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OSSR: Online Scalable Scheduling and Routing for Industrial Time-Sensitive Networking

IEEE Transactions on Network Science and engineering 2025年第3期12卷 1761-1775页

作者： Xu, Lei Xu, Qimin Zhang, Yanzhou Wang, Shouliang Chen, Cailian Guan, Xinping Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai200240 China Shanghai Jiao Tong University School of Electronics Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University SJTU-Paris Elite Institute of Technology Shanghai200240 China

As the promising deterministic networking technology of Industrial Internet of Things (IIoT), Time-Sensitive Networking (TSN) has been widely investigated in recent years. Most existing research focuses on offline scheduling and routing for TSN, which is time-consuming and thus unsuitable for dynamic stream demands. To tackle this problem, an online scalable scheduling and routing (OSSR) scheme is proposed for TSN in this paper. A novel slot occupancy representation (SOR) model is established based on divisibility theory to transform the clique-based to a three-level tree-based mode in complex IIoT scenarios. This transformation reduces the computational complexity of maximum slot occupancy judgment from exponential to linear complexity. Based on the above SOR model, a load balance metric for stream scheduling is constructed to guide the optimal routing. Assessed by this metric, an online decoupled routing and scheduling algorithm is proposed to minimize the maximum slot occupancy of all links while guaranteeing high scalability. Evaluation results show that the proposed OSSR scheme outperforms the existing approaches with better adaption to dynamics and lower slot occupancy of links. © 2013 IEEE.

关键词： Scheduling algorithms

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Enabling Intelligent Connectivity: A Survey of Secure ISAC in 6G Networks

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IEEE Communications Surveys and Tutorials 2025年第2期27卷 748-781页

作者： Zhu, Xiaoqiang Liu, Jiqiang Lu, Lingyun Zhang, Tao Qiu, Tie Wang, Chunpeng Liu, Yuan Beijing Jiaotong University School of Software Engineering Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing100044 China Tianjin University College of Intelligence and Computing Tianjin300350 China Qilu University of Technology School of Cyber Security and the Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250353 China

The rapid growth of intelligent sensing capabilities and super computation power in 6G mobile communication systems has facilitated their application in diverse domains such as smart health, smart factories, and the industrial Internet of Things. Integrated Sensing and Communication (ISAC), as a core technology, has merged with artificial intelligence (AI) to enable intelligent connectivity, leading to a paradigm shift in traditional communication modes. This paper presents a visionary design for an ISAC-oriented unified IoT architecture that integrates software-defined communication and super-intelligent agents. By leveraging dynamic adaptability, self-learning, and optimization, the ISAC system can intelligently and flexibly respond to evolving requirements and environments. The architecture is redefined into three layers: the hardware layer, the omniscient layer, and the application layer. Furthermore, a retrospective survey of ISAC technology development over the past decade is conducted, highlighting new design principles for AI-empowered networks and multi-modals that support "intelligent connectivity" across various application scenarios and reinforce the security of ISAC. This paper categorizes the related works according to the different layer structures of the proposed architecture, and some important physical and machine learning models are introduced. Additionally, we summarize the current technological bottlenecks associated with ISAC and propose future research directions and potential solutions that lay the foundation for the future development of secure and intelligent communication networks. © 1998-2012 IEEE.

关键词： Computer architecture

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Fiber-optic round trip time transfer tolerant to OSNR degradation via forward frequency transmission

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Optics Letters 2025年第8期50卷 2647-2650页

作者： Dong, Jiameng Li, Ge Wang, Zhaohui Yu, Song Luo, Bin State Key Laboratory of Information Photonics and Optical Communications School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing100876 China

In this Letter, we propose a fiber-optic round trip time transfer system tolerant to the received optical signal noise ratio (OSNR) degradation through forward frequency transfer. Typically, OSNR degrades with increased transmission distance and noise accumulation in fiber-optic time transfer systems, affecting the received signal-to-noise ratio (SNR) and system stability. The broad bandwidth of time signals limits the effectiveness of filtering to improve the received SNR. The proposed system overcomes these limitations by incorporating a forward-transmitted frequency (FTF) signal and a phase-locked pulse generator (PLPG), enhancing the receivedSNRand generating high-precision time pulses with minimal jitter. Theoretical simulations confirm the insensitivity to OSNR degradation of the system in short-term stability. Experiments over laboratory fiber links of 320 km, 640 km, and 960 km demonstrate short-term stabilities below 10 ps, with no significant deterioration despite increased transmission distance and OSNR degradation. Given its superior performance and noise resistance, this system holds significant promise for future ground-based fiber-optic time-frequency systems. © 2025 Optica Publishing Group.

