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Exploring MEC Server Strategy in Blockchain Networks: Mining for Mobile Users or for Self

IEEE Transactions on Mobile Computing 2025年第7期24卷 6030-6044页

作者： Ling, Xintong Jiang, Rui Cao, Weihang Chen, Mingkai Wang, Jiaheng Ding, Zhi Gao, Xiqi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Purple Mountain Laboratories Nanjing210023 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States Southeast University School of Cyber Science and Engineering Nanjing210096 China University of California Department of Electrical and Computer Engineering DavisCA95616 United States

Blockchain-based decentralized applications (DApps) offer enhanced security and decentralization features;nevertheless, their maintenance demands substantial computational resources and poses challenges for deployment in mobile networks. To address this, a number of studies have explored offloading blockchain mining tasks from mobile users to mobile edge computing (MEC) servers. However, the existing literature overlooks the fact that MEC servers can not only mine for mobile users but also mine for themselves, potentially explaining why MEC mining offloading has not gained broad acceptance within the industry. In this work, we exploit a more practical case and rethink the question of whether MEC servers lease computing power to mobile users by taking into account that MEC servers can mine for themselves. We establish a game model and apply backward induction to analytically characterize Nash equilibria for mining strategies adopted by MEC and mobile users. Our findings suggest that, if MEC can mine for self, MEC would mine for mobile users only under specific conditions where mobile users possess superior information gathering capability (at least better than the MEC server) or the whole blockchain system exhibits significant network value. We further provide a series of simulations to verify our conclusion and illustrate the impact of network parameters on the strategies of both sides. © 2002-2012 IEEE.

关键词： Mobile edge computing

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Investigations and Time Estimation on Federated Learning for Future Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17387-17398页

作者： Fukumoto, Shun Li, Ruidong Zeng, Kai Nan, Haihan Su, Zhou Kanazawa University Intelligent Computation and Network Laboratory Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan Kunming University of Science and Technology Faculty of Information Engineering Automation Kunming066000 China Kanazawa University Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan George Mason University Electrical and Computer Engineering Department FairfaxVA22030 United States Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China

For future Internet of Vehicles (IoV), communications and computing will converge to provide services. Federated learning (FL), as one of the typical distributed computing technologies, needs to be integrated with IoV. For such integration, FL suffers from the straggler effect that the entire learning speed is lowered down, because of the existence of the devices, such as low-powered road side units and vehicles, taking more time to complete their tasks. Although the existing mechanisms reduce straggler effects by adopting asynchronous mechanisms and clustering mechanisms, they lack the detailed analysis of the reasons and the impacts of each cause, leading to inefficiencies in the design of algorithm. Additionally, most of the existing work only considered the impact of a single factor in computation, communication, or data distribution, which lacks comprehensive on research for causes of stragglers effects. The bottleneck is that it is laborious to observe the time delay precisely with the existing high-calculating evaluations. In this article, we elaborately explore the effects of computing power, communication capability, and data distributions on the straggler effects with carefully designing and conducting the extensive experiments. After investigations, we propose a novel learning completion time estimation formula for low computing capability devices with mini-batch stochastic gradient decent (SGD). We compare our proposed estimation formula with the one based on floating operation per second (FLOPs). Through the evaluations, our formula can demonstrate the improvement up to 72.4% at docker and 32.4% at Raspberry Pi device compared to the existing work. © 2014 IEEE.

关键词： Stochastic systems

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Vibration Signal Feature Extraction of Wu’s Shallow Acupuncture Based on CV-SVM

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第4期9卷 2322-2340页

作者： Fang, Weidong Chen, Zebin Pan, Jeng-Shyang School of Electronic Electrical Engineering and Physics Fujian Provincial Key Laboratory of Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Chaoyang University of Technology Taichung413310 Taiwan

Wu Binghuang shallow acupuncture technique was selected as the sixth batch of intangible heritage items in Fujian Province in 2019, and Wu Binghuang shallow acupuncture technique has good effect on treating insomnia in clinical trials. The shallow acupuncture technique has three kinds of techniques: " drainage method", " tonic method", and " flat tonic and flat drainage", which can be used for different treatment purposes, and the three techniques have high operational similarity. In the development of the shallow needle instrument using modern electronic technology to simulate the shallow needle technique of Bing-Huang Wu, it is necessary to extract and distinguish the vibration signals of the three modes. To address the problem of difficulty in differentiating Wu’s shallow acupuncture techniques, a feature extraction method based on EMD sample entropy, energy occupation ratio after Pyramid decomposition and CV-SVM is proposed in this paper. The vibration signal is noise reduced by using wavelet noise reduction, firstly, the EMD decomposition is performed on the noise reduced data, the correlation coefficient between individual IMF and the original signal is calculated, the IMF with the correlation coefficient greater than 0.1 is selected as the effective component, the sample entropy of the effective component is calculated, then the Pyramid decomposition of the noise reduced vibration signal is divided into 9 layers, the relative energy of each layer is calculated, and the sample entropy of the effective component and the relative energy of each layer are calculated. The sample entropy of the effective component and the relative energy of each layer are formed into a Govett collection. The CV-SVM is then employed to identify the signal patterns, resulting in an average recognition rate of 76% that possesses engineering application value. The vibration data of Prof. Wu Binghuang’s treatment with shallow needles were analyzed, and the practical application of the p

