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Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs

IEEE Network 2024年

作者： Chen, Xianfu Wu, Celimuge Shen, Yi Ji, Yusheng Yoshinaga, Tsutomu Ni, Qiang Zarakovitis, Charilaos C. Zhang, Honggang Shenzhen CyberAray Network Technology Co. Ltd China Chinese Academy of Sciences Shanghai Advanced Research Institute China Meta-Networking Research Center China The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo Japan National Institute of Informatics Information Systems Architecture Research Division Tokyo Japan Lancaster University School of Computing and Communications Ukraine AXON Logic Greece City University of Macau Faculty of Data Science Macau China China

This article investigates a control system within the context of sixth-generation wireless networks. The remote control performance optimization confronts the technical challenges that arise from the intricate interactions between communication and control sub-systems, asking for a co-design. Considering the system dynamics, we formulate the sequential co-design decision-makings of communication and control over a discrete time horizon as a Markov decision process, for which a practical offline learning framework is proposed. Our proposed framework integrates large language models into the elements of reinforcement learning. We present a case study on the age of semantics-aware communication and control co-design to showcase the potential of our proposed learning framework. Furthermore, we discuss the open issues remaining to make our offline learning framework feasible for real-world implementations and highlight the research directions for future explorations. © 1986-2012 IEEE.

关键词： Markov processes

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Cross-Technology Communication between WiFi and ZigBee 9

Cross-Technology Communication between WiFi and ZigBee

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9th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE 2022

作者： Fan, Wendong Chen, Tian Gu, Yu Li, Yang Hefei University of Technology S2AC Lab School of Computer and Information Hefei China Hefei University of Technology Institute of Affective Computing and Systems Architecture Hefei China Anhui Agricultural University School of Information & Computer Hefei China

ISBN: (数字)9781665427753

ISBN: (纸本)9781665427753

The coexistence of heterogeneous devices in the Internet of Things wireless network brings a new topic of cross-technology communication in order to improve the communication efficiency between heterogeneous devices and promote the cooperation between heterogeneous devices. WiFi and ZigBee are the two most commonly used IoT devices in IoT environments. They have the advantages of low communication delay, high speed, low cost, and easy deployment. Since the spectrum of WiFi and ZigBee overlap, ZigBee signal will affect the transmission of CSI signal. We propose a CTC technique based on machine learning and deep learning, which uses only WiFi channel state information (CSI), and can distinguish whether there is ZigBee signal transmission in WiFi signals by classifying WiFi channel state information. In this paper, machine learning classification methods and deep learning methods are used to classify CSI sequences respectively. We extract the features of 8 CSI sequences to improve the accuracy of machine learning classifier and LSTM classifier, and adopt transformer network classifier to further improve the classification accuracy. In our experimental dataset, the highest accuracy rate can reach 94.9%. The evaluation results show that the accuracy of this method is significantly higher than the existing classification methods. © 2022 IEEE.

关键词： Channel state information

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Detecting Model Poisoning Attacks Via Dummy Symbol Insertion for Secure Over-the-Air Federated Learning

Detecting Model Poisoning Attacks Via Dummy Symbol Insertion...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Hang Zhou Yi-Han Chiang Caijuan Chen Xiaoyan Wang Yusheng Ji Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan Department of Electrical and Electronic Systems Engineering Osaka Metropolitan University Osaka Japan Graduate School of Science and Engineering Ibaraki University Hitachi Japan

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

With the rapid advancement of intelligent IoT services, the need for high-quality and efficient wireless communication has become increasingly critical for information exchanges and collaborations among intelligent edge devices such as autonomous mobile robots (AMRs), robots in smart factories, and surveillance cameras, etc., Federated Learning (FL) is a promising distributed learning framework by exploring the computation capability on edge devices while protecting data privacy of users. On the other hand, Over-the-Air (OTA) computation techniques is a new paradigm of integrated computation and communication. OTA based FL (OTA-FL) can enhance spectrum efficiency by leveraging the superposition properties of wireless channels for model aggregations. The implementation of OTA-FL on edge devices can further protect user data privacy for clients, improve the throughput of inter-device communications, and enhance the distributed learning performance. However, despite these advantages, the convergence of OTA-FL systems remain vulnerable to model poisoning attacks, presenting significant challenges. In this study, we address these vulnerabilities by proposing a two-phase detection mechanism that secures OTA-FL system while preserving high spectral efficiency. Our simulation results demonstrate that under varying conditions, our approach can make distributed learning more secure and communication-efficient.

