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Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

computers, Materials & Continua 2024年第9期80卷 3945-3966页

作者： R.Mahaveerakannan Thanarajan Tamilvizhi Sonia Jenifer Rayen Osamah Ibrahim Khalaf Habib Hamam Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Solar Energy Al-Nahrain Research Center for Renewable EnergyAl-Nahrain UniversityJadriyaBaghdad64074Iraq Faculty of Engineering Universitéde MonctonNew BrunswickE1A3E9Canada Hodmas University College Mogadishu521376Somalia Bridges for Academic Excellence Tunis1002Tunisia School of Electrical Engineering University of JohannesburgAuckland ParkJohannesburg2006South Africa

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia *** light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of *** 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of ***,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate *** findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 *** a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G *** improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving *** improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

关键词： Information-centric networking caching schemes 5G communication non-negative matrix factorization(NMF) weighted clustering algorithm

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Implementation of PSO-Optimized PI Control Algorithm for SMES Based DVR in Power Quality Mitigation 3

Implementation of PSO-Optimized PI Control Algorithm for SME...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Jeba Singh, O. Immanuel, D. Godwin Mahapatra, Sheila Rajesh Sharma, R. Sungheetha, Akey Ghantasala, G.S. Pradeep Alliance University Centre for Academic Research Bengaluru India School of Electrical and Electronics Sathyabama Institute of Science of Technology Chennai India Alliance University Department of Electrical and Electronics Engineering Bengaluru India Alliance University Department of Computer Sciences and Engineering Bengaluru India

ISBN: (纸本)9798331518592

Nowadays, Power Quality (PQ) problems should be more concentrated in distribution systems of power sector. To maintain the power quality in the distribution system the occurrence of PQ disturbances must be identified and compensated. Disturbances like voltage sag and swell are the major issues that cause failure in electrical devices. In this paper, a Superconducting Magnetic Energy Storage (SMES) integrated Dynamic Voltage Restorer (DVR)is implemented to protect the grid voltage from sag, swell and transients. A better solution to PQ disturbances and mitigation related issues are provided through DVR topology. Voltage sag is one of the dominant problems which cause the PQ issues. In this proposed work, sag, swell and outages are mitigated thus the real power is recovered so that the power wastage is prevented. Moreover, this SMES technology-based DVR method compensates the grid from balanced and unbalanced sag, mitigation of outages, interruption, single phase and two-phase swell conditions. The principle, design and working of the SMES based DVR is implemented using MATLAB / SIMULINK. The testing of the established model and performance results are presented. © 2024 IEEE.

关键词： Dynamic voltage restorer Particle swarm optimization Superconducting magnetic energy storage Voltage sag Voltage swell

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Cluster-Factors of Mobile Sensor Network technology for Security Enhanced PEGASIS

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第18期17卷 143-155页

作者： Sivakumar, T.K. Dhyani, Saurabh Manikanthan, S.V. Kaliappan, Vishnu Kumar Baskaran, K. Kishore, Kakarla Hari Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chennai India Department of USCS Uttaranchal University Uttarakhand Dehradun India Melange Academic Research Associates Puducherry India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Tamil Nadu Coimbatore India Department of Biomedical Engineering Chennai Institute of Technology Tamil Nadu Chennai India Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India

Mobile wireless sensor networks (MWSNs) have been a hot topic of research, and numerous routing methods have been developed to increase energy efficiency and extend longevity. Nodes close to the sink often use more energy to transmit data from their neighbors to the sink, which causes them to run out of energy faster. These places are also referred to as rendezvous points, and choosing the best one is a hard task. The likelihood of choosing an ideal node as the rendezvous point will be extremely low because hierarchical algorithms only use their local information to select these places. The warm spot problem is addressed from four angles in this work using the Enhanced Power-Efficient Gathering in Sensor Information Systems (EPEGASIS) technique. In order to limit the amount of energy used during transmission, the ideal communication distance is first calculated. To balance the energy consumption among the nodes, mobile sink technology is employed once a threshold value is set to safeguard the dying nodes. The node can then modify its communication range based on how far away the sink node is from it. Thorough testing has been done to demonstrate that our suggested EPEGASIS works better in terms of longevity, drive usage, and web latency. © 2023 by the authors of this article. Published under CC-BY.

