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Virtualizing Next-Generation Programmable Networks: Techniques, Use Cases, and Promising Future Directions

IEEE Network 2025年第3期39卷 148-155页

作者： Chen, Xiang Du, Hongyang Liu, Wenjing Liu, Hongyan Zhang, Jianshan Yang, Xu Zhang, Dong Wu, Chunming Liu, Xuan Niyato, Dusit Zhejiang University College of Computer Science and Technology Hangzhou310027 China The University of Hong Kong Department of Electrical and Electronic Engineering Pokfulam Hong Kong Zhejiang Media Group Hangzhou310005 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Data Science Fuzhou350108 China Fuzhou University College of Computer and Data Science Fuzhou350108 China Yangzhou University College of Information Engineering College of Artificial Intelligence Yangzhou225009 China Nanyang Technological University College of Computing and Data Science Jurong West 639798 Singapore

For decades, network virtualization plays a crucial role in modern networks, e.g., 6G mobile networks: tenants construct arbitrary virtual networks on the same physical network. However, production networks are becoming programmable and need more ways of network configurations. So prior techniques like SDN hypervisors are deprecated since they cannot configure programmable networks. In response, a new category of network virtualization techniques has emerged recently to virtualize programmable networks, i.e., programmable network hypervisors (PNHs). This article first reviews this trend to comprehensively survey PNHs. To understand their benefits, we build a testbed with hardware switches and sophisticated topologies. Our testbed experiments stress-test hypervisors and demonstrate that they outperform prior works with higher acceptance ratios of virtual networks under large-scale scenarios and heavy loads. Finally, we highlight the open issues of these techniques to shed light on the future directions in this promising topic. © 1986-2012 IEEE.

关键词： Virtualization

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A Multi-UAV Formation Obstacle Avoidance Method Combined Improved Simulated Annealing and Adaptive Artificial Potential Field

arXiv

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arXiv 2025年

作者： Ma, Bo Ji, Yi Fang, Liyong School of Aeronautics and Astronautics University of Electronic Science and Technology of China Sichuan Chengdu611731 China SDU-ANU Joint Science College Shandong University Weihai264209 China University of Electronic Science and Technology of China Zhejiang Huzhou3130001 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China National Key Laboratory of Adaptive Optics Sichuan Chengdu611731 China

The traditional Artificial Potential Field (APF) method exhibits limitations in its force distribution: excessive attraction when UAVs are far from the target may cause collisions with obstacles, while insufficient attraction near the goal often results in failure to reach the target. Furthermore, APF is highly susceptible to local minima, compromising motion reliability in complex environments. To address these challenges, this paper presents a novel hybrid obstacle avoidance algorithm—Deflected Simulated Annealing–Adaptive Artificial Potential Field (DSA-AAPF)—which combines an improved simulated annealing mechanism with an enhanced APF model. The proposed approach integrates a Leader-Follower distributed formation strategy with the APF framework, where the resultant force formulation is redefined to smooth UAV trajectories. An adaptive gravitational gain function is introduced to dynamically adjust UAV velocity based on environmental context, and a fast-converging controller ensures accurate and efficient convergence to the target. Moreover, a directional deflection mechanism is embedded within the simulated annealing process, enabling UAVs to escape local minima caused by semi-enclosed obstacles through continuous rotational motion. The simulation results, covering formation reconfiguration, complex obstacle avoidance, and entrapment escape, demonstrate the feasibility, robustness, and superiority of the proposed DSA-AAPF algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Simulated annealing

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Surrogate-Assisted Multiobjective Gene Selection for Cell Classification from Large-Scale Single-Cell RNA Sequencing Data

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IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital Department of Pathology Wuhan University Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20,000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Multiplexed model predictive attitude control for nadir-pointing satellite using only magnetorquers

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control Engineering Practice 2025年 162卷

作者： Yang, Sen Ling, Keck Voon Wang, Zhenhua Li, Huiping School of Astronautic Harbin Institute of Technology Harbin150001 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

Due to the low failure risk of magnetorquers, the control strategy based on magnetic actuators can significantly enhance the reliability of the satellite attitude control system. In light of this advantage, this paper conducts research on model predictive control (MPC) algorithm for nadir-pointing satellites equipped only with magnetorquers. Firstly, to facilitate controller design, the linear time-varying (LTV) model for nadir-pointing satellites is derived by linearizing the nonlinear equations around the operating point. Then, leveraging this linearized representation, an LTV multiplexed MPC (MMPC) method with exponential weighting is proposed. The MMPC scheme allows for faster sampling rates and quicker responses to disturbances, thereby enhancing the overall performance of the satellite attitude control system while retaining the benefits of MPC. Finally, compared with a state-of-the-art SMPC method, the proposed method is particularly advantageous in situations where computational resources are limited, specifically for satellites that rely only on onboard computing capabilities. © 2025

关键词： Nonlinear equations

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Outage Analysis of RSMA Enabled Integrated Satellite-Terrestrial Networks

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IEEE Transactions on Vehicular technology 2025年

作者： Hu, Chenbo Yang, Hongjuan Zhou, Zhiquan Li, Bo Jiang, Xu Zhao, Nan Nallanathan, Arumugam Weihai264209 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Electronic Engineering Kyung Hee University Yongin-si Gyeonggi-do 17104 China

Rate splitting multiple access (RSMA) has emerged in the integrated satellite-terrestrial networks (ISTNs). However, the satellite-terrestrial channel suffers serious shadow fading and cannot maintain stable communication links effectively. From the perspective of reliability, this correspondence takes the lead in focusing on the outage probability (OP) of ISTNs based on the combination of RSMA and hybrid automatic repeat request with chase combining (HARQ-CC). The lower and upper bounds of OP are derived firstly according to the inclusion-exclusion principle. Then, the diversity order is deduced, pointing out the conditions for full time diversity. Monte Carlo simulations confirm the accuracy of the theoretical results, and superior outage performance of HARQ-CC-aided RSMA is present compared with benchmarks. © 1967-2012 IEEE All rights reserved.

