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arXiv 2023年

作者： Lai, Bingkun Wen, Jinbo Kang, Jiawen Du, Hongyang Nie, Jiangtian Yi, Changyan Kim, Dong In Xie, Shengli School of Automation Guangdong University of Technology Guangzhou510006 China Laboratory for Smart Discrete Manufacturing Guangzhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China The School of Computer Science and Engineering Nanyang Technological University Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

As the next-generation wireless communication system, Sixth-Generation (6G) technologies are emerging, enabling various mobile edge networks that can revolutionize wireless communication and connectivity. By integrating Generative Artificial Intelligence (GAI) with mobile edge networks, generative mobile edge networks possess immense potential to enhance the intelligence and efficiency of wireless communication networks. In this article, we propose the concept of generative mobile edge networks and overview widely adopted GAI technologies and their applications in mobile edge networks. We then discuss the potential challenges faced by generative mobile edge networks in resource-constrained scenarios. To address these challenges, we develop a universal resource-efficient generative incentive mechanism framework, in which we design resource-efficient methods for network overhead reduction, formulate appropriate incentive mechanisms for the resource allocation problem, and utilize Generative Diffusion Models (GDMs) to find the optimal incentive mechanism solutions. Furthermore, we conduct a case study on resource-constrained mobile edge networks, employing model partition for efficient AI task offloading and proposing a GDM-based Stackelberg model to motivate edge devices to contribute computing resources for mobile edge intelligence. Finally, we propose several open directions that could contribute to the future popularity of generative mobile edge networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion

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Time-Synchronized Safety-Critical Attitude Control for Spacecraft with Hardware-in-Loop Validation

Time-Synchronized Safety-Critical Attitude Control for Space...

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Complex Systems and Intelligent science (CSIS-IAC), International Annual Conference on

作者： Shang Tong Haoyang Yang Rongchuan Zhang Qinglei Hu Shuzhi Sam Ge Dongyu Li Tianmushan Laboratory Hangzhou China School of Cyber Science and Technology Beihang University Beijing China School of Engineering University of Warwick Coventry UK Hangzhou International Innovation Institute Beihang University Hangzhou China School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

A time-synchronized controller is proposed to solve the time-varying constrained reorientation problem. Time-Synchronized Stability (TSS) that considers the interrelationships among different state errors plays an important role in our method, enabling synchronized convergence of individual error components while ensuring compliance with state constraints. Compared to traditional sliding mode controllers, the efficiency of our safety-critical attitude controller is imporoved without adding computational burden, as evidenced by improved control energy consumption and reduced convergence time. A hardware-in-the-loop (HiL) experiment confirms its practical deployment capabilities.

关键词： Space vehicles Energy consumption Attitude control Navigation Computational efficiency Safety Synchronization Complex systems Convergence

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Optimized Admittance Control for Manipulators Interacting with Unknown Environment

Optimized Admittance Control for Manipulators Interacting wi...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Haiyi Kong Guangzhu Peng Guang Li Chenguang Yang Department of Electrical and Electronic Engineering University of Manchester Oxford Rd Manchester UK Bristol Robotics Laboratory University of the West of England Bristol UK School of Automation Nanjing University of Information Science and Technology Nanjing China Department of Computer Science University of Liverpool Liverpool UK

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

This paper considers the study scenario that the end-effector of a manipulator follows a desired trajectory and interacts with external environment. To maximize the interaction performance, admittance control is combined with adaptive dynamic programming (ADP). The optimal admittance parameters can be learned online without prior knowledge of the environment. A data-driven Hybrid Iteration is employed in the ADP, which can relax the initial stabilizing requirement and at the same time has a faster convergence rate compared with Value Iteration. In addition, a more accurate environment model is considered in the system control design, where a general iterative expression is proposed to describe the varying contour of the environment. At last, simulation and experimental studies are given to verify the effectiveness of the proposed method.

