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2022 International Conference on Smart Applications, Communications and networking, SmartNets 2022

作者： Alnajjar, Satea Hikmat Abrahem, Walaa Khalil Al-iraqia University Department of Network Engineering Baghdad Iraq Al-iraqia University Department of Computer Engineering Baquba Iraq

ISBN: (纸本)9781665487580

Li-Fi (light-fidelity) considers a new technology in the wireless communication domain that operates light for transmission free space;the end-user has employed Visible Light Communication based on Light Emitting Diodes. This study aims to investigate the performance of Li-Fi to transmit data like video and pictures using different data rates under atmospheric turbulence such as rain and dust that affect FSO, therefore it affects at end-user and verifies the reliability of the Visible Light Communication (VLC) system sending data at high-speed data transmission. The systems are simulated by Optisystem V 18;the proposed system is built as a VLC system linked with fiber optic and free space optic channels to transmit various video sizes and an image using data rates of about 100 Mbps and 600 Mbps, and 1 Gbps over a lengthy distance under different weather, System was estimated in phrases of bit error rate, quality factor, power of signal, signal to noise ratio, and variation in angles. Despite the harsh environmental conditions imposed on the communication network, VLC has proven its ability to transmit high-speed data transmission for user's requirement. © 2022 IEEE.

关键词： Visible light communication

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Fuzzy Logic-based Enhanced Edge Server Selection for Hierarchical Federated Learning

Fuzzy Logic-based Enhanced Edge Server Selection for Hierarc...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Du, Zhaoyang Wu, Celimuge Lin, Yangfei Zhong, Lei Djahel, Soufiene Chong, Peter Han Joo The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan Toyota Motor Corporation Tokyo Japan Coventry University Centre for Future Transport and Cities Coventry United Kingdom Auckland University of Technology School of Engineering Computer and Mathematical Sciences New Zealand

ISBN: (纸本)9798350351255

In the rapidly evolving landscape of federated learning (FL), hierarchical architectures are pivotal for improving computational efficiency and safeguarding data privacy. A key challenge in this research area is the optimal selection of edge servers, crucial for executing distributed learning tasks across multiple clients and servers efficiently. Traditional selection methods falter due to their inability to dynamically handle the uncertainties in network conditions and server capabilities. To addressing this weakness, we propose a fuzzy logic-based approach that optimizes edge server selection in a novel smart way, thus enhancing resource allocation by efficiently handling the unpredictable nature of network environments and servers performance. This method is integrated with a previously developed scheme for selecting an optimal subset of clients, thereby establishing a comprehensive framework that significantly boosts the performance and reliability of FL networks. The performance of our approach is validated through real-world experiments and the results demonstrate its superiority over existing methods in terms of accuracy and processing time. © 2024 IEEE.

关键词： Client Selection Edge Computing Federated Learning Fuzzy Logic IoT

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Blockchain-Based Smart Contracts for Supply Chain Management: A Strategic Analysis 3

Blockchain-Based Smart Contracts for Supply Chain Management...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Santosh, Kathari Dash, Chinmaya Aarif, Mohd Kumar, Yadavalli Suresh Verma, Mrinal Kiranbala, B. Cmr Institute of Technology Department of Mba Bengaluru India St. Claret College Department of Computer Science Bangalore India Global Research Network Noida India Aditya College of Engineering Department of Computer Science & Engineering Andhra Pradesh India Soil School of Business Design Manesar Gurgaon India K.Ramakrishnan College of Engineering Department of Ai and Ds Trichy India

