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Computing Power in the Sky: Digital Twin-assisted Collaborative Computing with Multi-UAV networks

IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Chao Han, Yu Zhang, Long Jia, Ziye Zhang, Hongliang Hong, Choong Seon Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Kyung Hee University Department of Computer Science and Engineering Gyeonggi-do Yongin-si17104 Korea Republic of University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The collaboration of computing powers (CPs) among unmanned aerial vehicles (UAVs)-mounted edge servers is essential to handle data-intensive tasks of user equipments (UEs). This paper presents a multi-UAV computing power network (CPN) that orchestrates the CP resources of edge servers to cooperatively process tasks through collaborative computing. Due to the frequent interactions among edge servers and the increased complexities for large-scale task executions, we propose a digital twin (DT)-driven multi-UAV CPN framework, where the aerial DT network is created as a digital replica of the multi-UAV network to assist collaborative computing. A joint optimization problem of the service association, offloading power control, task partitions, CP allocation, and UAV trajectory design is formulated to minimize the long-term average delay of UEs. We use the Lyapunov technique to tackle the long-term energy constraint, forming a tractable optimization problem, which is modeled as a Markov decision process to balance the UAV's deficit queue stability and the UE's task completion delay. A hybrid soft actor-critic based deep reinforcement learning algorithm is developed to optimize the joint design by sampling the hybrid action from the Gumbel and Gaussian distributions. Simulation results verify that the multi-UAV CPN contributes to significant performance gains when supported by DTs. © 2025 IEEE.

关键词： Markov processes

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Sensing-Communication-Computing-Control Closed-Loop Optimization for 6G Digital Twin-Empowered Unmanned Robotic systems

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IEEE Journal on Selected Areas in Communications 2025年

作者： Fang, Xinran Lei, Chengleyang Feng, Wei Chen, Yunfei Xiao, Ming Ge, Ning Wang, Cheng-Xiang Tsinghua University State Key Laboratory of Space Network and Communications Department of Electronic Engineering Beijing100084 China University of Durham Department of Engineering DurhamDH1 3LE United Kingdom Royal Institute of Technology School of Electrical Engineering and Computer Science Department of Information Science and Engineering Sweden Southeast University National Mobile Communications Research Laboratory School of Information Science and Engineering Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

In recent decades, cyber-physical systems (CPSs) have received great attention due to their broad applications. This paper investigates CPS deployment in remote areas, specifically focusing on a digital twin-empowered unmanned robotic system. The system consists of a multifunctional unmanned aerial vehicle (UAV), sensors, and actuators. The UAV carries communication and computing modules, acting as an edge information hub (EIH) that connects sensors and actuators - forming reflex-arc-like sensing-communication-computing-control (SC3) loops. A digital twin is integrated into the EIH to emulate the system's behavior and assist in the decision-making. To alleviate resource limitations in remote areas, we propose a goal-oriented closed-loop optimization scheme. The proposed scheme takes the SC3 loop as an integrated structure and jointly optimizes uplink and downlink (UL&DL) communication and computing resources to minimize the total linear quadratic regulator (LQR) cost. To address the non-convex optimization problem, we derive the closed-form solution for intra-loop allocation and propose an efficient iterative algorithm for inter-loop optimization. Under the condition of adequate CPU frequency, we derive an approximate closed-form solution for inter-loop bandwidth allocation. Simulation results demonstrate the superiority of the proposed scheme, which achieves a two-tier task-level balance within and across the SC3 loops. © 1983-2012 IEEE.