关键词： Adaptation models Control design Heuristic algorithms End effectors Dynamic programming Trajectory Iterative methods

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Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach

arXiv

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arXiv 2023年

作者： Huang, Xumin Wu, Yuan Kang, Jiawen Nie, Jiangtian Zhong, Weifeng Kim, Dong In Xie, Shengli School of Automation Guangdong University of Technology Guangzhou510006 China State Key Laboratory of Internet of Things for Smart City University of Macau China Department of Computer and Information Science University of Macau China School of Computer Science and Engineering Nanyang Technological University Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Metaverse enables users to communicate, collaborate and socialize with each other through their digital avatars. Due to the spatio-temporal characteristics, co-located users are served well by performing their software components in a collaborative manner such that a Metaverse service provider (MSP) eliminates redundant data transmission and processing, ultimately reducing the total energy consumption. The energy-efficient service provision is crucial for enabling the green and sustainable Metaverse. In this article, we take an augmented reality (AR) application as an example to achieve this goal. Moreover, we study an economic issue on how the users reserve offloading services from the MSP and how the MSP determines an optimal charging price since each user is rational to decide whether to accept the offloading service by taking into account the monetary cost. A single-leader multi-follower Stackelberg game is formulated between the MSP and users while each user optimizes an offloading probability to minimize the weighted sum of time, energy consumption and monetary cost. Numerical results show that our scheme achieves energy savings and satisfies individual rationality simultaneously compared with the conventional schemes. Finally, we identify and discuss open directions on how several emerging technologies are combined with the sustainable green Metaverse. © 2023, CC BY-NC-SA.

关键词： Energy utilization

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Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective

arXiv

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arXiv 2023年

作者： Chen, Jiayuan Zhang, Xiang Xu, Yinfei Zhao, Tianli Xie, Renjie Xu, Wei School of Computer Science and Engineering Southeast University China School of Information Science and Engineering Southeast University China Institute of Automation Chinese Academy of Sciences China National Mobile Communications Research Laboratory Southeast University China Purple Mountain Laboratories China

Recently, graph-based models designed for downstream tasks have significantly advanced research on graph neural networks (GNNs). GNN baselines based on neural message-passing mechanisms such as GCN and GAT perform worse as the network deepens. Therefore, numerous GNN variants have been proposed to tackle this performance degradation problem, including many deep GNNs. However, a unified framework is still lacking to connect these existing models and interpret their effectiveness at a high level. In this work, we focus on deep GNNs and propose a novel view for understanding them. We establish a theoretical framework via inference on a probabilistic graphical model. Given the fixed point equation (FPE) derived from the variational inference on the Markov random fields, the deep GNNs, including JKNet, GCNII, DGCN, and the classical GNNs, such as GCN, GAT, and APPNP, can be regarded as different approximations of the FPE. Moreover, given this framework, more accurate approximations of FPE are brought, guiding us to design a more powerful GNN: coupling graph neural network (CoGNet). Extensive experiments are carried out on citation networks and natural language processing downstream tasks. The results demonstrate that the CoGNet outperforms the SOTA models. © 2023, CC BY.

关键词： Markov processes

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Privacy-preserving location authentication for low-altitude UAVs:A blockchain-based approach

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Security and Safety 2024年第2期3卷 58-72页

作者： Hengchang Pan Yuanshuo Wang Wei Wang Ping Cao Fangwei Ye Qihui Wu College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Information Fusion Technology(Ministry of Education) School of AutomationNorthwestern Polytechnical UniversityXi'an 710072China College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Efficient and trusted regulation of unmanned aerial vehicles(UAVs)is an essential but challenging issue in the future era of the Internet of Low-altitude Intelligence,due to the difficulties in UAVs'identity recognition and location matching,potential for falsified information reporting,*** address this challenging issue,in this paper,we propose a blockchain-based UAV location authentication scheme,which employs a distance bounding protocol to establish a location proof,ensuring the authenticity of UAV *** preserve the privacy of UAVs,anonymous certificates and zero-knowledge proof are *** security of the proposed scheme is *** demonstrate the efficiency and feasibility of the proposed scheme.