ISBN: (纸本)9798350361186

The supply chain management sector strategic examination of the blockchain relies smart contract technology employs a comprehensive approach, drawing insights from reputable secondary sources to explore performance metrics, transactional flow optimization, consensus mechanisms, and security considerations. The study reveals nuanced performance variations in average throughput and transaction duration, emphasizing the scalability and stability of the blockchain network. The depicted transactional flow showcases enhanced communication and transparency, aligning with strategic goals for supply chain optimization. The introduction of a Proof of Authority (PoA) consensus algorithm underscores the importance of efficient consensus mechanisms for resilience against attacks. By integrating PoA, the proposed blockchain-based smart contracts contribute to a strategic and reliable supply chain management system, enhancing transparency and mitigating potential risks. A robust security analysis demonstrates moderate fault tolerance, high defense mechanisms, and effective security recovery capabilities, aligning with the overarching goals of confidentiality, integrity, and availability of critical supply chain data. Ethereum's Proof of Stake (PoS) mechanism is referenced as an exemplar for improving scalability and security. The comparative analysis highlights the proposed CMBC (Consensus Mechanism with Blockchain) as a standout solution, offering middle-ground high attack diversity, fault tolerance, recovery, and a high attack cost, robust security. CMBC outperforms alternatives, demonstrating superiority in enhancing security and resilience against potential adversarial threats. The proposed CMBC demonstrates notable strengths across key performance indices when compared to Fortified-Chain and SaYoPillow. The proposed method is implemented using python software. The effective standard deviation values, ranging from 9.58 to 25.13, further underscore the system's stability and re

关键词： Smart contract

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A Multi-Task Learning Framework for Joint Sub-Nyquist Wideband Spectrum Sensing and Modulation Recognition

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China Communications 2025年第1期22卷 128-138页

作者： Dong Xin Stefanos Bakirtzis Zhang Jiliang Zhang Jie Department of Electronic and Electrical Engineering University of SheffieldSheffield S102TNUnited Kingdom Department of Computer Science and Technology University of CambridgeCambridge CB21TNUnited Kingdom College of Information Science and Engineering Northeastern UniversityShenyang 110819China Ranplan Wireless Network Design Ltd. Cambridge CB233UYUnited Kingdom

The utilization of millimeter-wave frequencies and cognitive radio(CR)are promising ways to increase the spectral efficiency of wireless communication ***,conventional CR spectrum sensing techniques entail sampling the received signal at a Nyquist rate,and they are not viable for wideband signals due to their high *** paper expounds on how sub-Nyquist sampling in conjunction with deep learning can be leveraged to remove this *** this end,we propose a multi-task learning(MTL)framework using convolutional neural networks for the joint inference of the underlying narrowband signal number,their modulation scheme,and their location in a wideband *** demonstrate the effectiveness of the proposed framework for real-world millimeter-wave wideband signals collected by physical devices,exhibiting a 91.7% accuracy in the joint inference task when considering up to two narrowband signals over a wideband ***,the proposed data-driven approach enables on-the-fly wideband spectrum sensing,combining accuracy,and computational efficiency,which are indispensable for CR and opportunistic networking.

关键词： automated modulation classification cognitive radio convolutional neural networks deep learning spectrum sensing sub-Nyquist sampling

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Mobility-aware Seamless Service Migration and Resource Allocation in Multi-edge IoV Systems

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IEEE Transactions on Mobile Computing 2025年第07期24卷 6315-6332页

作者： Chen, Zheyi Huang, Sijin Min, Geyong Ning, Zhaolong Li, Jie Zhang, Yan Fuzhou University College of Computer and Data Science Fuzhou350116 China Ministry of Education Engineering Research Center of Big Data Intelligence Fuzhou350002 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China University of Exeter Department of Computer Science Faculty of Environment Science and Economy ExeterEX4 4QF United Kingdom Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China University of Oslo Department of Informatics Oslo0316 Norway

