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IEEE Networking Letters 2024年第3期6卷 183-187页

作者： Abbasi, Omid Kaddoum, Georges Carleton University Non-Terrestrial Networks Lab Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada Université du Québec École de Technologie Supérieure Department of Electrical Engineering MontrealQCH3C 1K3 Canada Lebanese American University Cyber Security Systems and Applied Ai Research Center Beirut2801 Lebanon

Satellite communication systems encounter channel aging issues due to the substantial distance that separates users and satellites. In such systems, the estimated channel state at a given time slot reflects the channel state from several time slots in the past. This letter proposes a long short-term memory (LSTM)-based architecture for channel prediction to mitigate the channel aging problem. The proposed scheme predicts the next time slot's channel based on a block of estimated channel state information (CSI) from previous time slots. We consider the effect of channel aging in the training phase so that channel prediction in the testing phase is performed based on available data. We demonstrated through simulation experiments on new radio non-terrestrial network tapped delay line (NR NTN TDL) channel models, that our proposed scheme can effectively mitigate channel aging, and that it performs better than outdated channels. The proposed scheme improves the reliability and efficiency of satellite communication systems with long propagation delays. © 2019 IEEE.

关键词： Satellite communication systems

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PpNNT: Multiparty Privacy-Preserving Neural Network Training System

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 370-383页

作者： Feng, Qi He, Debiao Shen, Jian Luo, Min Choo, Kim-Kwang Raymond Wuhan University School of Cyber Science and Engineering Wuhan430072 China Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou310018 China Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Matrix Elements Technologies Shanghai201204 China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

By leveraging smart devices [e.g., industrial Internet of Things (IIoT)] and real-time data analytics, organizations, such as production plants can benefit from increased productivity, reduced costs, enhanced self-monitoring, and autonomous decision-making. In such a setting, machine learning plays an important role in data analytics, but the use of conventional centralized machine learning solutions may raise uncomfortable concerns about data privacy. Hence, one can explore the use of federated learning. In this article, we propose privacy-preserving deep neural network training (PpNNT), which is designed to support federated learning in the multiparty setting. To minimize the overall costs, we further design a hybrid architecture to fully maximize resource utilization. Our proposed design allows the PpNNT system to provide high security, efficiency, and scalability for IIoT data analytics, as evidenced by our theoretical security proof and experimental results on the CIFAR10 dataset. © 2020 IEEE.

关键词： Decision making

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TailClip: Mitigating Tail Latency in Cloud Gaming via Smart Video Frame Generation

TailClip: Mitigating Tail Latency in Cloud Gaming via Smart ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Qianyun Gong Kunheng Jiang Jingjing Wen Xinjing Yuan Jianxin Shi Lingjun Pu Institute of Systems and Networks College of Computer Science Nankai University Tianjin China Key Laboratory of Data and Intelligent System Security Ministry of Education Nankai University Tianjin China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Latency is one of the most significant issues in cloud gaming, among which tail latency, mainly attributed to dynamic network environments (i.e., transmission) and limited device computing capacity (e.g., decoding), has attracted increasing attention. To mitigate the tail latency, different from existing researches considering resource adaptation such as bitrate adaptation, we propose TailClip, whose novel idea is to enable video frame generation at the client if the tail latency is about to happen. TailClip consists of two innovative components: a Deep Reinforcement Learning (DRL) driven tail latency trigger that jointly decides a series of subsequent frame generation regarding multidimensional features of historical tail latency; a lightweight frame generation model derived by adaptive pruning in terms of device computing capacity at runtime. Extensive evaluations indicate the superior performance of TailClip. For example, it can remove the high-latency frames (i.e., over 100 ms) by 77% with an acceptable video quality (i.e., 0.45 dB reduction on average).

