检索结果-内蒙古大学图书馆

communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity

IEEE Transactions on Cognitive communications and Networking 2025年

作者： Tian, Zhuojun Zhang, Zhaoyang Li, Yiwei Bennis, Mehdi Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Oulu Center for Wireless Communications Oulu90014 Finland State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multimodal Communication Networks and Intelligent Information Processing Hangzhou310027 China Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China

To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a communication-efficient personalized learning algorithm is developed. In the proposed method, each local model is represented as the ‌Hadamard product of global real-valued parameters and a personalized binary mask for pruning. The local model is learned by updating and fusing the personalized binary masks while the real-valued parameters are fixed among different agents. To further reduce the complexity of hardware implementation, we incorporate a group sparse regularization term in the loss function, enabling the learned local model to achieve structured sparsity. Then, a binary mask aggregation algorithm is designed by introducing an intermediate aggregation tensor and adding a personalized fine-tuning step in each iteration, which constrains model updates towards the local data distribution. The proposed method effectively leverages the relativity among agents while meeting personalized requirements in heterogeneous node conditions. We also provide a theoretical proof for the DSLTH, establishing it as the foundation of the proposed method. Numerical simulations confirm the validity of the DSLTH and demonstrate the effectiveness of the proposed algorithm. © 2015 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

A Data Association Method Based on Azimuth Inverse Cotangent Value

A Data Association Method Based on Azimuth Inverse Cotangent...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Nan Zou Muze Yin Guangpu Zhang Zhenqi Yang Pengbo Ma Dongyu Li National Key Laboratory of Underwater Acoustic Technology Harbin Engineering University Harbin China Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University) Ministry of Industry and Information Technology Harbin China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

In this paper, we address the challenge of data association in scenarios involving multiple observers for underwater non-cooperative localization, where it is unclear how measurement data from different stations corresponds to the same target. We propose a novel data association method that leverages the inverse cotangent of azimuthal sequence features. The method first calculates the sequence of cotangent values measured by each station's bearing in a limited time. Linearly analyzes the sequence to obtain the slope, and finally realizes the data association according to the characteristic that the inverse cotangent value of the slope corresponds to the target's motion heading. The simulation results show that the proposed method has better association localization ability compared with the traditional method, overcomes the problem of the conventional method that the computational volume is too large when the number of observation stations and targets is large, and ensures the association correctness under a certain error.

关键词： Location awareness Power engineering Accuracy Azimuth Simulation Noise Observers Time measurement

来源：评论

学校读者我要写书评

暂无评论

Prediction of Distributed Photovoltaic Accommodation Capability Based on Ridge Regression 9th

Prediction of Distributed Photovoltaic Accommodation Capabil...

引用

9th Purple Mountain Form on Smart Grid Protection and control, PMF 2024

作者： Ji, Xingquan Zhang, Bowen Zhang, Yumin Sun, Pengkai Zhang, Xiaofeng Liu, Wei dong Shandong University of Science and Technology Qingdao266590 China Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250061 China Information and Communication Company State Grid Shandong Electric Power Company Jinan250013 China Qingdao Yihe Electric Group Co. Ltd. Qingdao266510 China

ISBN: (纸本)9789819616701

A prediction method of distributed photovoltaic accommodation capability is proposed based on ridge regression. First, the factors influencing the distributed photovoltaic accommodation capacity are analyzed, and the concept of the contribution degree of distributed photovoltaic accommodation is introduced. The gray relation analysis method is used to evaluate the correlation between different factors and distributed photovoltaic accommodation, and a model of factors affecting distributed photovoltaic accommodation is constructed. Then, a prediction model of distributed photovoltaic accommodation capability is established based on ridge regression. The factors with high photovoltaic accommodation contribution degrees are incorporated in the prediction model. The mapping relationship between the driving factors of distributed photovoltaic accommodation and the prediction model is derived, then the development strategies for future photovoltaic accommodation capacity are formulated. Finally, simulation is performed on the SPSSPRO platform, and the results show that the proposed method can predict the distributed photovoltaic accommodation capability accurately and provide strategic suggestions for improving future photovoltaic accommodation capacity. © State Grid Electric Power 2025.