关键词： Energy efficiency

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Efficient Data Completion and Augmentation

Efficient Data Completion and Augmentation

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International Conference on Data Science and Advanced Analytics (DSAA)

作者： Antonina Krajewska Ewa Niewiadomska-Szynkiewicz Research and Academic Computer Network (NASK) Warsaw Poland Institute of Control and Computation Engineering Warsaw University of Technology Warsaw Poland

ISBN: (数字)9798350364941

ISBN: (纸本)9798350364958

Fast data completion and augmentation methods with provable theoretical guarantees enable efficient and reliable data analysis. Many datasets can be represented as real-valued matrices and filled using matrix completion (MC) methods. This paper proposes a novel two-step approach for matrix recovery involving the sequential solution of convex optimization tasks. Firstly, a subset of columns is randomly chosen, and the matrix is completed using a nuclear norm minimization algorithm. Secondly, we solve the least squares problem by incorporating the known elements and the completed columns. We introduce three algorithms for implementing our Columns Selected Matrix Completion (CSMC) method, tailored to different problem sizes. Provided necessary assumptions and the probability of achieving accurate solutions are validated through extensive numerical experiments. Synthetic data experiments assess the method's performance regarding matrix size, rank, and missing element proportion. Evaluation in image completion and graph link prediction demonstrates that CSMC provides comparable solution quality to state-of-the-art convex optimization-based MC algortthms while significantly reduciny computation time.

关键词： Accuracy Reliability theory Data science Minimization Convex functions Optimization Synthetic data

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A Comprehensive Approach to Identify Stroke based on Real-time Medical Data 1

A Comprehensive Approach to Identify Stroke based on Real-ti...

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1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Maragatharajan, M. Shanmugapriya, S. Sudhan, M.B. Deeptha, R. Paramasivam, Sankar Muthu Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh Kothrikalan India Kalasalingam Academy of Research and Education School of Computing Department of Computer Science and Engineering Tamilnadu Srivilliputhur India Srm Institute of Science and Technology Department of Computer Science and Engineering RamapuramTamilnadu Chennai India Srm Institute of Science and Technology Department of Information Technology RamapuramTamilnadu Chennai India Palo Alto Networks Inc Distinguished Software Engineer 3000 Tannery Way Santa ClaraCA United States

ISBN: (纸本)9798350372748

Strokes or cardiovascular disorders continue to be a major global health concern. Proactive intervention and timely detection greatly reduce the morbidity and death related to strokes. The goal of this research is to build a prediction model using machine learning techniques to assess a person's risk of stroke based on a variety of sociodemographic and health characteristics. The dataset used in this study consists of a large collection of medical records. It contains important details including age, gender, BMI, smoking habits, heart disease, hypertension, and the type of residential property. Using this information, a Decision Tree Classifier is trained to predict the likelihood of strokes, enabling early detection and customized treatment plans. A Decision Tree Classifier with a predetermined maximum depth is used in the proposed methodology's rigorous data preprocessing, which includes handling missing values, encoding categorical features, and developing models. Both the training and testing datasets are used to evaluate the model's performance using evaluation measures including accuracy, precision, and recall. The model's insights provide important characteristics that influence the prediction of stroke risk, assisting medical professionals in focused risk assessment and preventive intervention. The proposed method has the potential to improve healthcare practices by facilitating prompt interventions and personalized treatment for stroke risk individuals. The proposed model has resulted in 86.78% accuracy for this dataset by using the traditional machine learning algorithms. This work highlights the value of predictive modelling in the healthcare industry by demonstrating how it may improve early detection techniques and lessen the impact of strokes on public health. © 2024 IEEE.

关键词： Forecasting

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Blockchain Based Secure Interoperable Framework for the Internet of Medical Things 16th

Blockchain Based Secure Interoperable Framework for the Inte...

