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20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Li, Yan Yi, Zhaozhi Long, Qingmin Luo, Lailong Guo, Deke School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410004 China National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819628636

With the increase of computing-intensive and delay-sensitive applications, mobile edge computing (MEC) technology has sprung up. It effectively satisfies the needs of user equipment (UE) for real-time computing resources by placing servers at the edge of the network. However, traditional MEC infrastructures are constrained by their fixed locations and emergency mobility needs. Unmanned aerial vehicles (UAVs) offer an effective solution with low cost, high mobility, and flexible deployment capabilities. In this paper, we propose a region-centric UAV-assisted MEC model, where the whole network space is divided into a set of hexagonal cells of equal area, and all UAVs in the same cell jointly process UE offloading data. Assume all UAVs are assumed to be equipped with independent MEC servers, and both UAVs and terrestrial UE follow independent homogeneous Poisson point process (PPP) distributions. Using the stochastic geometry analysis framework, we derive the successful uplink communication probability (SUCP) of uplink transmission for users. Finally, we compare the simulation results with the theoretical values to verify the model’s accuracy and evaluate the influence of key performance parameters on the network performance. © IFIP International Federation for information Processing 2025.

关键词： Stochastic systems

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Adaptive Evolutionary Reinforcement Learning Algorithm with Early Termination Strategy 23

Adaptive Evolutionary Reinforcement Learning Algorithm with ...

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23rd International Conference on Autonomous Agents and Multiagent systems, AAMAS 2024

作者： Wu, Xiaoqiang Zhu, Qingling Lin, Qiuzhen Chen, Weineng Li, Jianqiang College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China School of Computer Science and Engineering South China University of Technology Guangzhou China

Evolutionary reinforcement learning algorithms (ERLs), which combine evolutionary algorithms (EAs) with reinforcement learning (RL), have demonstrated significant success in enhancing RL performance. However, most ERLs rely heavily on Gaussian mutation operators to generate new individuals. When the standard deviation is too large or small, this approach will result in the production of poor or highly similar offspring. Such outcomes can be detrimental to the learning process of the RL agent, as too many poor or similar experiences are generated by these individuals. In order to alleviate these issues, this paper proposes an Adaptive Evolutionary Reinforcement Learning (AERL) method that adaptively adjusts both the standard deviation and the evaluation process. By tracking the performance of new individuals, AERL maintains the mutation strength within a suitable range without the need for additional gradient computations. Moreover, the proposed AERL approach early terminates unnecessary evaluations and discards experiences arising from poor individuals, thereby resulting in enhanced learning efficiency. Empirical assessments conducted on a variety of continuous control problems demonstrate the effectiveness of the AERL method. © 2024 International Foundation for Autonomous Agents and Multiagent systems.

关键词： Reinforcement learning

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Swarming magnetic photonic-crystal microrobots withon-the-fly visual pH detection and self-regulated drug delivery

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InfoMat 2023年第10期5卷 64-79页

作者： Zheng Yu Luolin Li Fangzhi Mou Shimin Yu Di Zhang Manyi Yang Qing Zhao Huiru Ma Wei Luo Tianlong Li Jianguo Guan State Key Laboratory of Advanced Technology for Materials Synthesis and Processing International School of Materials Science and Engineering Wuhan University of TechnologyWuhanthe People's Republic of China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbinthe People's Republic of China Wuhan Institute of Photochemistry and Technology Wuhanthe People's Republic of China

Swarming magnetic micro/nanorobots hold great promise for biomedical applications,but at present suffer from inferior capabilities to perceive and respond to chemical signals in local *** we demonstrate swarming magnetic photonic crystal microrobots(PC-bots)capable of sponta-neously performing on-the-fly visual pH detection and self regulated drug delivery by perceiving local pH *** magnetic PC-bots consist of pH-responsive hydrogel microspheres with encapsulated one-dimensional periodic assemblies of Fe3O4 *** programming extemnal rotating magnetic fields,they can self-organize into large swarms with much-enhanced collective velocity to actively find targets while shining bright“blinking”structural *** approaching the target with abnormal pH conditions(*** ulcerated superficial tumor lesion),the PC-bots can visualize local pH changes on the fly via pH-responsive structural colors,and realize self-regulated release of the loaded drugs by recognizing local *** work facilita tes the develop-ment of intelligent micro/nanorobots for active“motile-targeting”tumor diag-nosis and treatment.