关键词： Photovoltaics

来源：评论

学校读者我要写书评

暂无评论

Multi-channel transmission meta-holograms enabled by a single-layer complex-amplitude metasurface

引用

Optics Letters 2025年第8期50卷 2542-2545页

作者： Zhu, Lei Wang, Yiya Dong, Liang Shang, Guanyu Burokur, Shah Nawaz Ding, Xumin School of Computer and Control Engineering Qiqihar University Qiqihar161006 China Communication and Electronics Engineering Institute Qiqihar University Qiqihar161006 China Key Laboratory of Big Data Network Security Detection and Analysis in Heilongjiang Qiqihar University Qiqihar161006 China Innovation Photonics and Imaging Center Instrumentation Science and Engineering Harbin Institute of Technology Harbin150001 China LEME UPL Univ. Paris Nanterre Ville d'AvrayF92410 France Advanced Microscopy and Instrumentation Research Center Harbin Institute of Technology Harbin150080 China

With an increasing demand for wireless communications, it is difficult for traditional communication technologies to achieve high-quality multi-channel wireless transmissions. Complex-amplitude metasurfaces provide an effective method to deal with this issue by jointly controlling the amplitude and phase of electromagnetic (EM) waves. However, the limitations of single-layer transmission efficiency and amplitude-phase coupling make it challenging to achieve multi-channel high-quality transmission and system integration. Here, a single-layer complex-amplitude metasurface design strategy for multi-channel high-quality transmission is proposed. The amplitude and phase of each transmission channel can be concurrently controlled by adjusting the structural parameters and rotation angles of the resonators. The metasurface successfully reconstructs different holograms in five transmission channels. All experimental results align well with the calculated and simulated results, demonstrating an innovative solution for multi-channel high-quality information transmission, with significant potential applications in the fields of wireless communications. © 2025 Optica Publishing Group.

关键词： Holograms

来源：评论

学校读者我要写书评

暂无评论

Domain Adaptation-based Radio Frequency Fingerprint Identification for Industrial Cyber-Physical Systems

引用

IEEE Network 2025年

作者： Wang, Yatong Cao, Bin Wen, Zhongyi Yan, Mu Song, Changqing Beijing Institute of Technology School of Information and Electronics Beijing100081 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100191 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100191 China

With the widespread adoption of cloud and fog platforms, security issues facing Industrial Cyber-Physical Systems (ICPSs) are increasingly prominent. Radio Frequency Fingerprinting (RFFI) emerges as a promising physical layer security technique for user authentication, effectively enhancing ICPS security over wireless networks by exploiting inherenthardware imperfections in transmitters. However, as technologies evolve and user environments become denser and more complex, existing RFFI techniques encounter significant domain shift challenges, leading to performance degradation. Therefore, developing domain-adaptive RFFI techniques is crucial for the effectiveness of ICPSs. In this article, we first provide a comprehensive review of the RFFI framework, emphasizing its applications in ICPSs and the key processes involved. Next, we focus on the domain shift issues faced by RFFI in ICPSs and present a comprehensive survey of domain adaptation methods. To tackle these challenges, we propose a novel feature-alignment based domain adaptation (FADA) framework for RFFI, which is designed to mitigate the performance degradation caused bycross-domain shifts by aligning the feature representations of the source and target domain. Finally, we discuss the inherent challenges and future directions for developing domain adaptation based RFFI to enhance the security of ICPSs. © 2025 IEEE. All rights reserved.