关键词： Noise abatement

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Active terahertz beam steering based on mechanical deformation of liquid crystal elastomer metasurface

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Light(science & Applications) 2023年第1期12卷 118-127页

作者： Xiaolin Zhuang Wei Zhang Kemeng Wang Yangfan Gu Youwen An Xueqian Zhang Jianqiang Gu Dan Luo Jiaguang Han Weili Zhang Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronic Information TechnologyMinistry of EducationTianjin University300072 TianjinChina Department of Electrical and Electronic Engineering Southern University of Science and Technology518055 ShenzhenChina School of Electrical and Computer Engineering Oklahoma State UniversityStillwaterOK 74078USA

Active metasurfaces are emerging as the core of next-generation optical devices with their tunable optical responses and flat-compact *** for the terahertz band,active metasurfaces have been developed as fascinating devices for optical chopping and compressive sensing ***,performance regulation by changing the dielectric parameters of the integrated functional materials exhibits severe limitations and parasitic ***,we introduce a C-shape-split-ring-based phase discontinuity metasurface with liquid crystal elastomer as the substrate for infrared modulation of terahertz ***-focused infrared light is applied to manipulate the deflection of the liquid crystal elastomer substrate,enabling controllable and broadband wavefront steering with a maximum output angle change of 22°at *** as another control method is also investigated and compared with infrared *** further demonstrate the performance of liquid crystal elastomer metasurface as a beam steerer,frequency modulator,and tunable beam splitter,which are highly desired in terahertz wireless communication and imaging *** proposed scheme demonstrates the promising prospects of mechanically deformable metasurfaces,thereby paving the path for the development of reconfigurable metasurfaces.

关键词： tunable modulator beam

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Joint Power Allocation and Task Scheduling for Data Offloading in Non-Geostationary Orbit Satellite Networks

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2882-2896页

作者： He, Lijun Jia, Ziye Wang, Juncheng Lansard, Erick Han, Zhu Yuen, Chau China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University State Key Laboratory of Integrated Services Networks Xi’an710071 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China Hong Kong Baptist University Department of Computer Science Kowloon Tsai Hong Kong Nanyang Technological University School of Electrical and Electronics Engineering Jurong West 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

In Non-Geostationary Orbit Satellite Networks (NGOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving data offloading efficiency. In this work, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in NGOSNs. Our goal is to properly balance the minimization of the total energy consumption and the maximization of the sum weights of tasks. Due to the tight coupling between power allocation and task scheduling, we first derive the optimal power allocation solution to the joint optimization problem with any given task scheduling policy. We then leverage the conflict graph model to transform the joint optimization problem into an Integer Linear Programming (ILP) problem with any given power allocation strategy. We explore the unique structure of the ILP problem to derive an efficient semidefinite relaxation-based solution. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the original joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the reduction of total energy consumption and the improvement of the sum weights of tasks, thus achieving superior system performance over the current literature. © 2004-2012 IEEE.

关键词： Geostationary satellites

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Arbitrary acoustic orbital angular momentum detection using dual-layer metasurfaces

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science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 106-112页

作者： Zhanlei Hao Haojie Chen Yuhang Yin Shan Zhu Yadong Xu Cheng-Wei Qiu Huanyang Chen Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China School of Physical Science and Technology and Jiangsu Key Laboratory of Thin Films Soochow UniversitySuzhou 215006China

Orbital angular momentum(OAM),with its unique physical properties and vast application prospects,has attracted widespread attention in various ***,the development of valid and practical acoustic OAM detection methods continues to be a challenging *** this paper,we propose a novel construction method of dual-layer metasurfaces to achieve a doubleconversion process for the waveform reshaping and differentiated focusing of two-dimensional vortex sources with different ***,by utilizing a concise formula,a one-to-one correspondence is established between the OAM of incident vortex waves and different imaging *** fundamental principle of this special conversion relationship is rigorously constrained by the directional compensation of phase and the material parameters of dual-layer metasurfaces with different quadratic phase *** importantly,the highly consistent results between numerical demonstrations and acoustic experiments further confirm the feasibility and effectiveness of the proposed OAM detection *** work provides a new perspective on the precise manipulation for the phase of vortex fields,holding potential applications in super-resolution imaging and the design of acoustic OAM-based devices.

关键词： arbitrary acoustic OAM detection vortex waves dual-layer metasurfaces waveform reshaping differentiated focusing acoustic experiments

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Channel-Feedback-Free Transmission for Downlink FD-RAN:A Radio Map Based Complex-Valued Precoding Network Approach

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China Communications 2024年第4期21卷 10-22页

作者： Zhao Jiwei Chen Jiacheng Sun Zeyu Shi Yuhang Zhou Haibo Xuemin(Sherman)Shen School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310058China Department of Mathematics and Theories Peng Cheng LaboratoryShenzhen 518000China Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada

As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network ***,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the *** paper proposes a novel transmission scheme without relying on physical layer channel ***,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user *** comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input ***,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified *** also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss *** evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.