关键词： Performance evaluation Runtime Computational modeling Tail Cloud gaming Streaming media Deep reinforcement learning

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Modeling and Optimization of Discrete Evolutionary systems of İnformation security Management in a Random Environment 1

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International Conference on Machine Learning and Autonomous systems, ICMLAS 2021

作者： Lakhno, V.A. Kasatkin, D.Y. Skliarenko, O.V. Kolodinska, Y.O. Department of Computer Systems and Networks National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Information Technology Cyber Security and Mathematical Sciences Private Higher Education Institution European University Kyiv Ukraine

ISBN: (数字)9789811679964

ISBN: (纸本)9789811679957

A method for studying the stability of zero solutions of a system of nonlinear difference equations depending on the semi-Markov chain is proposed. The essence of the proposed method is to study the stability of moment equations that are deterministic for the above systems. The necessary optimality conditions for these systems are derived. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nonlinear equations

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Performance Framework for Virtual Machine Migration in Cloud Computing

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computers, Materials & Continua 2023年第3期74卷 6289-6305页

作者： Tahir Alyas Taher M.Ghazal Badria Sulaiman Alfurhood Munir Ahmad Ossma Ali Thawabeh Khalid Alissa Qaiser Abbas Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Information Technology Skyline University CollegeUniversity City SharjahSharjah1797UAE Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebansaan Malaysia(UKM)Bangi43600SelangorMalaysia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Dean of Student Affairs Skyline University CollegeUniversity City SharjahSharjah1797UAE Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Faculty of Computer and Information Systems Islamic University Madinah Madinah42351Saudi Arabia

In the cloud environment,the transfer of data from one cloud server to another cloud server is called *** can be delivered in various ways,from one data centre to *** research aims to increase the migration performance of the virtual machine(VM)in the cloud *** allow cloud customers to store essential data and ***,server usage has grown dramatically due to the virtualization of computer systems,resulting in higher data centre power consumption,storage needs,and operating *** VMs on one data centre manage share resources like central processing unit(CPU)cache,network bandwidth,memory,and application ***-cloud,VMmigration addresses the performance degradation due to cloud server configuration,unbalanced traffic load,resource load management,and fault situations during data *** speed is influenced by the size of the VM,the dirty rate of the running application,and the latency ofmigration *** a result,evaluating VM migration performance while considering all of these factors becomes a difficult *** effort of this research is to assess migration problems on *** simulation results in Matlab show that if the VMsize grows,themigration time of VMs and the downtime can be impacted by three orders *** dirty page rate decreases,themigration time and the downtime grow,and the latency time decreases as network bandwidth increases during the migration time and post-migration overhead calculation when the VMtransfer is *** the simulated cases of VMs migration were performed in a fuzzy inference system with performance graphs.

关键词： Latency cloud computing dirty page ratio storage migration performance

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Problems of Ensuring the Protection of Industrial Enterprises Technological networks

Problems of Ensuring the Protection of Industrial Enterprise...

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International Russian Automation Conference (RusAutoCon)

作者： Ulyana Kuzmina Ivan Bachurin Olga Mikhailova Department of computer science and information security Nosov Magnitogorsk State Technical University (NMSTU) Magnitogorsk Russia Department of Computers Systems and Networks National Research University (MPEI) Moscow Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The article discusses the basics of constructing technological networks of industrial enterprises and approaches to ensuring their protection. A generalized block diagram of the automated process control system of an industrial enterprise is considered. The article provides an analysis of cyber attack statistics for 2023. The testing ground for the study was the industrial enterprises of the region. Based on experimental studies on a wide range of security indicators, statistics on measures to ensure the security of industrial enterprises in the region were obtained. Based on the statistics obtained, recommendations were developed to ensure information security measures for industrial networks of enterprises.

关键词： Wireless communication Production management Current measurement Process control Intrusion detection Software Protection Standards Monitoring Testing

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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Engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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AI in Education: Improving Quality for Both Centralized and Decentralized Frameworks 14

AI in Education: Improving Quality for Both Centralized and ...