关键词： Radio frequency identification (RFID)

来源：评论

学校读者我要写书评

暂无评论

Cognitive Jammer Time Resource Scheduling With Imperfect information Via Fuzzy Q-Learning

引用

IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Gan, Linchuan Xiong, Kui Liao, Maosen Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China UESTC Shenzhen Institute for Advanced Study Shenzhen518038 China

Effective strategy generation of the jammer with inaccurate or undetermined information for combating the radar system is a challenging problem and the relevant research is scarce in existing work. This paper aims at exploring this promising topic and proposing a transmitting time slots scheduling strategy generation method for the cognitive jammer with imperfect time-matching information based on fuzzy reinforcement learning. First, the interaction between the jammer and environment is modeled as a Markov decision process (MDP) with uncertain state and continuous action, in which the goal of the jammer in interaction is to maximize accumulated discount pulse transmitting time slot jamming probability. Then, the uncertain pulse repeat intervals (PRIs) of the radar signal is inferred using the fuzzy inference system (FIS), where the inferred reward is evaluated by the correntropy of the inferred radar PRI and the previously measured one, thus presenting the fuzzy Q-learning based time scheduling (TSFQL) algorithm. Finally, numerical simulations in typical scenarios are performed to illustrate the effectiveness and superiority of the TSFQL algorithm over conventional methods. © 1965-2011 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Scloud+: An Efficient LWE-Based KEM Without Ring/Module Structure 9th

Scloud+: An Efficient LWE-Based KEM Without Ring/Module Stru...

引用

9th International Conference on security Standardisation Research, SSR 2024

作者： Wang, Anyu Zheng, Zhongxiang Zhao, Chunhuan Qiu, Zhiyuan Zeng, Guang Yuan, Ye Mu, Changchun Wang, Xiaoyun Institute for Advanced Study BNRist Tsinghua University Beijing China School of Computer and Cyber Sciences Communication University of China Beijing China Shield Lab Huawei Technologies Beijing China Shandong Institute of Blockchain Jinan China Digital Currency Institute the People’s Bank of China China Zhongguancun Laboratory Beijing China National Financial Cryptography Research Center Beijing China Key Laboratory of Cryptologic Technology and Information Security School of Cyber Science and Technology Shandong University Qingdao China

ISBN: (纸本)9783031875403

We present Scloud+, an LWE-based key encapsulation mechanism (KEM). The key feature of Scloud+ is its use of the unstructured-LWE problem (i.e., without algebraic structures such as rings or modules) and its incorporation of ternary secrets and lattice coding to enhance performance. A notable advantage of the unstructured-LWE problem is its resistance to potential attacks exploiting algebraic structures, making it a conservative choice for constructing high-security schemes. However, a key disadvantage of such schemes is their limited computational and communication efficiency. Scloud+ utilizes ternary secrets and BW32 lattice codes to enhance noise control and ensure robust error correction during decryption, enabling smaller parameters while maintaining low decryption failure probabilities. Equipped with these techniques, Scloud+ exhibits a significant improvement in efficiency. When compared with FrodoKEM for parameter sets targeting 128, 192, and 256 bits of security respectively, Scloud+ achieves practical performance with a public key size approximately 0.71∼0.87x and a ciphertext size approximately 0.56∼0.78x that of FrodoKEM. The encapsulation plus decapsulation time is approximately 0.74∼0.84x that of FrodoKEM. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

DEEPCON: Improving Distributed Deep Learning Model Consistency in Edge-Cloud Environments via Distillation

引用

IEEE Transactions on Cognitive communications and Networking 2025年

作者： Qian, Bin Qian, Jiaxu Wen, Zhenyu Wu, Di He, Shibo Chen, Jiming Ranjan, Rajiv Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou China University of St Andrews School of Computer Science United Kingdom Newcastle University United Kingdom

In a typical distributed Deep Learning (DL) based application, models are configured differently to meet the requirements of resource constraints. For instance, a large ResNet56 model is deployed on the cloud server while a small lightweight MobileNet model is more suitable for the end-user device with fewer computation resources. However, the heterogeneity of the model architectures and configurations may bring a systemic problem -models may produce different outputs when given the same input. This inconsistency problem may cause severe system failure of prediction agreement inside the application. Current research has not studied the systemic design for efficiently detecting and reducing the inconsistency among models in distributed DL applications. With the increasing scale of distributed DL applications, the challenges of inconsistency mitigation should consider both algorithm and system design. To this end, we design and implement DEEPCON, an adaptive deployment system across the edge-cloud layer with over-the-air model updates. We implement ASRS sampling for efficiently sampling data to reveal the real data distribution as well as model prediction inconsistency. Then, we implement DMML-Par, an asynchronous parallel training algorithm for quickly updating the models and reducing inconsistency. implements over-the-air updates with a set of APIS to enable seamless inconsistency detection and reduction in such deep learning applications. Our experiment results on both vision and language tasks demonstrate that DMML could improve the model consistency up to 4%, 7%, and 13% at CIFAR10/100 and IMDB datasets without sacrificing the accuracy of individual models. We also show that the ASRS sampling can save 90% network bandwidth of data transmission and that DMML-Par is up to 60% faster compared to simple synchronous parallel training. 2015 IEEE.