关键词： Drones

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Hierarchical Recording Architecture for Three-Dimensional Magnetic Recording

arXiv

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arXiv 2025年

作者： Jian, Yugen Luo, Ke Chen, Jincai Fong, Xuanyao Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Computer of Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan430074 China

Three-dimensional magnetic recording (3DMR) is a highly promising approach to achieving ultra-large data storage capacity in hard disk drives. One of the greatest challenges for 3DMR lies in performing sequential and correct writing of bits into the multi-layer recording medium. In this work, we have proposed a hierarchical recording architecture based on layered heat-assisted writing with a multi-head array. The feasibility of the architecture is validated in a dual-layer 3DMR system with FePt-based thin films via micromagnetic simulation. Our results reveal the magnetization reversal mechanism of the grains, ultimately attaining appreciable switching probability and medium signal-to-noise ratio (SNR) for each layer. In particular, an optimal head-to-head distance is identified as the one that maximizes the medium SNR. Optimizing the system’s noise resistance will improve the overall SNR and allow for a smaller optimal head-to-head distance, which can pave the way for scaling 3DMR to more recording layers. Copyright © 2025, The Authors. All rights reserved.

关键词： Hard disk storage

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Harmonic Current Correction for Common Mode Voltage Reduction and Narrow Pulse Elimination Method in DC-AC Matrix Converter

Harmonic Current Correction for Common Mode Voltage Reductio...

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China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Guangcheng Ye Hao Qin Abhishek Kumar Bikash Sah Raj M. Naidoo Yan Deng Research Group for Energy Network Transition (ReGENT) College of Electrical Engineering Zhejiang University Hangzhou China Hochschlue Bonn-Rhein-Sieg & Fraunhofer Institute for Energy Economics and Energy System Technology (IEE) Germany Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The expected functionality of a single-stage isolated AC-DC matrix converter involves meeting the multifunctional deployment requirements of different AC/DC systems. Its design facilitates bidirectional power conversion while ensuring electrical isolation. Conversely, recent methods have greatly magnified the complexity of modulation and control programs, neglecting in-depth analysis of mathematical models. This paper presents a novel strategy of symmetric-SVM (S-SVM) to operate in discontinuous conduction mode (DCM), which improves performance in DC bias, narrow pulse, and common mode voltage. In addition, an in-depth study was conducted on the precise correlation between vector modulation ratio and three-phase sinusoidal current. The proposed method effectively reduces total harmonic distortion (THD) in three-phase currents and achieves efficient bidirectional power transmission.

关键词： Support vector machines Total harmonic distortion Statistical analysis Electromagnetic interference Modulation Switches Harmonic analysis Vectors Matrix converters Voltage control

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Emotion Recognition Empowered Human-computer Interaction with Domain Adaptation network

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IEEE Transactions on Consumer Electronics 2024年

作者： Xu, Xu Fu, Chong Chen, Junxin Northeastern University School of Computer Science and Engineering Shenyang110004 China Dalian University of Technology China The School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Ministry of Education Engineering Research Center of Security Technology of Complex Network System Shenyang110004 China Dalian University of Technology School of Software Dalian116621 China

Multi-modal emotion recognition plays a vital role in the human-computer interaction (HCI) for consumer electronics. Nowadays, many studies have developed multi-modal fusion algorithms for this ***, two challenging issues remain unsolved, i.e., inefficient multi-modal feature fusion and unclear distance in feature *** this end, we develop a novel framework, namely LAFDA-Net, for cross-subject emotion recognition using EEG and eye movement *** is based on low-rank fusion and domain adaptation *** specifically, the multi-modal signals are input into the feature extraction branch in parallel to generate ***, these features are fused by the low-rank fusion branch, reducing complexity and avoiding ***, the fused features are flattened and sent to the classification branch to determine the emotion *** training, these features are input into the domain adaptive branch to bridge the gap between the source domain and target *** benchmark datasets, i.e., SEED, SEED-IV, and SEED-V, are employed for performance *** results demonstrate that the proposed LAFDA-Net is robust, effective, and has advantages over peer methods. © 1975-2011 IEEE.

关键词： Emotion Recognition

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Att-TCN: An Advertising Attribution Method Based on Temporal Convolutional network with Attention Mechanism

Att-TCN: An Advertising Attribution Method Based on Temporal...