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16th International Conference on Information technology and Applications, ICITA 2022

作者： Rafique, Wajid Shah, Babar Hakak, Saqib Khan, Maqbool Anwar, Sajid Department of Computer Science and Operations Research University of Montreal Quebec Canada Center of Excellence in IT Institute of Management Sciences Peshawar Pakistan Faculty of Computer Science Canadian Institute for Cybersecurity University of New Brunswick Fredericton Canada Pak-Austria Fachhochschule Institute of Applied Sciences and Technology Haripur Pakistan Software Competence Center Hagenberg Vienna Austria College of Information Technology Zayed University Academic United Arab Emirates

ISBN: (纸本)9789811993305

Internet of Medical Things (IoMT) has revolutionized the way medical infrastructure has been managed in the past. Multiple platforms in IoMT have disparate communication standards, data format requirements, and access policies, which produce immense overhead during data transfer among these platforms. In order to provide seamless healthcare services using IoMT, interoperability concerns of heterogeneous devices need to be addressed. Smart contracts using blockchain provide a secure communication for distributed objects to interact in a secure way. We propose a Blockchain-based Secure Interoperable Framework (BSIIoMT) using smart contracts for secure communication in IoMT. We present components, workflow, and design considerations of the BSIIoMT framework to show the feasibility of using edge-enabled blockchain for secure interoperability in IoMT. The BSIIoMT framework is an ongoing project where we present the framework and its components in this research where further results and evaluation will be presented in future. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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An Empirical Study of MPQUIC Schedulers in Mobile Wireless Networks 22

An Empirical Study of MPQUIC Schedulers in Mobile Wireless N...

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11th International Symposium on Information and Communication technology, SoICT 2022

作者： Vu, Minh Hai T. T. Nguyen, Giang Tran, Hai Dang Nguyen, Thanh Trung Do, Phan Thuan Nguyen, Phi Le Nguyen, Kien School of Information and Communication Technology Hanoi University of Science and Technology Viet Nam Faculty of Computer Science Phenikaa University Viet Nam Institute for Advanced Academic Research Chiba University Japan

ISBN: (纸本)9781450397254

Multipath QUIC (MPQUIC), an emerging multipath transport protocol (MTP) that inherits the advantages of the canonical multipath TCP (MPTCP) and the widespread QUIC, potentially plays a vital role in 5G and beyond. MPQUIC can exploit multiple networks (e.g., Wi-Fi, LTE, 5G) on a mobile device to boost the quality of services while efficiently utilizing network resources. In MPQUIC, the scheduler, which is in charge of concurrently scheduling data transmission in several paths, largely impacts the protocols' performance, especially in dynamic environments. In fact, in the literature, a considerable number of MTP schedulers for MPQUIC have been proposed. Unfortunately, their performances have been primarily evaluated in static networks without (or simply) considering mobile ones. Hence, this work attempts to investigate the performance of MPQUIC schedulers in the mobile context, aiming to fill the literature gap. Specifically, we implement and assess the performance of five MPQUIC schedulers in various mobility patterns using the Mininet-WiFi emulator. More importantly, we introduce q-ReLeS, an extension of an MPTCP scheduler called ReLeS for MPQUIC. The experimental results show that q-ReLeS reduces the download time from to compared to the others. Besides, the empirical investigation demonstrates that mobility and velocity patterns substantially impact the performance of MPQUIC schedulers. © 2022 ACM.

关键词： Wi-Fi

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Friendly Chatbot with IBM Watson Assistant Support Elderly Delightful in Smart Mirror 11

Friendly Chatbot with IBM Watson Assistant Support Elderly D...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Prajugjit, Nattapon Silapasuphakornwong, Piyarat Sookhanaphibarn, Kingkarn Uehira, Kazutake Department of Computer Engineer Bangkok University Thailand Bangkok Thailand Lab Bangkok University Thailand Bangkok Thailand Kanagawa Institute of Technology Advance AI Research Center Atsugi Japan

ISBN: (纸本)9781665492324

This paper used IBM Watson Assistant to create dialog for a 'friendly' chatbot for supporting elderly people who have to live alone. The system invites the elderly to have a continued conversation for the purpose of decreasing problems related to depressions and slowing the progression of dementia. We created dialogues in Japanese for three characters, a benign nurse, a lovely girl, and a kind senior, and seven events. The accuracy was 93.44% in the case of talking with the different words in dialogues having the same meaning. This chatbot can act as a communication function in our previously proposed smart mirror to support the elderly by enabling them to talk with a bot in long-term health-care programs for monitoring the elderly in the future. © 2022 IEEE.

