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arXiv 2025年

作者： Jia, Ziye Cao, Yilu He, Lijun Li, Guangxia Zhou, Fuhui Wu, Qihui Han, Zhu College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China State Key Laboratory of ISN Xidian University Xian710071 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 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

To achieve ubiquitous connectivity of the sixth generation communication, the space-air-ground integrated network (SAGIN) is a popular topic. However, the dynamic nodes in SAGIN such as satellites and unmanned aerial vehicles, may be fragile and out of operation, which can potentially cause service failure. Therefore, the research on service recovery in SAGIN under situations of resource failure is critical. In order to facilitate the flexible resource utilization of SAGIN, the network function virtualization technology (NFV) is proposed to be employed. Firstly, the task management is transformed into the deployment of service function chains (SFCs). Then, we design an NFV-based SFC recovery model in SAGIN in the face of resource failure, so that tasks can quickly select alternative resources to complete deployments. Moreover, the problem of SFC recovery is formulated to minimize the total time consumption for all completed SFCs. Since it is an NP-hard integer linear programming problem, we propose the efficient recovery algorithm based on the matching game. Finally, via various simulations, the effectiveness of the proposed algorithm and its advantages are verified, where the total time consumption is optimized by about 25%, compared with other benchmark methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Network function virtualization

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Model Reference Adaptive Stabilizing control for Leader-following Consensus

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IEEE Transactions on Automatic control 2025年

作者： Yue, Dongdong Shi, Jiantao Shi, Ling Frasca, Paolo Baldi, Simone Nanjing Tech University College of Electrical Engineering and Control Science Nanjing211816 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay China Univ. Grenoble Alpes Cnrs Inria Grenoble Inp GIPSALab Grenoble38000 France Southeast University School of Mathematics Nanjing210096 China

Complex networks, neuroscience, and other applications have shown examples of multi-agent adaptive systems that must follow (over possibly short times) reference dynamics that are neither Hurwitz nor neutrally stable. However, such leader-following behavior would be impossible with existing adaptive consensus methods, e.g., based on model reference adaptive control (MRAC), since the stability of the reference dynamics is required. To fill this gap, we propose a novel model reference adaptive stabilizing control (MRASC) framework for leader-following consensus of multi-agent systems with unknown and heterogeneous dynamics. Differently from several approaches in the leader-following consensus literature, the proposed framework is free of any extra distributed observer layer for the leader's signal, as the reconstruction of such signals is intrinsic in the adaptive laws. Besides, the framework does not require Hurwitz or neutral stability of the leader and generalizes existing acyclic requirements on the communication graph among the follower. Starting from any weakly connected communication digraph, the proposed method allows to derive a lower bound, useful from the network design point of view, for the minimum number of followers that should be pinned by the leader. © 2025 IEEE.

关键词： Multi agent systems

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Publishing Social Graphs with Differential Privacy Guarantees Based on wPINQ

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Chinese Journal of Electronics 2019年第2期28卷 273-279页

作者： LI Xiaoye YANG Jing SUN Zhenlong ZHANG Jianpei College of Computer Science and Technology Harbin Engineering University College of Computer and Control Enginewaeering Qiqihar University

To publish social graphs with differential privacy guarantees for reproducing valuable results of scientific researches, we study a workflow for graph synthesis and propose an improved approach based on weighted Privacy integrated query(wPINQ). The workflow starts with a seed graph to fit the noisy degree sequence, which essentially is the 1K-graph. In view of the inaccurate assortativity coefficient, we truncate the workflow to replace the seed graph with an optimal one by doing target 1K-rewiring while preserving the 1K-distribution. Subsequently, Markov chain Monte Carlo employs the new seed graph as the initial state, and proceeds step by step guided by the information of Triangles by intersect to increase the number of triangles in the synthetic graphs. The experimental results show that the proposed algorithm achieves better performance for the published social graphs.

关键词： Differential privacy Social networks weighted Privacy integrated query(wPINQ) dK-graph model

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Heterogeneous Graph Distillation for Stance Prediction

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Expert Systems 2025年第6期42卷

作者： Lu, Yibing Sun, Jingyun Li, Yang College of Computer and Control Engineering Northeast Forestry University Harbin China

Stance prediction is a critical task in public opinion analysis, aiming to identify users' viewpoints on specific events. Existing research often relies on user interactions for stance inference but generally underutilizes multi-source heterogeneous information such as user entities, opinion text, issues and topics. To address this limitation, this study proposes a stance prediction approach based on heterogeneous entity modeling. By integrating four types of heterogeneous entities to capture similarity in users' participation in issues, the proposed method improves stance inference accuracy. Specifically, we design a heterogeneous graph knowledge extraction framework that fully incorporates both content features and structural semantic information of various entities. First, we construct a heterogeneous information network to capture different types of social media entities and their interactions, learning rich feature representations in the process. Next, we employ matrix factorization to assess users' preferences toward specific issues. Finally, by introducing a knowledge distillation mechanism, the approach significantly enhances prediction accuracy with only a modest increase in computational cost. Experimental results on public datasets demonstrate that our method outperforms existing baselines, verifying its effectiveness. © 2025 John Wiley & Sons Ltd.