Mobile Edge Computing (MEC) offers low-latency and high-bandwidth support for Internet-of-Vehicles (IoV) applications. However, due to high vehicle mobility and finite communication coverage of base stations, it is hard to maintain uninterrupted and high-quality services without proper service migration among MEC servers. Existing solutions commonly rely on prior knowledge and rarely consider efficient resource allocation during the service migration process, making it hard to reach optimal performance in dynamic IoV environments. To address these important challenges, we propose SR-CL, a novel mobility-aware seamless Service migration and Resource allocation framework via Convex-optimization-enabled deep reinforcement Learning in multi-edge IoV systems. First, we decouple the Mixed Integer Nonlinear Programming (MINLP) problem of service migration and resource allocation into two sub-problems. Next, we design a new actor-critic-based asynchronous-update deep reinforcement learning method to handle service migration, where the delayed-update actor makes migration decisions and the one-step-update critic evaluates the decisions to guide the policy update. Notably, we theoretically derive the optimal resource allocation with convex optimization for each MEC server, thereby further improving system performance. Using the real-world datasets of vehicle trajectories and testbed, extensive experiments are conducted to verify the effectiveness of the proposed SR-CL. Compared to benchmark methods, the SR-CL achieves superior convergence and delay performance under various scenarios. © 2025 IEEE.

关键词： Convex optimization

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On Construction of Precise Positioning System via IEEE 802.11ax

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IEEE Internet of Things Journal 2023年第14期10卷 12951-12960页

作者： Tsung, Chen-Kun Yang, Chao-Tung Liu, Jung-Chun Hsiung, Chun Chang, Shih-Kuang Hsu, Ming-Shang National Chin-Yi University of Technology Department of Computer Science and Information Engineering Taichung41170 Taiwan Tunghai University Department of Computer Science and Research Center for Smart Sustainable Circular Economy Taichung407224 Taiwan Tunghai University Department of Computer Science Taichung40704 Taiwan Krystal Technology Company Ltd. Network Department Taichung42756 Taiwan

Wireless network stability is critical for organizations. Most companies rely on a solid Internet connection for at least part of their day-to-day activities. It is essential to show the fast and high capacity of Wi-Fi. Wireless network management also significantly supplies the user with quality service and helps the system administrator manage and track the network infrastructure. The user must be able to stay connected. The Wi-Fi connection engine was applied in this article using the analysis and locations engine (ALE). ALE provides the information, including MAC address, location, floor information, and the building where the device belongs. From this data, we presented the Web visualization of the Wi-Fi network monitoring system on the map using Cesium. Except for the common information about Wi-Fi users, this work presents the vertical position visualization in the buildings to provide more details about user usage. This work analyzes the user experience of using the proposed system, and latency is the appropriate metric to measure the user experience. The experiment results show that the optimized number of cluster partitions is four, and the latency is less than 1.3 s for 4-MB data. Therefore, the system provides a visualization platform with acceptable system response, and Internet managers would consider the proposed system as the management tool. © 2014 IEEE.

关键词： Engines

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An Effective Analysis of Predicting Clothes types in E-commerce reviews using CatBoost Algorithm with Extreme Gradient Boosting Classifier 2

An Effective Analysis of Predicting Clothes types in E-comme...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Sai Varshith, Pabbisetty Venkata Parthipan, V. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Big Data and Network Security Tamil Nadu Chennai India

ISBN: (纸本)9798350364699

The purpose of this study is to determine whether the Catboost algorithm is superior to the Extreme Gradient Boosting Classifier (XGBoost) method in terms of its ability to generate predictions about the sorts of clothing based on evaluations from online retailers. This study contains 2 groups: Novel Catboost algorithm and Extreme Gradient Boosting Classifier, where each group is iterated for a sample size of 10 calculated using the ClinCalc software with 0.05 as the alpha value, and a CI of 95%. The e-commerce reviews dataset with a size of 23485 was considered from ***. The novel catboost algorithm accuracy is 92%, which appears to be superior to the XGBoost classifier's accuracy of 89%. It can be concluded that there exists a statistically significant distinction between the CatBoost algorithm and the XGBoost classifier algorithm. This is evidenced by a value of p=0.007 (Independent sample t-test p © 2024 IEEE.

关键词： Marketplaces

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SECURITY SYSTEMS IN GREEK HEALTH CARE INSTITUTIONS: A SCOPING REVIEW TOWARDS AN EFFECTIVE BENCHMARKING APPROACH 22

SECURITY SYSTEMS IN GREEK HEALTH CARE INSTITUTIONS: A SCOPIN...