关键词： Computer aided instruction Data privacy Federated learning Distance learning Wireless networks Computational modeling Surveillance Symbols Throughput Convergence

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Secure- and Privacy-Preserving Policies for Distributed Cooperative Control of Multiple Vehicle systems

Secure- and Privacy-Preserving Policies for Distributed Coop...

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Autonomous systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023

作者： Nguyen, Binh T. Nghiem, Truong X. Nguyen, Linh Nguyen, Tuy Tan Nguyen, Thang The Department of Engineering Texas A&M University-Corpus Christi Corpus ChristiTX78412 United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ86011 United States Institute of Innovation Science and Sustainability Federation University Australia ChurchillVIC3842 Australia

ISBN: (纸本)9781510661967

Conventional distributed formation control of multiple vehicle systems (MVSs) has two drawbacks: inflexible formation changes and explicit-value exchanges of vehicles' information such as position and velocity among all vehicles. Since formation changes are needed, each vehicle is required to update its relative position which is quite difficult in large spatial applications. Firstly, the explicit-value exchanges possibly result in two critical issues. When each vehicle policy needs to keep its information confidential from another unexpected listener, the explicit-value exchanges are invalid for the privacy policies. Additionally, the explicit-value storing or exchanging signals or parameters are much more vulnerable and dangerous to security threats. This work proposes an approach to overcome the above challenges by taking advantage of model predictive control-consensus algorithms to achieve desired formations. We will also allow the computation to be effectively distributed among the vehicle agents according to their computational capabilities. Secondly, we use the highly secure encryption scheme that empowers all computations carried out in encrypted forms, including system parameters and signals. Our results are verified by the formation control of multiple vehicles working in large-scale environments where a ground station does not touch all vehicles due to limited communication ranges and security problems. Compared to cutting-edge studies, the formation of vehicles is still able to be changed securely by the ground station without updating new formations to all vehicles. Besides, the data privacy of each vehicle is preserved by encrypting all physical signals. © 2023 SPIE. All rights reserved.

关键词： Vehicles

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Intelligent Resource Allocation in Power Grids: Leveraging Variable Neighborhood Search for Optimal Switch Allocation

Intelligent Resource Allocation in Power Grids: Leveraging V...

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IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Henrique O. Caetano Matheus de S. S. Fogliatto N. Luiz Desuó Benvindo R. Pereira J Carlos D. Maciel Marco Aiello Dept. of Electrical and Computer Engineering São Carlos School of Engineering University of São Paulo Department of Service Computing Institute for Architecture of Application Systems University of Stuttgart

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

Within the paradigm of Evolving and Adaptive Intelligent systems, the Electrical Power System (EPS) represents a Critical Infrastructure demanding robust reliability metrics. This study pioneers the application of Variable Neighborhood Search (VNS) heuristic to the Optimal Switch Allocation (OSA) problem in the EPS. Adapting neighborhood structures and local search methods, we consider the joint allocation of Manual Switches and Remote-Controlled switches, addressing interdependencies. Results highlight VNS efficacy in navigating OSA challenges, showcasing its adaptability in an evolving system. Comparative analyses endorse VNS as a valuable tool for addressing EPS reliability within the dynamic landscape of evolving and adaptive intelligent systems.

关键词： Adaptive systems Uncertainty Switches Search problems Robustness Power grids Critical infrastructure

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Quantifying uncertainty in Bayesian Networks structural learning

Quantifying uncertainty in Bayesian Networks structural lear...

