICVs technology, contributing to the advancement of intelligent transportation systems.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143533301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Crop Disease Image Recognition Based on Internet of Things Technology and Stacking Integrated Learning","authors":"Fan Tongke","doi":"10.1002/itl2.651","DOIUrl":"https://doi.org/10.1002/itl2.651","url":null,"abstract":"<div>\u0000 \u0000 <p>In the field of agriculture, disease control and management have been a hot research topic of great interest. In recent years, with the reduction of the cost of image sensors and the improvement of the accuracy of deep-learning algorithms, various information processing methods have been widely used in agricultural production. In this paper, an in-depth exploration of crop disease image recognition methods based on IoT technology is carried out. Initially, an innovative method of deploying sensor nodes within an irregular triangular grid is designed to facilitate effective data collection. Subsequently, accurate image segmentation and feature extraction were executed on the accumulated data. A two-tier Stacking framework was used to integrate three lightweight convolutional neural networks. The first level classifier is used to generate data output values for model training; the second level classifier learns further from the output of the first level classifier, corrects the bias of each individual learner in the framework, and produces the final prediction. On the publicly available PlantVillage data set, the EMNet integration model proposed in this thesis has an accuracy of 98.96%, which is at least 0.68% better than other influential DCNN validation accuracies, with good robustness and generalization.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143533302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MADE-TransUNet Induced Brain Tumor Detection for Smart Medicare Using Internet of Medical Things","authors":"Zihui Zhu","doi":"10.1002/itl2.654","DOIUrl":"https://doi.org/10.1002/itl2.654","url":null,"abstract":"<div>\u0000 \u0000 <p>The traditional medical diagnosis using magnetic resonance imaging (MRI) is tedious and seriously depends on doctor's experience. In order to handle this issue, this paper proposes an internet of medical things (IoMT) based intelligent MRI medical diagnosis architecture for brain tumor detection, which adopts cloud computing and deep learning technologies. First, the MRI data is obtained through the scanning using MRI machine and to send to a cloud server in which an intelligent image segmentation model is deployed. Second, the cloud server uses deployed intelligent image segmentation model to implement automatically brain tumor detection and sends the results to clients. The key of proposed medical diagnosis architecture is the intelligent image segmentation model in cloud server. This paper proposes MADE-TransUNet in which bilinear fusion multimodal feature module (BFMF) is applied in the encoder stage for better fusion of multimodal features, adaptive response fusion (ARF) is applied in the bottleneck stage for fusion of features with different resolutions to improve feature expression, and the edge-sensitive enhancement and learning (ESEL) module are applied in the encoder to enhance the edge information. The results of experiments and simulation demonstrate MADE-TransUNet outperforms existing networks for brain tumor segmentation tasks. The code is available at \u0000https://github.com/zhzhuac/MADE.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing the Performance of Free-Space-Optics Transmission System Using Mode-Division-Multiplexing of Hermite–Gaussian and Laguerre–Gaussian Beams","authors":"K. C. Ramya,&nbsp;M. R. Thiyagupriyadharsan,&nbsp;V. Sivasankaran,&nbsp;Leta Tesfaye Jule,&nbsp;A. Sampathkumar","doi":"10.1002/itl2.649","DOIUrl":"https://doi.org/10.1002/itl2.649","url":null,"abstract":"<div>\u0000 \u0000 <p>Emergence of 5G networks has led to rising demand for high-speed data networks. Free-space optics (FSO) play a pivotal role in providing high-speed large-capacity secure communication links required for fronthaul/backhaul services in 5G communication networks. Conventional FSO links are based on wavelength division multiplexing which make the system costlier, bulky and spectral-inefficient. In this work, a mode-division-multiplexing-(MDM)-enabled-FSO transmission system is proposed and evaluated to provide cost-effective, high-speed, and spectral-efficient data transmission. Hybrid Hermite–Gaussian (HG) and Laguerre–Gaussian (LG) modes are integrated to enhance the performance of the system. Four independent 10 Gbps data signals are transmitted along 2-distinct HG beams <span></span><math>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <msub>\u0000 <mi>HG</mi>\u0000 <mn>10</mn>\u0000 </msub>\u0000 <mspace></mspace>\u0000 <mtext>and</mtext>\u0000 <mspace></mspace>\u0000 <msub>\u0000 <mi>HG</mi>\u0000 <mn>11</mn>\u0000 </msub>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow></math> and 2-distinct LG beams <span></span><math>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <msub>\u0000 <mi>LG</mi>\u0000 <mn>00</mn>\u0000 </msub>\u0000 <mspace></mspace>\u0000 <mtext>and</mtext>\u0000 <mspace></mspace>\u0000 <msub>\u0000 <mi>LG</mi>\u0000 <mn>11</mn>\u0000 </msub>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow></math> over the free space channel. The performance evaluated is reported for clear climate and also for adverse rain climate where Quality factor metrics, Bit Error Rate Metrics, and eye diagram representation of the received signals are discussed. The proposed work reports definitive 40 Gbps along 11 km for clear climate followed by 1100–2300 m for varying levels of rain climate.