关键词： collective behaviors drug delivery micro/nanorobots on-the-fly sensing responsivephotonic crystals

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Study of the geomagnetic field's regional gradients in Chinese continent using three-dimensional surface Spline model

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Earth and Planetary Physics 2023年第1期7卷 74-83页

作者： Yan Feng YiJun Li JinYan Zhang Shuang Liu Abbas Nasir Ya Huang Institute of Space Weather Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Space Weather Chinese Academy of SciencesBeijing 100190China State Key Laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao 999078China School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China

We combined domestic ground-based and satellite magnetic measurements to create a regional three-dimensional surface Spline(3DSS)gradient model of the main geomagnetic field over the Chinese *** improve the precision of the model,we considered the data gap between the ground and satellite *** compared and analyzed the results of the Taylor polynomial,surface Spline,and CHAOS-6(the CHAMP,?rsted and SAC-C model of Earth’s magnetic field)gradient *** showed that the gradients in the south-north and east-west directions of the four models were *** 3DSS model was able to express not only gradients at different altitudes,but also average gradients inside the research *** two Spline models were able to capture more information on gradient anomalies than were the fitted *** local anomalies were observed in northern Xinjiang,Beijing,and the junction area between Jiangsu and Zhejiang,and the total intensity F decreased whereas the altitude *** gradient decreased by 21.69%in the south-north direction and increased by 11.78%in the east-west *** addition,the altitude gradient turned from negative to positive while the altitude *** Spline model and the two fitted models differed mainly in the field sources they expressed and the modeling theory.

关键词： geomagnetic field main field gradients regional model three-dimensional modeling

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Secure RFID-Assisted Authentication Protocol for Vehicular Cloud Computing Environment

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IEEE Transactions on Intelligent Transportation systems 2024年第9期25卷 12528-12537页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Tariq, Tayyaba Alenazi, Mohammed J. F. Das, Ashok Kumar University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Sichuan University Key Laboratory of Data Protection and Intelligent Management Ministry of Education Chengdu610065 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518000 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Yunlin Douliu64002 Taiwan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500032 India

Vehicular network technology has made substantial advancements in recent years in the field of Intelligent Transportation systems. Vehicular Cloud Computing (VCC) has emerged as a novel paradigm with a substantial increase in data exchange within Vehicular ad-hoc networks (VANETs). VCC integrates cloud computing, vehicular networking, and Internet of Things (IoT) technologies. It enables Infrastructure-to-Vehicle (I2V), Vehicle-to-Vehicle (V2V), and Vehicle-to-Device (V2D) communication. VCC optimizes vehicle, cloud infrastructure, and IoT resources while addressing significant communication security and vehicle-user privacy challenges. To address these issues, we developed an RFID-based authentication protocol for VCC based on a Henon map using a hash function. In addition, we also incorporated a Physical Unclonable Function (PUF) to resist physical tampering attacks. We validate the protocol's security formally and informally. The formal security analysis is conducted through a widely used RoR model. We use the Scyther simulation tool to verify the proposed protocol's security against various attacks. Moreover, we compare the performance of our protocol with similar existing protocols across important performance parameters such as communication and computation overheads and security attributes. The proposed protocol yields substantial improvements, demonstrating a 40.74% reduction in computation overhead and a 13.03% decrease in communication overhead as compared to related protocols, delivering both enhanced performance and resource efficiency. The analysis demonstrates its capacity to support secure communication in the VCC environment and satisfy desirable security attributes. © 2024 IEEE.