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IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Vitor O. Barth Henrique O. Caetano Carlos D. Maciel Marco Aiello Dept. of Electrical and Computer Engineering São Carlos School of Engineering University of São Paulo Department of Service Computing Institute for Architecture of Application Systems University of Stuttgart

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

The key goals in learning Bayesian networks (BNs) from data are to identify significant statistical relationships between variables and to build a Directed Acyclic Graph (DAG) that represents these relationships through Joint Probability Distributions. Most research relies on score-based or conditional test methods for model selection. However, when using real-world data, it can be challenging to identify whether the learned DAG represents the underlying relations inherent in the limited datasets, particularly when evaluating data obtained from multiple independent sources. This study presents a methodology to assess the credible interval for both the existence and direction of each edge within Bayesian networks derived from data. Furthermore, it explores the fusion of models acquired from distinct and independent datasets. This approach enables the Bayesian learning of Bayesian Networks (BNs) from data by treating the uncertainty associated with the existence and orientation of each edge as a random variable. By evaluating the probability of the orientation of each edge, it is possible to suggest the existence of a potential latent variable within the dataset. If an edge exhibits equiprobable directions and is verified to exist, it becomes a plausible hypothesis for a latent variable. The Fast Causal Algorithm, originally introduced by [1], is the foundation of this approach. Finally, by employing a maximum a posteriori estimation, the most prominent edges and their respective orientations are identified and employed to create the leading DAG. We present our findings in simulated datasets with different length sizes. By comparing the structure of the learned DAGs with existing structures and evaluating the inference capabilities of the final BN, we establish that our approach achieves results comparable to the most recent studies in the field, while offering insights into the model’s reliability and improving the use of the data.

关键词： Maximum a posteriori estimation Uncertainty Scalability Data models Probability distribution Bayes methods Random variables

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Technology Mediated Caregiving For Older Adults Aging in Place

Technology Mediated Caregiving For Older Adults Aging in Pla...

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2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Mynatt, Elizabeth D. Kobayashi, Masatomo Pradhan, Alisha Mathur, Niharika Vines, John Seaborn, Katie Buehler, Erin Waycott, Jenny Rudnik, John Zubatiy, Tamara Rozga, Agata Khoury College of Computer Sciences Northeastern University BostonMA United States IBM Research Tokyo Japan Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States School of Interactive Computing Georgia Institute of Technology AtlantaGA United States University of Edinburgh Edinburgh United Kingdom Institute of Science Tokyo Japan Google Mountain ViewCA United States School of Computing and Information Systems The University of Melbourne Melbourne Australia School of Information University of Michigan Ann ArborMI United States Northeastern University BostonMA United States

ISBN: (纸本)9798400713958

The caregiving environment for an older adult aging in place includes a network of caregivers working with the older adult to support their needs and maintain independence. As older adults experience cognitive and functional changes, their caregiving network expands to include spouses or siblings (who are often older adults themselves), children, friends, neighbors and community members—each bringing unique values, expectations, and goals. In this network of care, technology-enabled support offers the potential to mediate care responsibilities, such as coordinating activities and assisting with everyday tasks. However, designing these systems requires addressing value tensions among caregivers, cultural norms around aging, participatory research practices and balancing autonomy with safety concerns for older adults in later life. This workshop brings together researchers and practitioners to discuss (1) opportunities and challenges for designing technological systems for caregiving for older adults;(2) longitudinal interactions with these systems as older adults progress through stages of functional and cognitive changes;(3) potential for such systems to support caregivers while centering older adults’ privacy and autonomy needs;and (4) the influence of cultural norms on caregiving and technology use. © 2025 Copyright held by the owner/author(s).