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14th IEEE Global Engineering Education Conference, EDUCON 2023

作者： Madathil, Nisha Thorakkattu Alrabaee, Saed Al-Kfairy, Mousa Damseh, Rafat Belkacem, Abdelkader N College of IT United Arab Emirates University Department of Information Systems and Security United Arab Emirates College of Technological Innovation Zayed University Dubai United Arab Emirates College of IT Department of Computer Science and Software Engineering United Arab Emirates University United Arab Emirates College of IT Department of Computer Engineering and Networks United Arab Emirates University United Arab Emirates

ISBN: (纸本)9798350399431

Education is essential for achieving many Sustainable Development Goals (SDGs). Therefore, the education system focuses on empowering more educated people and improving the quality of the education system. One of the latest technologies to enhance the quality of education is Artificial Intelligence (AI)-based Machine Learning (ML). As a result, ML has a significant influence on the education system. ML is currently widely applied in the education system for various tasks, such as creating models by monitoring student performance and activities that accurately predict student outcomes, their engagement in learning activities, decision-making, problem-solving capabilities, etc. In this research, we provide a survey of machine learning frameworks for both distributed (clusters of schools and universities) and centralized (university or school) educational institutions to predict the quality of students' learning outcomes and find solutions to improve the quality of their education system. Additionally, this work explores the application of ML in teaching and learning for further improvements in the learning environment for centralized and distributed education systems. © 2023 IEEE.

关键词： Sustainable development

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Reliability Models of Multi-state UAV-based Monitoring systems: Mission Efficiency Degradation Issues

Reliability Models of Multi-state UAV-based Monitoring Syste...

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International Conference on Digital Technologies (DT)

作者： Ihor Kliushnikov Vyacheslav Kharchenko Herman Fesenko Elena Zaitseva Vitaly Levashenko Department of Computer Systems Networks and Cyber Security National Aerospace University “KhAI“ Kharkiv Ukraine Faculty of Management Science and Informatics University of Zilina Zilina Slovakia

General classification of multi-state UAV-based monitoring systems (MsUMSs) in view of types of used main and redundant unmanned aerial vehicles (UAVs), automatic battery maintenance stations (ABMSs), and mission efficiency degradation parameters is presented. General classification of reliability models for the MsUMS in view of the numbers of the main routes, route sections, UAVs, ABMSs, and degradation levels, is given and discussed. Reliability models for the MsUMS with various parameters are developed. The mission efficiency of the MsUMS and the probability of successful UAV mission plan fulfilment within the specified time frame on each of the degradation levels are utilized as basic indicators. Zero, one, and two-level-degradation reliability models for the MsUMS are explored and discussed in detail. A comparative analysis of the developed models is carried out.

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Applied Aspects of Polyharmonic Functions for security and Reliability of Data Transmission 8

Applied Aspects of Polyharmonic Functions for Security and R...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Laptiev, Oleksandr Sobchuk, Andrii Ryzhov, Anton Perehuda, Oleh Tsygansvska, Iryna Kopytko, Serhii Taras Shevchenko National University of Kyiv Faculty of information technology Department of Cyber Security and Information Protection Kyiv Ukraine State University of Information and Communication Technologies Department of Information and Cyber Security Kyiv Ukraine Taras Shevchenko National University of Kyiv Faculty of Mechanics and Mathematics Department of General Mathematics Kyiv Ukraine Taras Shevchenko National University of Kyiv Faculty of Mechanics and Mathematics Department of Algebra and Computer Mathematics Kyiv Ukraine Lviv Polytechnic National University Department of Information Systems and Networks Lviv Ukraine

ISBN: (纸本)9798350354423

At present, when armed conflicts have intensified, and especially against the background of Russia's armed aggression against Ukraine, a new era of development of high-precision means of protection and weapons has begun. Their effectiveness is primarily determined by the state of radio-electronic technical means. These include means of communication and control, radar and hydroacoustics, telemetry, etc. Thus, the effectiveness of the solution of the tasks before the radio-electronic device depends on the class of signals used. In particular, the type of signal depends on the quality of the communication, the range, the resolution capabilities according to various parameters, the probability of detection, the quality of control, stealth, etc. But the detection of hidden signals requires high-quality signal processing with consistent mathematical analysis of the signal. This requires a powerful mathematical apparatus. As an example of signal processing, the article discusses methods of using signal transformation using polyharmonic operators. The transformation of signals by two types of operators is presented: the Abel-Poisson operator and the Weierstrass operator. The simulation results proved the advantages of Weierstrass operators for signal transformation. © 2024 IEEE.

关键词： Mathematical transformations

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