关键词： beamforming complex neural networks deep learning FD-RAN

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Spectral period doubling and encoding of dissipative optical solitons via gain control

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PhotoniX 2024年第1期5卷 290-305页

作者： Kangwen Yang Yi Zhou Yuqing Ling Kevin K.Tsia Heping Zeng Kenneth K.Y.Wong Shanghai Key Laboratory of Modern Optical System and Engineering Research Center of Optical Instrument and SystemMinistry of EducationSchool of Optical Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Advanced Biomedical Instrumentation Centre Hong Kong Science ParkHong KongChina State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China

Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly restricted to self-sustained steady state,controllable manipulation and dynamic switching between period doubling and other intriguing dynamical states are still largely ***,we propose to expand the vision of dissipative soliton periodic doubling,which we illustrate experimentally by reporting original spontaneous,collisional,and controllable spectral period doubling in a polarization-maintaining ultrafast fiber ***,the spontaneous period doubling can be observed in both single-and *** mechanism of the switchable state and periodic doubling was revealed by numerical ***,state transformation of individual solitons can be resolved during the collision of triple solitons involving stationary,oscillating,and period ***,controllable deterministic switching between period doubling and other dynamical states,as well as exemplifying the application of period-doubling-based digital encoding,is achieved under programmable pump *** results open a new window for unveiling complex Hopf bifurcation in dissipative systems and bring useful insights into nonlinear science and applications.

关键词： Period doubling Mode locking Ultrafast fiber lasers

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MMLN: Multi-directional and Multi-constraint Learning Network for Remote Sensing Imagery Semantic Segmentation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2024年 1-16页

作者： Sun, Hang Xie, Yongchang Ren, Dong Wen, Fangqing Tong, Lyuyang Chang, Laibin Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China Institute of Vehicle Information Control and Network Technology Hubei University of Automotive Technology Shiyan China School of Computer Science Wuhan University Wuhan China

Recent advances in satellite remote sensing technology and computer technology have significantly impacted practical applications in remote sensing image segmentation. However, the prevalent hybrid segmentation models that combine Convolutional Neural Networks (CNNs) and Transformers, often overlook the critical exploration of local and global feature correlations across various scales. This exploration is essential for learning more representative features and strengthening context modeling capabilities. Additionally, the decoding layers of these models do not effectively exploit the pixel-level semantic relationships within cross-layer feature maps, thereby limiting the models' ability to discern small object features. To address these challenges, this paper introduces a Multi-directional and Multi-constraint Learning Network (MMLN) designed for semantic segmentation of remote sensing imagery. This network features a Multi-directional Dynamic Complement Decoder (MDCD), which enhances the interaction between local and global features in the feature space, and subsequently improves the feature discrimination within the segmentation network. Moreover, a Multi-constraint Saliency Boundary-adaptive Module (MSBM) is implemented to reinforce the spatial constraints on saliency at the edge regions and ensure semantic consistency along the mask boundaries. This, in turn, augments the segmentation model's capability to detect small objects. The evaluation on four datasets reveals that the MMLN outperforms the existing state-of-the-art methods in remote sensing imagery segmentation. The code is available at https://***/zhongyas/MMLN. Authors

关键词： Semantics

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Reinforcement Learning-Based Time-Synchronized Optimized Control for Affine Systems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 5216-5231页

作者： Zhang, Yuxiang Liang, Xiaoling Li, Dongyu Ge, Shuzhi Sam Gao, Bingzhao Chen, Hong Lee, Tong Heng National University of Singapore Department of Electrical and Computer Engineering 117576 Singapore Beihang University School of Cyber Science and Technology Beijing100191 China Tianmushan Laboratory Hangzhou310023 China Tongji University Clean Energy Automotive Engineering Center Shanghai201804 China

The approach of (fixed-) time-synchronized control (FTSC) aims at attaining the outcome where all the system state-variables converge to the origin simultaneously/synchronously. This type of outcome can be the highly essential performance desired in various real-world high-precision control applications. Toward this objective, this article proposes and investigates the development of a time-synchronized reinforcement learning algorithm (TSRL) applicable to a particular class of first- and second-order affine nonlinear systems. The approach developed here appropriately incorporates the norm-normalized sign function into the optimal system control design, leveraging on the special properties of this norm-normalized sign function in attaining time-synchronized stability and control. Concurrently, the actor–critic framework in reinforcement learning (RL) is invoked, and the dual quantities of system control and gradient term of the cost function are decomposed with appropriate time-synchronized control items and unknown actor/critic part and to be learned independently. By additionally employing the adaptive dynamic programming technique, the solution of the Hamilton–Jacobi–Bellman equation is iteratively approximated under this actor–critic framework. As an outcome, the proposed TSRL method optimizes the system control while attaining the notable time-synchronized convergence property. The performance and effectiveness of the proposed method are demonstrated to be effectively applicable via detailed numerical studies and on an autonomous vehicle nonlinear system motion control problem. © 2020 IEEE.

关键词： Synchronization

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