关键词： Signal to noise ratio

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ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

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Frontiers of Computer Science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

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Real-Time Roadside 3-D Spatial Perception With LiDAR AIoT: An Edge-Cloud–Terminal Collaborative Sensing Prototype

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IEEE Internet of Things Journal 2025年第9期12卷 12624-12639页

作者： Xiao, Wen Li, Peiguang Tang, Miao Song, Chengwen Yu, Dianyu Liu, Hanlin Chen, Dong Chen, Nengcheng China University of Geosciences School of Geography and Information Engineering National Engineering Research Center of Geographic Information System Wuhan430074 China China University of Geosciences School of Geography and Information Engineering Wuhan430074 China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan430074 China China University of Geosciences National Engineering Research Center of Geographic Information System Wuhan430074 China

In vehicle-road cooperation, the advancement of vehicle-side autonomous driving is hindered by bottlenecks, such as limited sensing range, computational power, and environmental adaptability. Collaboration with roadside units is essential for achieving more accurate and complex spatial perception. This study presents a new prototype to enhancing spatial perception in road environments within Augmented Intelligence of Things (AIoT) systems using light detection and ranging (LiDAR) technology. Unlike traditional AIoT systems, which rely on cameras and struggle in complex conditions, the proposed prototype uses an edge-cloud–terminal collaborative sensing model to enhance 3-D spatial perception. A notable feature of this prototype is the integration of the distance and density adaptive filtering (DDAF) method, which ensures efficient point cloud filtering at the edge, with an average F1-score of 96.03% and an average latency of 11.78 ms, demonstrating strong accuracy and low latency across various scenarios. The incorporation of DDAF further improves the mean average precision (mAP) of deep learning-based 3-D object detection on the cloud by 2.34%, reduces processing time by 83.54%, and decreases peak memory usage by 90.18%, facilitating precise 3-D spatial analysis. The final results are displayed in real-time on the terminal for visualization and interaction. The efficacy of this prototype is demonstrated through a real-world case study. This research highlights the role of LiDAR and AIoT in overcoming spatial perception challenges in vehicle-road cooperation, leading to safer, more efficient transportation solutions. © 2014 IEEE.

关键词： Adaptive filtering

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MATD3-Based End-Edge Collaborative Resource Optimization for NOMA-Assisted Industrial Wireless Networks

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Computers, Materials & Continua 2025年第2期82卷 3203-3222页

作者： Ru Hao Chi Xu Jing Liu College of Information Engineering Shenyang University of Chemical TechnologyShenyang110142China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China

Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.

关键词： Industrial wireless networks(IWNs) multi-access edge computing(MEC) non-orthogonal multiple access(NOMA) task offloading resource allocation

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Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 40-53页

作者： Qinglai Wei Shanshan Jiao Qi Dong Fei-Yue Wang IEEE the Institute of Systems Engineering Macau University of Science and Technology the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences the School of Artificial Intelligence University of Chinese Academy of Sciences China Academy of Electronics and Information Technology the State Key Laboratory of Multimodal Artificial Intelligence Systems the School of Artificial Intelligence University of Chinese Academy of Sciences

This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.

关键词： Adaptive dynamic programming (ADP) critic neural network (NN) event-triggered control optimal consensus control robust control

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Smartphone Platform for Multi-signal Parallel Detection, Processing, Visualization in Fluorescence Biosensing

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IEEE Sensors Journal 2025年第10期25卷 18312-18322页

作者： Zhan, Weihe Geng, Qingfubo Wang, Baole Liu, Yian Geng, Zhaoxin Minzu University of China School of Information Engineering Beijing100081 China Minzu University of China Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE Beijing100081 China