关键词： Mirrors

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ICERS:Intelligent Collaborative Emergency Response System 23

ICERS:Intelligent Collaborative Emergency Response System

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23rd International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2024

作者： Yang, Guoyin Zhang, Haotian Yao, Junfeng Cai, Chengyou Song, Jun Xu, Yuelin Deng, Bin School of Computer Engineer and Science Shanghai University Shanghai China The 32nd Research Institute of China Electronics Technology Group Corporation China CSSC Seago System Technology Co. Ltd. Shanghai200010 China Department of Geography Hong Kong Baptist University Hong Kong Science and Technology on Near-Surface Detection Laboratory Wuxi China

ISBN: (纸本)9781643685380

Advances in computer science and technology, coupled with the growing societal demand for enhanced safety, have paved the way for innovative smart home environments. While current smart home systems can send alarms and notify emergency contacts during a crisis, they do not provide timely and convenient on-site emergency assistance, potentially delaying critical aid and compromising user safety. This paper introduces the Intelligent Collaborative Emergency System (ICERS), which addresses this gap through three integrated subsystems: Fall Detection, Vital Signs Monitoring, and Central Dispatch. The Fall Detection module leverages camera video data to classify human positions and estimate potential falls. The Vital Signs Monitoring module employs millimeter-wave radar technology to provide non-contact, real-time health monitoring. The Central Dispatch system receives alert signals from on-edge devices and relays them to medical facilities and volunteer organizations for a coordinated emergency response. By utilizing multimodal data for collaborative efforts, the ICERS ensures that individuals receive timely notifications and coordinated emergency assistance during unforeseen situations. © 2024 IOS Press. All rights reserved.

关键词： Fall detection

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Fusion of DRL and CNN for Effective Face Recognition 1

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8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Kumar, Ankit Singh, Sushil Kumar Ravikumar, R.N. Khanna, Ashish Brahma, Biswajit Dr. APJ Abdul Kalam Technical University Lucknow India Department of Computer Engineering Marwadi University Rajkot India Computer Science and Engineering Department Maharaja Agrasen Institute of Technology Delhi India Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Chennai India Senior Data and Visualization Engineer McKesson Corporation USA 32559 Lake Bridgeport St FremontCA94555 United States

ISBN: (数字)9789819765812

ISBN: (纸本)9789819765805

Digital Authentication combined with IOT networks is one of the most innovative practices in innovations. IoT devices such as surveillance cameras have acquired real-time video data in the natural environment. Facial Biometrics for System authentication is considered to be a sophisticated technology used in various devices. The correct processing of digital information in a natural environment is one of the challenging tasks. Noise effect inducts random variations on the subject in the natural environment that may hinder the recognition efficiency of the model. The proposed system recognizes facial biometric features under the natural environment that may contain non-symmetrical randomness of variations. The system's objective is to mitigate the false recognition rates under adverse environmental conditions. It combines digital information with a person’s real-time environment. The detection of the facial region of interest form frames in a real-time dataset has been taken through the Viola-Jones algorithm. Feature extrication using video frames has been developed through Deep Reinforcement Learning (DRL) algorithm, which aims to generate binary trees containing feature vectors. Further, the system uses a convolutional neural network (CNN) model to establish the correlation of feature vectors belonging to the facial identity. The model's objective is to retain high recognition of facial biometric trait feature units under various randomness in a natural environment. The proposed system is also tested under various attacks to test the robustness of the proposed model. The model can secure an average accuracy of 98.85%. Digital forensics, crime investigation, online attendance, etc., are the few applications of Facial data authentication from dynamic input. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep reinforcement learning

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