关键词： Satellite links

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One-stone-two-birds: over 26% efficiency in perovskite solar cells via synergistic crystallization & interface regulation

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Energy and Environmental Science 2025年

作者： Jiao, Boxin Tan, Liguo Ye, Yiran Ren, Ningyu Li, Minghao Li, Hang Li, Xiaoyi Yi, Chenyi State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Center of Materials Science and Optoelectronics Engineering College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Institute of Carbon Neutrality Tsinghua University Beijing100084 China

Organic-inorganic hybrid perovskites have emerged as promising photovoltaic materials due to their excellent photoelectronic properties and low-cost fabrication techniques. However, the performance and stability of perovskite solar cells (PSCs) are compromised by the random orientation of optically active phase crystals and bulk/interface defects. In this paper, we developed a multifunctional organic material, parabanic acid, to regulate the crystallization and realize full-range defect passivation integrated passivation of defects in perovskites. Attributed to the synergistic effect of functional groups, perovskite films with concentrated out-of-plane spatial orientation were formed. In addition, the introduction of an interface passivation layer based on parabanic acid achieved integrated passivation of bulk and interface defects in perovskite solar cells. The resulting PSCs achieved a power conversion efficiency of 26.03% (certified 25.51%) with excellent environmental stability. Notably, under standard measurement conditions (ISOS-L-1I), the maximum power point output maintained 96.3% of its initial efficiency over 2000 hours. The synergistic regulation of crystal orientation and integrated passivation of defects provide a new approach to promote the development of perovskite solar cells. © 2025 The Royal Society of Chemistry.

关键词： Organic-inorganic materials

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UV-activated TiO2 nanoparticles for sensitively detecting ppb-level dimethyl sulfide at room temperature

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Sensors and Actuators B: Chemical 2025年 441卷

作者： Rong, Dandan Meng, Gang Mi, Longqing Li, Meng Zhang, Ruofan Ji, Xiaohua Dai, Tiantian Li, Hongtao Fang, Xiaodong You, Libing Deng, Zanhong Anhui Provincial Key Laboratory of Photonic Devices and Materials Anhui Institute of Optics and Fine Mechanics and Key Lab of Photovoltaic and Energy Conservation Materials Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China Mozi Laboratory Zhengzhou450000 China School of Information and Artificial Intelligence Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment Anhui Provincial Engineering Research Center for Agricultural Information Perception and Intelligent Computing Anhui Agricultural University Hefei230036 China School of Physics and Optoelectronic Engineering Key Laboratory of Opto-Electronic Information Acquisition and Manipulation of Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China College of New Materials and New Energies Shenzhen Technology University Shenzhen518118 China

Dimethyl sulfide (DMS) is one kind of volatile sulfur compounds (VSCs) possessing disagreeable odor, with a low olfactory threshold around 20 ppb. Highly sensitive detection of DMS at room temperature (RT) is critically needed for emerging application with low power consumption, but it remains a significant challenge owing to its low reactivity. Herein, UV photoactivated titanium dioxide (TiO2) nanoparticles (NPs) have been employed for detecting DMS at RT. An eco-friendly ultrasonic crushing solution spray technique was developed to prepare TiO2 based sensors. An ultrahigh response of 30–500 ppb DMS and a low experimental limit of detection (Ra/Rg = 2.7@50 ppb) could be achieved at RT under UV light activation. This work opens a new avenue to achieve highly sensitive, energy-efficient sensors for trace VSCs detection at RT in ambient odor monitoring. © 2025 Elsevier B.V.

关键词： Sulfur dioxide

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Improving Performance of Repetitive control for Nonlinear Systems via Improved Disturbance Compensation

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IEEE Transactions on Industrial Informatics 2025年

作者： Tian, Shengnan Wang, Yibing Zhang, Manli Li, Yang Lu, Chengda Liu, Kang-Zhi She, Jinhua Wu, Min China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Chiba University Department of Electrical and Electronic Engineering Chiba263-8522 Japan Tokyo University of Technology School of Engineering Hachioji192-0982 Japan

In practice, repetitive control (RC) is a type of learning control that exhibits good tracking performance. However, existing nonlinear RC methods lack analysis and design of the learning property, which results in limited performance. This study addresses the learning-enhanced issue. First, a new fuzzy Lyapunov candidate is constructed for stability analysis, which contains an integral term associated with the membership function and a double integral term. The design of the learning-dependent term integrates the nonlinear membership function information, which enhances the learning ability. Second, an additional first-order low-pass filter is incorporated into the conventional equivalent input disturbance estimator. The new filter acts as an integrator that adjusts the bandwidth of the disturbance compensation and gradually eliminates the disturbances in the output error. Third, a recursive optimization algorithm is used to design the controllers. Experimental comparisons on motor drive systems demonstrate the effectiveness and superiority of the method. © 2005-2012 IEEE.

关键词： Membership functions

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 PP卷 PP页

作者： Jun Chen Liling Yang Wei Yu Wenping Gong Zhanchuan Cai Jiayi Ma School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Faculty of Engineering China University of Geosciences Wuhan China School of Computer Science and Engineering Macau University of Science and Technology Taipa Macau China Electronic Information School Wuhan University Wuhan China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. The code will be posted at: https://***/Liling-yang/SDSFusion.

关键词： Degradation Image fusion Semantics Training Visualization Meteorology Feature extraction Lighting Image segmentation Brightness

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