关键词： Matrix factorization

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Unleashing the Potentials of IoT with Focus on Energy and Path Loss for Internet of Medical Things

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Journal of Circuits, Systems and computers 2025年

作者： Hussain, Altaf Li, Shuaiyong Attar, Razaz Waheeb Al Dabel, Maryam M. Bashir, Ali Kashif Alhomoud, Ahmed Hussain, Tariq School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Management Department College of Business Administration Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer Science and Engineering College of Computer Science and Engineering University of Hafr Al Batin Saudi Arabia Department of Computing and Mathematics Manchester Metropolitan University United Kingdom Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Computer Science College of Science Northern Border University Arar91431 Saudi Arabia School of Computer Science and Technology Zhejiang Gongshang University Hangzhou310018 China

The Internet of Things (IoT) encompasses a broad platform of sensor networks incorporating independent wireless networks. With advancements in sensor technology and IoT-enabled networks, their applications in the medical field have led to the development of the Internet of Medical Things (IoMT). In IoMT, sensor nodes monitor and evaluate patient conditions such as heartbeat, blood sugar levels, blood pressure and temperature, and can also remotely track patient activities through remote analysis. These IoMT systems utilize tiny sensors with limited communication ranges to gather essential patient information. Wireless devices are equipped with a short range and need a direct communication path. However, transmitting data from the source node to the destination node ultimately results in energy consumption and path loss. Path loss models and energy consumption models are essential to address these issues. In this paper, we propose a novel routing protocol named Energy Efficient and Path Loss Preserving (EEPLP) for IoMT. The EEPLP protocol focuses on energy efficiency and path loss preservation based on the relay approach. Two models are being proposed, one for path loss and the other for energy consumption. Finally, both models are merged since the major contribution is to avoid path loss and enhance the protocol's energy efficiency. The EEPLP evaluates the state-of-the-art existing approaches of IoMT. The protocol is evaluated by simulating conditions and compared with other similar routing protocols already deployed in the IoMT;it has been observed that the EEPLP scheme has the potential to be maneuvered in IoMT structures with core targets of energy efficiency as well as path loss preservation techniques. © 2025 World Scientific Publishing Company.

关键词： Sensor nodes

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A direct predictive DC-link voltage control with warm-starting iterative approach for three-level NPC BTB converter fed PMSG-based wind turbine systems

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Expert Systems with Applications 2025年 283卷

作者： Ganesh, Mayilsamy Jeong, Jae Hoon Research Center for Wind Energy systems School of IT Information and Control Engineering Kunsan National University 588 Daehak-ro Gunsan-si Jeonbuk54150 Korea Republic of College of Computer and Software Kunsan National University 588 Daehak-ro Gunsan-si Jeonbuk54150 Korea Republic of

This article presents a direct predictive DC-link voltage control (DPVC) scheme for a three-level (3L) neutral point clamped (NPC) back-to-back (BTB) converter fed permanent magnet synchronous generator (PMSG)-based wind turbine system (WTS). The conventional 3L NPC BTB converter employs an external PI controller to regulate the DC-link voltage at the set point by generating power or current references for the cascaded finite control set (FCS) predictive control. The presented strategy incorporates the DC-link voltage regulation term into the power regulation term in the grid-side converter (GSC) cost function, identifying the optimum switching state that directly regulates the DC-link voltage at the set point. Through this, the required active power is transferred to the grid to maintain power balance, and the conventional cascaded control structure is eliminated. In addition, a warm-starting iterative approach (WSIA) is introduced to derive the switching states employed for each switching instant. This reduces computation in both the GSC and machine-side converter (MSC) control and inherently incorporates switching frequency optimization. The presented scheme is validated in 3 MW rated WTS simulations under various operating conditions, with comparative studies performed to demonstrate its significance. © 2025 Elsevier Ltd

关键词： Predictive control systems

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TS-CGNet: Temporal-Spatial Fusion Meets Centerline-Guided Diffusion for BEV Mapping

arXiv

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arXiv 2025年

作者： Hong, Xinying Li, Siyu Zeng, Kang Shi, Hao Peng, Bomin Yang, Kailun Li, Zhiyong The College of Computer Science and Electronic Engineering Hunan University Changsha410082 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China The State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China