关键词： Blockchain UAV zero-knowledge proof location proof

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Variational Disentangled Graph Auto-Encoders for Link Prediction

arXiv

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arXiv 2023年

作者： Fu, Jun Zhang, Xiaojuan Li, Shuang Chen, Dali The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Computer Science and Technology Beijing Institute of Technology Beijing China The College of Information Science and Engineering Northeastern University Shenyang China

With the explosion of graph-structured data, link prediction has emerged as an increasingly important task. Embedding methods for link prediction utilize neural networks to generate node embeddings, which are subsequently employed to predict links between nodes. However, the existing embedding methods typically take a holistic strategy to learn node embeddings and ignore the entanglement of latent factors. As a result, entangled embeddings fail to effectively capture the underlying information and are vulnerable to irrelevant information, leading to unconvincing and uninterpretable link prediction results. To address these challenges, this paper proposes a novel framework with two variants, the disentangled graph auto-encoder (DGAE) and the variational disentangled graph auto-encoder (VDGAE). Our work provides a pioneering effort to apply the disentanglement strategy to link prediction. The proposed framework infers the latent factors that cause edges in the graph and disentangles the representation into multiple channels corresponding to unique latent factors, which contributes to improving the performance of link prediction. To further encourage the embeddings to capture mutually exclusive latent factors, we introduce mutual information regularization to enhance the independence among different channels. Extensive experiments on various real-world benchmarks demonstrate that our proposed methods achieve state-of-the-art results compared to a variety of strong baselines on link prediction tasks. Qualitative analysis on the synthetic dataset also illustrates that the proposed methods can capture distinct latent factors that cause links, providing empirical evidence that our models are able to explain the results of link prediction to some extent. All code will be made publicly available upon publication of the paper. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Discrete-time Formation Control With Attitude Alignment: A Geometric Approach under Ergodic Products

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IEEE Transactions on Control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

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Multi-Domains Personalized Local Differential Privacy Frequency Estimation Mechanism for Utility Optimization

SSRN

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SSRN 2024年

作者： Li, Yunfei Fu, Xiaodong Liu, Li Ding, Jiaman Peng, Wei Jia, Lianyin Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Graduate School Yunnan University of Finance and Economics Kunming650221 China Yunnan Provincial Key Laboratory of Computer Technology Application Kunming University of Science and Technology Kunming650500 China

Local Differential Privacy (LDP) has garnered considerable attention in recent years because it does not rely on trusted third parties and has low interactivity and high operational efficiency. However, current LDP frequency estimation mechanisms aggregate data using different privacy budgets within the same data domain, overlooking the aggregation requirements across different data domains. This limits the potential for enhancing the data utility under fixed privacy budgets and meeting user preferences in multiple data domains and privacy budgets. To address this issue, we define a Multi-Domains Personalized Local Differential Privacy (MDPLDP) model that allows users to freely choose data domains and privacy budgets according to their privacy preferences. Furthermore, based on the MDPLDP model, two new frequency estimation mechanisms are proposed: MDPLDP-Generalized Randomized Response and MDPLDP-basic Randomized Aggregatable Privacy-Preserving Ordinal Response. These mechanisms support cross-domains data aggregation and optimize data utility by adjusting the data domains and increasing privacy budgets. Theoretical analysis reveals that these new mechanisms have lower estimation errors than the traditional LDP mechanisms. Experiments on real and synthetic datasets demonstrate that the proposed mechanisms effectively reduce estimation errors and enhance the utility of data-frequency estimation. © 2024, The Authors. All rights reserved.

关键词： Frequency estimation

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LQG Control Over SWIPT-enabled Wireless Communication Network

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IFAC-PapersOnLine 2023年第2期56卷 3824-3829页

作者： Huiwen Yang Lingying Huang Yuzhe Li Subhrakanti Dey Ling Shi Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Electrical and Electronic Engineering Nanyang Technological University Singapore State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110004 China Department of Electrical Engineering Uppsala University Uppsala Sweden

In this paper, we consider using simultaneous wireless information and power transfer (SWIPT) to recharge the sensor in the LQG control, which provides a new approach to prolonging the network lifetime. We analyze the stability of the proposed system model and show that there exist two critical values for the power splitting ratio α. Then, we propose an optimization problem to derive the optimal value of α. This problem is non-convex but its numerical solution can be derived by our proposed algorithm efficiently. Moreover, we provide the feasible condition of the proposed optimization problem. Finally, simulation results are presented to verify and illustrate the main theoretical results.

关键词： Networked control systems SWIPT packet drop stability

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