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Driven Network Security Situation Awareness Method in 6G Environment","authors":"Qianlin Tan","doi":"10.1002/itl2.70006","DOIUrl":"https://doi.org/10.1002/itl2.70006","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid advancement of computer technology, the incidence of network security breaches has significantly increased, leading to a corresponding rise in cyber-attacks. Traditional security defense mechanisms exhibit inherent limitations, characterized by their reactive nature and limited efficacy against unknown threats. In addition, these mechanisms often lack coordination among different components, further diminishing their overall effectiveness. In response to these challenges, this paper proposes a deep learning-driven network security situational assessment (DL-driven NSSA) method specifically designed for the 6G environment. Initially, a deep autoencoder (DAE) model is constructed to identify various types of attacks within the network. Subsequently, the model undergoes rigorous testing to calculate attack probabilities, determine impact scores for each attack, and compute the overall network security situational value. Experimental results demonstrate that the proposed DAE model outperforms existing models in terms of accuracy and recall rate, thereby enhancing the precision and reliability of assessment outcomes.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Lightweight Bidirectional Secure Authentication Protocol for Mobile Edge Computing in 6G Networks","authors":"Yuling Bai","doi":"10.1002/itl2.70001","DOIUrl":"https://doi.org/10.1002/itl2.70001","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid development of 6G networks, the era of interconnectivity is fully upon us, accompanied by an explosive increase in the number of mobile smart devices. Solutions centered on cloud computing often fail to meet the real-time computing requirements of mobile smart devices and place significant demands on energy consumption and bandwidth. To address these challenges, edge computing has become a necessity. By deploying mobile edge computing systems close to the sources of information, it is possible to meet the demands for real-time services, data analysis optimization, and intelligent applications on mobile devices. Focusing on the issue of identity secure authentication between mobile devices and mobile edge computing servers in mobile edge computing scenarios, this paper proposes a lightweight bidirectional secure authentication protocol using elliptic curve cryptography (ECC). Constructed with elliptic curve encryption and hash functions, the protocol achieves features such as bidirectional secure authentication, anonymity protection for mobile users, and untraceability of mobile users, while also resisting various threats such as replay attacks and man-in-the-middle attacks. Through performance analysis and comparison with similar protocols, the proposed protocol demonstrates a low overall computational cost, making it particularly suitable for mobile smart devices with limited computing resources. Furthermore, the protocol was implemented using tools such as Visual Studio, and its performance was analyzed to illustrate its practical applicability and reliability.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging Cloud and IoT-Based NLP in Virtual Reality for Sustainable Industry Innovation: A Pathway to Achieving SDG 9 (Industry, Innovation, and Infrastructure)","authors":"Gyana Prakash Bhuyan,&nbsp;Bibhu Kalyan Mishra,&nbsp;Gopinath Palai","doi":"10.1002/itl2.659","DOIUrl":"https://doi.org/10.1002/itl2.659","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper explores the integration of cloud computing, IoT, Natural Language Processing (NLP), and virtual reality (VR) as a pathway to achieving Sustainable Development Goal (SDG) 9, which focuses on fostering industry innovation, building resilient infrastructure, and promoting sustainable industrialization. The convergence of these technologies provides a powerful toolkit for driving the next wave of industrial digital transformation. Cloud platforms such as AWS, Azure, IBM Watson, and Google Cloud offer scalability, flexibility, and efficiency, enabling industries to adopt advanced technologies like NLP and VR without significant upfront capital investment. By leveraging IoT for real-time monitoring and data collection, industries can optimize processes, reduce energy consumption, and enhance predictive maintenance, contributing to sustainability. NLP enables natural and efficient human-machine interaction, automating key processes and improving decision-making. The use of VR allows for immersive simulations that enhance worker training, product design, and infrastructure management, reducing waste and increasing safety. This combination of technologies fosters innovation, inclusivity, and sustainability in industrial operations. The paper highlights practical applications of these technologies, including smart manufacturing, predictive maintenance, and infrastructure monitoring, while emphasizing the role of cloud platforms in democratizing access to advanced tools for industries worldwide. Ultimately, this approach supports the achievement of SDG 9 by enabling more sustainable, resilient, and inclusive industrial practices.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}