The fluorescence sensing method is widely used in biochemical sensing. With the development of hardware structures and software systems in smartphones, this method has gradually evolved from large laboratory equipment to smartphones. However, current methods mainly rely on single signal processing and provide few detection schemes, requiring greater flexibility and efficiency. To overcome these challenges, a new smartphone platform is proposed for signal processing in fluorescence biosensing experiments. The platform supports multi-signal parallel processing and precise target localization by integrating multiple image preprocessing algorithms and a Hough transform-assisted grayscale distribution algorithm. In addition, the platform provides multiple methods for sampling and concentration curve fitting, ensuring the flexibility and verifiability of experimental design. The experimental results demonstrate that the localization algorithm achieves a hit rate of 99.48%, with an average deviation distance of only 3.595 pixels. The minimum mean square error (MSE) between the average pixel value of the target signal area calculated by the platform and the actual pixel value is only 3.158, the minimum mean absolute error (MAE) is only 1.360. Validation experiments further confirm that the sensitivity and accuracy of the platform meet the basic requirements for fluorescence sensing detection. This platform has broad applicability in biomedical engineering and point-of-care testing (POCT), improving portable diagnostic tools and paving the way for home biochemical sensing applications, such as early cancer screening and cardiovascular disease prevention. © 2001-2012 IEEE.

关键词： Hough transforms

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KCl acts as a flux to assist the growth of sub-millimeter-scale metallic 2D non-layered molybdenum dioxide

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Rare Metals 2025年第1期44卷 404-416页

作者： Li-Ying Deng Qing Zhang Wang-Yang Li Xiao-Yuan Ye Yi-Fan Zhao Shen-Zhong Chen Yu-Lan Wang Xing-Hui Wang Hui-Peng Chen Zhi-Yang Yu Qun Yan Shu-Ying Cheng Tai-Liang Guo Wen-Ping Hu Feng Ding Jie Sun National and Local United Engineering Laboratory of Flat Panel Display Technology College of Physics and Information EngineeringFuzhou UniversityFuzhou350100China Fujian Key Laboratory of Agricultural Information Sensing Technology College of Mechanical and Electrical EngineeringFujian Agriculture and Forestry UniversityFuzhou350002China Key Laboratory of Organic Integrated Circuit Department of ChemistrySchool of ScienceMinistry of Education and Tianjin Key Laboratory of Molecular Optoelectronic SciencesTianjin UniversityTianjin300072China Collaborative Innovation Center of Chemical Science and Engineering(Tianjin) Tianjin300072China College of Physics and Information Engineering Institute of Micro-Nano Devices and Solar CellsFuzhou UniversityFuzhou350108China State Key Laboratory of Photocatalysis on Energy and Environment College of ChemistryFuzhou UniversityFuzhou350116China Faculty of Materials Science and Engineering/Institute of Technology for Carbon Neutrality Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518000China

Two-dimensional(2D)metal oxides(2DMOs),such as MoO_(2),have made impressive strides in recent years,and their applicability in a number of fields such as electronic devices,optoelectronic devices and lasers has been ***,2DMOs present challenges in their synthesis using conventional methods due to their non-van der Waals *** report that KCl acts as a flux to prepare large-area 2DMOs with sub-millimeter *** systematically investigate the effects of temperature,homogeneous time and cooling rate on the products in the flux method,demonstrating that in this reaction a saturated homogenous solution is obtained upon the melting of the salt and ***,the cooling rate was adjusted to regulate the thickness of the target crystals,leading to the precipitation of 2D non-layered material from the supersaturated solution;by applying this method,the highly crystalline non-layered 2D MoO_(2)flakes with so far the largest lateral size of up to sub-millimeter scale(~464μm)were *** studies have revealed that the 2D MoO_(2)features metallic properties,with an excellent sheet resistance as low as 99Ω·square^(-1 )at room temperature,and exhibits a property of charge density wave in the measurement of resistivity as a function of temperature.

关键词： 2D non-layered materials Metallic Metal oxide Thickness modulation Flux method

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Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints

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engineering 2025年第3期46卷 278-291页

作者： Xueyan Sun Weiming Shen Jiaxin Fan Birgit Vogel-Heuser Fandi Bi Chunjiang Zhang State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Institute of Automation and Information Systems Technical University of MunichGarching 85748Germany

This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision *** FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data *** proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning *** experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.

关键词： Multi-objective Markov decision process Multi-agent deep reinforcement learning Proximal policy optimization Distributed hybrid flow-shop scheduling Blocking constraints

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