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International Conference on computer and Communications (ICCC)

作者： Bowen Xie Yi Sun Zhaowen Lin Baoquan Ma School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China National Engineering Laboratory for Mobile Network Technologies Beijing China National Computer System Engineering Research Institute of China Beijing China National Engineering Laboratory for Industry Control System Information Security Technology Beijing China

Advertising attribution is an effective method to measure the effect of various advertisements in the era of Internet advertising. It enables scientific tracking back and refined operation of advertising by quantitatively evaluating the contribution of different advertising channels to reach the target. It is challenging to predict conversion results based on users' journey data accurately, reflect the impact of ads on user conversions, and appropriately assign attribution values to advertising channels. To achieve the above objectives, we propose an advertising attribution method based on a temporal convolutional network with an attention mechanism (Att-TCN). By mining the hidden information in time and attribution channels using the attention mechanism, our proposed method can improve the accuracy of conversion prediction and thus more rationally assign attribution values across channels. Experimental validation on a real dataset obtained from an operational commercial advertising monitoring company shows that our proposed attribution method has better accuracy than other state-of-the-art attribution methods and gives an open-ended approach to attribution value assignment.

关键词： Target tracking Costs Companies Predictive models Internet Convolutional neural networks Data mining

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Differential Privacy for Class-based Data: A Practical Gaussian Mechanism

arXiv

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arXiv 2023年

作者： Ramakrishna, Raksha Scaglione, Anna Wu, Tong Ravi, Nikhil Peisert, Sean Division of Network and Systems Engineering EECS KTH Royal Institute of Technology Stockholm Sweden The Department of Electrical and Computer Engineering Cornell Tech New York CityNY10044 United States The Computer Sciences Research and Development Department Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

In this paper, we present a notion of differential privacy (DP) for data that comes from different classes. Here, the class-membership is private information that needs to be protected. The proposed method is an output perturbation mechanism that adds noise to the release of query response such that the analyst is unable to infer the underlying class-label. The proposed DP method is capable of not only protecting the privacy of class-based data but also meets quality metrics of accuracy and is computationally efficient and practical. We illustrate the efficacy of the proposed method empirically while outperforming the baseline additive Gaussian noise mechanism. We also examine a real-world application and apply the proposed DP method to the autoregression and moving average (ARMA) forecasting method, protecting the privacy of the underlying data source. Case studies on the real-world advanced metering infrastructure (AMI) measurements of household power consumption validate the excellent performance of the proposed DP method while also satisfying the accuracy of forecasted power consumption measurements. © 2023, CC BY.

关键词： Electric power utilization

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Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles

arXiv

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arXiv 2025年

作者： You, Jiahao Jia, Ziye Dong, Chao Wu, Qihui Han, Zhu The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211106 China National Mobile Communications Research Laboratory Southeast University Jiangsu Nanjing211111 China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible aerial services, and ground stations (GSs) can provide powerful supports, which can cooperate to help the USVs in complex scenarios. However, the collaboration between UAVs and GSs for USVs faces challenges of task uncertainties, USVs trajectory uncertainties, heterogeneities, and limited computational resources. To address these issues, we propose a cooperative UAV and GS based robust multi-access edge computing framework to assist USVs in completing computational tasks. Specifically, we formulate the optimization problem of joint task offloading and UAV trajectory to minimize the total execution time, which is in the form of mixed integer nonlinear programming and NP-hard to tackle. Therefore, we propose the algorithm of generative artificial intelligence-enhanced heterogeneous agent proximal policy optimization (GAI-HAPPO). The proposed algorithm integrates GAI models to enhance the actor network ability to model complex environments and extract high-level features, thereby allowing the algorithm to predict uncertainties and adapt to dynamic conditions. Additionally, GAI stabilizes the critic network, addressing the instability of multi-agent reinforcement learning approaches. Finally, extensive simulations demonstrate that the proposed algorithm outperforms the existing benchmark methods, thus highlighting the potentials in tackling intricate, cross-domain issues in the considered scenarios. © 2025, CC BY.

关键词： Unmanned surface vehicles

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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Congress on Evolutionary Computation

作者： Wenjing Hong Cheng Chen Zexuan Zhu Ke Tang National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design.

关键词： Measurement Design methodology Evolutionary computation Search problems Linear programming Stability analysis Vaccines

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

引用

Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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