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22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Mariettou, Savina Koutsojannis, Constantinos Triantafyllou, Vassilis University of Peloponnese Electrical and Computer Engineering Department Patras Greece Health Physics & Computational Intelligence Laboratory Physiotherapy Department School of Health Rehabilitation Sciences University of Patras Patras Greece Network Technologies and Digital Transformation lab Electrical and Computer Engineering Dpt. University of Peloponnese Patras Greece

Healthcare has undoubtedly brought many advancements through information technology. Specifically, healthcare informatics involves the use of various technologies, data management and communication systems to collect, store, analyze and effectively disseminate information. Therefore, the above serves to improve care as well as patient outcomes, improve efficiency, promote innovation and data analysis, as digitization has become an integral part of our daily lives in today's world. However, with the increased use of interconnected systems and electronic health records, hospitals have become prime targets for cyber-attacks. In this article we will delve into the critical topic of cybersecurity in hospitals as well as nursing facilities. The deepening of this issue was carried out with extensive analysis of the security systems of Greek hospitals. We investigated all their web sites and the security systems already in place on those sites. By checking we found a number vulnerabilities and potential risks. The most important weakness is the lack of legal as well as technical information for all interested citizens and patients. More organizational as well as technical work concerning internal architecture of information systems is needed, towards the improvement of security. In conclusion, we present our proposals on strategies to strengthen healthcare facilities against cyber threats. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： Cybersecurity Digitization Healthcare Information Patients Systems

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CPIMAC: MEC-assisted Message Dissemination Based on Traffic Prediction at Intersections 10

CPIMAC: MEC-assisted Message Dissemination Based on Traffic ...

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10th IEEE Smart World Congress, SWC 2024

作者： Liu, Bingyi Shao, Xun Zhao, Haoxiang Wang, Enshu Liu, Zhi Wuhan University of Technology Sanya Science and Education Innovation Park Sanya China Toyohashi University of Technology Department of Electrical and Electronic Information Engineering Aichi Japan Wuhan University School of Cyber Science and Engineering Wuhan China The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9798331520861

The Internet of Vehicles (IoV) is gaining increasing attention for its ability to improve traffic safety and efficiency by providing situational awareness and detecting potential hazards beyond the visual range. Time division multiple access (TDMA) based communication protocol effectively prevents transmission collisions in IoV. However, road intersections pose challenges for the implementation of TDMA-based MAC protocols, as vehicles converge from different directions, leading to severe communication access and merging collisions. To address this issue, we propose a distributed MAC protocol named slot collisions prediction based MAC at intersection (CPIMAC). Specifically, We combine mobile edge computing (MEC) with a CNN-BiLSTM-Attention neural network model to predict potential transmission collisions and propose corresponding collision avoidance algorithms. In addition, we design the head-tail beacon (HTB) algorithm to reduce slot collisions during vehicle waiting periods at intersections by adjusting beacon frequency. Finally, we conduct extensive experiments to evaluate the proposed protocol. The results show that transmission collisions can be reduced by 58.1 % compared to the existing protocols. © 2024 IEEE.

关键词： Time division multiple access

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Performance Analysis of Predicting LIC Stock Price using Lasso Regression Compared with Random Forest Regression 2

Performance Analysis of Predicting LIC Stock Price using Las...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Kumar, Chennupati Charan Parthipan, V. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Big Data and Network Security Tamil Nadu Chennai India

ISBN: (纸本)9798350364699

With regard to the objective of the entire study, the goal is to improve the accuracy of predicting stock price using Lasso Regression in comparison to Random Forest Regression. The Novel K-Nearest Neighbors and Support Vector Machine Algorithm are the two groups that are the emphasis of this research activity. Each of these groups is carried out ten times. For the purpose of calculating samples, the Clincal software was utilized. The alpha value was determined to be 0.05, and the confidence interval was set at 95%. We took into consideration the stock price prediction dataset that was available on *** and had a size of 12617. With a value of p=0.000 (Independent sample t-test p © 2024 IEEE.

关键词： Support vector regression

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