关键词： Authentication

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Hybrid of bulk NbC and layered Nb_(4)C_(3)MXene for tailoring the hydrogen storage kinetics and reversibility of Li-Mg-B-H composite:An experimental and theoretical study

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Journal of Materials science & technology 2024年第27期194卷 225-235页

作者： Haizhen Liu Liwen Lu Hui Luo Jiayi Deng Guangxu Li Hua Ning Yi Fan Cunke Huang Zhiqiang Lan Wenzheng Zhou Jin Guo Xinhua Wang Guangxi Novel Battery Materials Research Center of Engineering Technology Key Laboratory of Blue Energy and Systems Integration(Guangxi University)Education Department of Guangxi Zhuang Autonomous RegionSchool of Physical Science and TechnologyGuangxi UniversityNanning 530004China College of Mathematics and Physics Guangxi Minzu UniversityNanning 530006China Nanning Engineering Technology Research Center for Power Transmission System of New Energy Vehicle Transportation CollegeNanning UniversityNanning 530200China Department of Materials Science and Engineering Zhejiang UniversityHangzhou 310027China

The Li-Mg-B-H composite(2LiBH_(4)+MgH_(2))is acknowledged as a promising material for hydrogen storage due to its large hydrogen capacity(11.4 wt.%).However,the sluggish kinetics and poor reversibility make it difficult to be practically *** this work,the hydrogen storage performances of 2LiBH_(4)+MgH_(2)have been significantly improved by a hybrid of bulk NbC and layered Nb_(4)C_(3)MXene(denoted as“Nb-C”).The 2LiBH_(4)+MgH_(2)+6 wt.%Nb-C can release 8.5 wt.%H_(2)within 30 min at 400℃and the dehy-drogenated composite can absorb 9.3 wt.%H_(2)within 30 min at 350℃and 7.5 MPa H_(2).The reversible dehydrogenation capacity maintains at 8.4 wt.%after 24 cycles,with a capacity retention ratio of 95.4%.By contrast,the undoped 2LiBH_(4)+MgH_(2)suffers from serious capacity degradation,with the capacity decreased dramatically to 3.5 wt.%after 3 *** studies revealed that the doped com-posite has uniform particle and elemental distributions and possesses various multiphase interfaces of LiH/MgB_(2)/NbC/Nb_(4)C_(3),which is beneficial to hydrogen diffusion during the hydrogen uptake and release *** studies by first principle calculation presented an extended bond length of the Mg-H and B-H bonds in the 2LiBH_(4)+MgH_(2)+NbC system,which may also explain the improved hydrogen storage properties of 2LiBH_(4)+MgH_(2)by addition of *** work provides new insights into the role of transition metal carbides in regulating the Li-Mg-B-H hydrogen storage materials both experimentally and theoretically.

关键词： Hydrogen storage Lithium borohydride Magnesium hydride MXene NbC Nb_(4)C_(3)

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DRL-Based Time-Varying Workload Scheduling With Priority and Resource Awareness

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2838-2852页

作者： Liu, Qifeng Fan, Qilin Zhang, Xu Li, Xiuhua Wang, Kai Xiong, Qingyu Chongqing University School of Big Data and Software Engineering Chongqing400044 China Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing400044 China Nanjing University School of Electronic Science and Engineering Nanjing210023 China Haihe Laboratory of Information Technology Application Innovation Tianjin300072 China Harbin Institute of Technology School of Computer Science and Technology Weihai264209 China Shandong Key Laboratory of Industrial Network Security Weihai264209 China

With the proliferation of cloud services and the continuous growth in enterprises' demand for dynamic multi-dimensional resources, the implementation of effective strategy for time-varying workload scheduling has become increasingly significant. In this paper, we propose a deep reinforcement learning (DRL)-based method for time-varying workload scheduling, aiming to allocate resources efficiently across servers in the cluster. Specifically, we integrate a classifier and queue scorer to construct a priority queue that exploits temporal resource utilization patterns across different workload classes. Then, we design parallel graph attention layers to capture the dimensional features and temporal dynamics of cloud server cluster. Moreover, we propose a DRL algorithm to generate scheduling strategies that can adapt to dynamic environments. Validation on real-world traces from Google cluster demonstrates that our method outperforms existing approaches in key metrics of cloud server cluster management. © 2004-2012 IEEE.