Bird’s Eye View (BEV) perception technology is crucial for autonomous driving, as it generates top-down 2D maps for environment perception, navigation, and decision-making. Nevertheless, the majority of current BEV map generation studies focusing on visual map generation lack depth-aware reasoning capabilities. They exhibit limited efficacy in managing occlusions and handling complex environments, with a notable decline in perceptual performance under adverse weather conditions or low-light scenarios. Therefore, this paper proposes TS-CGNet, which leverages Temporal-Spatial fusion with Centerline-Guided diffusion. This visual framework, grounded in prior knowledge, is designed for integration into any existing network for building BEV maps. Specifically, this framework is decoupled into three parts: Local mapping system involves the initial generation of semantic maps using purely visual information;The Temporal-Spatial Aligner Module (TSAM) integrates historical information into mapping generation by applying transformation matrices;The Centerline-Guided Diffusion Model (CGDM) is a prediction module based on the diffusion model. CGDM incorporates centerline information through spatial-attention mechanisms to enhance semantic segmentation reconstruction. We construct BEV semantic segmentation maps by our methods on the public nuScenes and the robustness benchmarks under various corruptions. Our method improves 1.90%, 1.73%, and 2.87% for perceived ranges of 60×30m, 120×60m, and 240×60m in the task of BEV HD mapping. TS-CGNet attains an improvement of 1.92% for perceived ranges of 100×100m in the task of BEV semantic mapping. Moreover, TS-CGNet achieves an average improvement of 2.92% in detection accuracy under varying weather conditions and sensor interferences in the perception range of 240×60m. The source code will be publicly available at https://***/krabs-H/TS-CGNet. Copyright © 2025, The Authors. All rights reserved.

关键词： Decision making

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Stability Analysis of Connected Vehicle Platoons with Markovian Packet Losses

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IEEE Internet of Things Journal 2025年

作者： Wu, Yilin Zhao, Xiaoyan Shen, Zhiping Liu, Yonggui Li, Zeming Guangdong University of Education School of Computer Science Guangzhou510310 China Henan Normal University School of Mathematics and Statistics Xinxiang453007 China South China University of Technology Key Laboratory of Autonomous Systems and Network Control Ministry of Education The College of Automatic Science and Engineering Guangzhou510640 China

This article focuses on discussing the effects of inter-vehicular communication on the performance of platoon control. Different from the existing results established under a critical assumption that the fading channels are independent, this paper models the inter-vehicular communication as Markovian packet loss channel which can capture the temporal interdependencies of packet losses. Our aim is to decide whether there exists a distributed controller such that the underlying vehicle platoon can achieve mean square stability (MSS) over Markovian packet loss channels. First, for the scenario with identical Markovian packet losses, we begin by deriving a necessary and sufficient condition for the platoon MSS, which is established by utilizing the stability principles of Markov jump linear systems. Additionally, we propose a numerically verifiable criterion for MSS, which can be validated through the feasibility of linear matrix inequalities (LMIs). Furthermore, based on the modified Riccati inequality (MRI), we provide an analytical sufficient condition that ensures MSS for vehicle platoons. This condition is expressed in terms of the information flow topology (IFT) and the statistical parameters of Markov channels. Second, for the case with nonidentical packet dropouts, we introduce a Markovian loss channel based switching (MLCBS) model. Building upon this model, we further propose a sufficient conditon related to IFT and the transition probability matrix, and a distributed controller that is not only easy to implement but also enables the achievement of MSS for vehicle platoons with nonidentical packet dropouts. Ultimately, numerical experiments are performed to validate the obtained outcomes. © 2014 IEEE.

关键词： Intelligent Transportation Systems Resource-Constrained Networks Vehicular Networks

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Decoupling While Coupling: Towards More Accurate Stereo Image Sand Removal Beyond Certainty

Decoupling While Coupling: Towards More Accurate Stereo Imag...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Bingcai Wei Hui Liu Chuang Qian Yi Jia Wangyu Wu Zhishan Li School of Computer Science Wuhan University Wuhan China GNSS Research Center Wuhan Unicersity Wuhan China Intelligent Transport Systems Research Center Wuhan University of Technology Wuhan China College of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China University of Liverpool Liverpool UK School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Stereo image sand removal is crucial to improve the perceptual quality for autonomous driving perception. Existing methods often fall short in accurately estimating the uncertainty inherent in degraded images, leading to suboptimal outcomes. To address this, we introduce a novel framework named Decoupling While Coupling(DWC). DWC pioneers the integration of inter-view uncertainty estimation, cross-view uncertainty-aware interaction and block-wise uncertainty representation for superior stereo image sand removal. For cross-view information interaction, we propose an Uncertainty-aware Cross-view Attentive Interaction module(UCAI) to cope with the lack of uncertainty estimation ability in the existing cross-view information interaction mechanism. For the uncertainty perception and information interaction within the inter-view, we propose a Distribution Modeling Coupling Block(DMCB), which transmits the representation of uncertainty between each backbone module. For block-wise uncertainty estimation, we use our proposed Uncertainty-aware Distribution Feature Modulator(UDFM) as the backbone of DWC to modulate the uncertainty inside the neural network itself. Extensive experimental validations on our proposed stereo image sand removal dataset SandST confirm the efficacy of DWC. Our method not only achieves higher PSNR and SSIM, but also exhibits enhanced robustness against various sand degrees and patterns.

关键词： Couplings Uncertainty Neural networks Estimation Signal processing Robustness Stereo vision Image restoration Speech processing Autonomous vehicles

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