关键词： Distributed cloud

来源：评论

学校读者我要写书评

暂无评论

Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning

引用

IEEE Transactions on Automation science and Engineering 2025年

作者： Betalo, Mesfin Leranso Leng, Supeng Seid, Abegaz Mohammed Abishu, Hayla Nahom Erbad, Aiman Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, and providing computing services and power to sensor nodes (SNs). UAVs offer significant advantages, including exceptional mobility, cost-effective deployment, and the ability to be easily reprogrammed for a wide range of missions. However, the limited onboard power capacity of UAVs, coupled with the lack of dynamic and intelligent charging station (CS) management and inefficient path planning, can lead to SN failure in dynamic mobile environments. To address these challenges, we propose an energy-efficient laser-charged UAV (LCU)-enabled RWSN environment, wherein UAVs, powered by laser beams from ground-based stations, provide services, collect data, and transfer energy to SNs. We formulate a joint optimization problem involving power allocation, dynamic charging strategy (DCS), and path planning to minimize task completion time and sensor node death time. Given the NP-hard nature of the problem, we employ a stochastic game model based on a Markov decision process (MDP) for its solution. To solve this problem, we propose a deep reinforcement learning (DRL) based algorithm that enables real-time charging scheduling decisions while optimizing network performance. We introduce a multi-agent double deep Q-network (MA-DDQN) model to determine the optimal trajectories for all UAVs in large and complex environments. Simulation results demonstrate that the MA-DDQN approach outperforms state-of-the-art techniques, showing significant improvements in terms of average delay, energy consumption, and task completion time. © 2004-2012 IEEE.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

UAV-NIDD: A Dynamic Dataset for Cybersecurity and Intrusion Detection in UAV Networks

引用

IEEE Transactions on Network science and Engineering 2025年

作者： Hadi, Hassan Jalil Cao, Yue Khan, Muhammad Khurram Ahmad, Naveed Hu, Yulin Fu, Chao Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430073 China King Saud University Center of Excellence in Information Assurance Riyadh Saudi Arabia Prince Sultan University College of Computer and Information Science Riyadh Saudi Arabia Wuhan University School of Electronic Information China Information and Communication Technology Co. LtdChina China

Unmanned Aerial Vehicles (UAVs) are necessary for numerous tasks but are vulnerable to cyber threats due to their widespread use and connectivity. The lack of a comprehensive dataset necessitates the development of effective detection and mitigation solutions. Our work introduces UAV-NIDD, a new dataset that addresses the gaps in understanding and countering both cyber and physical threats in UAV networks. It includes three distinct attack scenarios: compromised UAV initiating a network-wide attack, access point compromised network-wide intrusion, and compromised Ground control Station (GCS) establishing a network-wide attack. We develop a real-time testbed for creating UAV-NIDD (Unmanned Aerial Vehicles-Network Intrusion Detection Dataset), incorporating UAV devices, data collection tools, and controllers. Our testbed facilitates cyberattack execution and data gathering under normal and attack conditions. Our dataset covers various cyber-attacks like Scanning, Reconnaissance, DoS, DDoS, GPS Jamming & Spoofing, MITM, Replay, Evil Twin, Brute-Force, and Fake Landing packet attacks. Additionally, UAV-NIDD presents a valuable resource for AI and ML solutions, strengthening UAV networks against evolving cyber threats. Moreover, we offer open access and cooperative innovation in terms of long-term updating of dataset. © 2013 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：