关键词： Assistive Technology Caregiving Older Adults

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Analysis and Design of Mobile Model for DTN

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Chinese Journal of Electronics 2023年第4期18卷 635-638页

作者： Zhiting Lin Yugui Qu Yusheng Ji Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China Province Key Laboratory of Software in Computing and Communication Hefei China Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

Delay tolerant networks may become unexpectedly partitioned due to node mobility or variation in signal strength. However, most widely used models in some relative works are generally very simplistic. In order to exploit intelligent forwarding algorithms, a novel nodal mobile model of delay tolerant networks is presented to map reality with more accuracy. And several approaches are introduced to analyze the network structure, such as n-cliques, n-clans, degree, closeness and betweenness. Our research results showed that the centralizations became smaller when the wireless connections were concerned. It meant that quite a number of nodes became potential relays because of the new structure of networks.

关键词： Wireless communication Analytical models Wireless sensor networks Protocols Social networking (online) Sensitivity analysis Social network theory

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Full life-cycle cost model for practical application of solar energy system

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Energy informatics 2025年第1期8卷

作者： Sha, Ang Xiong, Zhen Zang, Xiaolin Zhao, Wei Ge, Ruibang Yao, Wanxiang Aiello, Marco Innovation Institute for Sustainable Maritime Architecture Research and Technology Qingdao University of Technology Qingdao266033 China School of Architecture and Urban Planning Qingdao University of Technology Qingdao266033 China School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Continuing Education Qingdao University of Technology Qingdao266033 China Service Computing Department Institute of Architecture of Application Systems University of Stuttgart Universitätsstraße 38 Stuttgart70569 Germany

In pursuit of carbon neutrality, a swift transformation is underway in the global energy structure, marked by a consistent rise in the installed capacity of solar energy systems. Meanwhile, the substantial reduction of government subsidies in the solar industry intensifies focus on the economic viability of solar energy installations. In this study, we propose a full life-cycle cost model, named the F-LCC model, for calculating the cost of the solar energy system on the long term, e.g., 20–30 years. This model integrates replacement costs, residual value calculation, interest rate, and inflation impacts while supporting market price estimation for individual components, thereby aiding feasibility analysis in the early project phase. We design an investment cost recovery algorithm based on the F-LCC model to calculate the break-even electricity price for solar energy system. Moreover, we analyze component cost distributions, Net Present Value (NPV), and Discounted Payback Period (DPP) for grid-connected and off-grid solar energy systems with capacities of 10 kWp and 100 kWp in the Chinese market. The results show that the proposed model, compared to other models, captures the fact that payback times are longer. In a solar energy system without storage, solar panels have the highest component cost share at 28.8%. With battery storage, batteries dominate the total cost, reaching up to 74.6%. And the the grid-connected systems DPP ranging from a minimum of 5.5 to a maximum of 7.0 years by grid-connected electricity price, while off-grid systems require at least 19.9 years. The 10 kWp off-grid fixed mounting system’s break-even price being 137.1% higher than its grid-connected counterpart. In addition, tracking-mount systems offer greater cost-reduction potential than fixed installations, with the payback period reduced by 20% for 100 kWp grid-connected systems and 15% for off-grid systems. Finally, we develop a plugin based on the F-LCC model. These findings deepen unde

关键词： Commerce

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Hysteretic Optimality of Container Warming Control in Serverless computing systems

IEEE Networking Letters

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IEEE Networking Letters 2021年第3期3卷 138-141页

作者： Chiang, Yi-Han Zhu, Chao Lin, Hai Ji, Yusheng Department of Electrical and Information Systems Osaka Prefecture University Osaka599-8531 Japan School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan

Keeping containers warm for prompt service responses and reducing warm containers for light-weight system management exhibit a fundamental tradeoff in serverless computing systems. In this letter, we investigate the problem of container warming control for serverless computing, and we formulate it as a Markov decision process (MDP). By observing that the value functions corresponding to the MDP are partially submodular, we show that the derived optimal policy is hysteretic and partially non-decreasing. Our numerical results show that the derived optimal policy exhibits a hysteretic structure, which can be realized via switching-up/-down thresholds in practice. © 2019 IEEE.

关键词： Hysteresis

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