关键词： Cloud platforms

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Combined Representation Learning for Uncertain Knowledge Graphs 2

Combined Representation Learning for Uncertain Knowledge Gra...

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2nd International Conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Qiao, Rui Zhong, Xiaolei Fu, Yang Wuhan University of Science and Technology School of Computer Science and Technology Wuhan China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China Dianchi College Kunming China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350386639

Uncertain knowledge graphs store the relations between entities in the real world in the form of weighted triples, where the weights indicate the confidence scores of the triples to be true. However, there is limited research on the inference of uncertain knowledge graphs, especially in the integration of symbolic and numerical methods. Rules are explicit knowledge. Encoding the rules directly can provide more knowledge graph semantic information and can make full use of the interpretability and accuracy of logical rules. Unfortunately, none of the existing methods directly encode rules for uncertain knowledge graphs, but only use rules to calculate the confidence of unseen triples in training data. In this paper, we propose a new reasoning model CRLUKG for uncertain knowledge graphs, that combines the advantages of symbolic and numerical reasoning. We directly encode rules mined from the knowledge graph as one of the inputs of the CRLUKG model. Compositional representation learning with triple and rule embedding is implemented for optimizing objective function for triples and relations pairs. Experimental results demonstrate that our proposed method enhances the accuracy of reasoning, and furthermore, CRLUKG exhibits superior performance in comparison to baseline models when handling multi-task scenarios. © 2024 IEEE.

关键词： Knowledge graph

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Design and Tool Flow of a Reconfigurable Asynchronous Neural Network Accelerator

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Tsinghua science and technology 2021年第5期26卷 565-573页

作者： Jilin Zhang Hui Wu Weijia Chen Shaojun Wei Hong Chen the Institute of Microelectronics Tsinghua National Laboratory for Information Science and Technologyand Beijing Engineering Center of Technology and research on Wireless Medical and Health SystemTsinghua UniversityBeijing 100084China

Convolutional Neural Networks(CNNs)are widely used in computer vision,natural language processing,and so on,which generally require low power and high efficiency in real ***,energy efficiency has become a critical indicator of CNN *** that asynchronous circuits have the advantages of low power consumption,high speed,and no clock distribution problems,we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor(CMOS)*** the absence of a commercial design tool flow for asynchronous circuits,we develop a novel design flow to implement Click-based asynchronous bundled data circuits efficiently to mask layout with conventional Electronic Design Automation(EDA)*** also introduce an adaptive delay matching method and perform accurate static timing analysis for the circuits to ensure correct *** accelerator for handwriting recognition network(LeNet-5 model)is *** test results show that the asynchronous accelerator has 30%less power in computing array than the synchronous one and that the energy efficiency of the asynchronous accelerator achieves 1.538 TOPS/W,which is 12%higher than that of the synchronous chip.

关键词： Convolutional Neural Network(CNN)accelerator asynchronous circuit energy efficiency adaptive delay matching asynchronous design flow

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Bearing fault signal detection based on whale algorithm to optimize stochastic resonance parameters 34

Bearing fault signal detection based on whale algorithm to o...

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第34届中国控制与决策会议

作者： Huang Weichao Zhang Ganggang Faculty of automation and Information Engineering Xi'an University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781665478977

Aiming at the problem that the traditional stochastic resonance system cannot adaptively adjust the structural parameters in the bearing fault signal detection,this paper proposes a parameter adaptive stochastic resonance bearing fault signal detection method based on the whale optimization *** method is based on the bistable stochastic resonance system model,and the structural parameters of the bistable stochastic resonance are optimized through the adaptive whale algorithm,so that the fault signal is enhanced,and the bearing fault signal detection is *** method was verified by actual bearing fault signals,and a series of comparative experiments were carried *** results show that the method in this paper has a simple model,few algorithm parameters,fast convergence speed,and a large output signal-to-noise ratio of the stochastic resonance system,which can accurately and efficiently detect bearing fault signals.

关键词： Stochastic Resonance Whale Optimization Algorithm Bearing Failure Signal

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