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Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation

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CSEE Journal of power and Energy Systems 2023年第6期9卷 2236-2250页

作者： Minglei Bao Xiaocong Sun Yi Ding Chengjin Ye Changzheng Shao Sheng Wang Yonghua Song the College of Electrical Engineering Zhejiang UniversityHangzhou 310027China the State key laboratory of power Transmission Equipment and System Security at Chongqing University Chongqing 400044China the State key laboratory of internet of things for Smart City University of MacaoMacao 999078China

With the increasing interactions between natural gas systems(NGS)and power systems,component failures in one system may propagate to the other one,threatening reliable operation of the whole *** to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems(IEGSs),traditional economy-oriented reserve expansion models may lead to unreasonable planning *** order to address this,an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and ***,novel multifactor-influenced reliability indices are defined con-sidering synthetic effects of multiple uncertainties,including failure propagation,load uncertainties and generation *** reliability index formulation,contribution of failure propagation on system reliability is analytically *** avoid high computational complexity,the fuzzy set theory is combined with conventional methods,e.g.,Monte-Carlo simulation technique to reduce numerous contingency *** contingency states are aggregated into several clusters represented by a fuzzy *** effectively solve the planning model,a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability *** studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.

关键词： Cross-sectorial 1 failure propagation fuzzy model integrated electricity-gas systems long-term reserve planning reliability

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CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

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Computers, Materials & Continua 2024年第7期80卷 1491-1519页

作者： Xiangyu Wu Xuehui Du Qiantao Yang Aodi Liu Na Wang Wenjuan Wang He’nan Province key laboratory of Information Security Information Engineering UniversityZhengzhou450000China School of Cyber Science Engineering Zhengzhou UniversityZhengzhou450000China

Blockchain has been widely used in finance,the internet of things(IoT),supply chains,and other scenarios as a revolutionary *** protocol plays a vital role in blockchain,which helps all participants to maintain the storage state ***,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus *** address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation *** can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore *** addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of *** experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

关键词： Blockchain consensus byzantine fault-tolerant collaborative filtering trust

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Achieving full mutualism with massive passive devices for multiuser MIMO symbiotic radio

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Science China(Information Sciences) 2024年第9期67卷 196-212页

作者： Jingran XU Zhuoyin DAI Yong ZENG Shi JIN Tao JIANG National Mobile Communications Research laboratory Southeast University Purple Mountain Laboratories Research Center of 6G Mobile Communications School of Cyber Science and Engineering and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology

Symbiotic radio(SR) is one of the attractive communication technologies to facilitate largescale internet of things(IoT) connections with enhanced energy and spectrum efficiency, where passive backscatter devices(BDs) modulate their information over the radio frequency(RF) signals emitted by the active primary transmitters(PTs). Meanwhile, the primary transmission can be strengthened with the additional multipaths created by BDs. To capitalize to a greater extent on the mutualism relationship between the two types of communication, this paper studies multiple-input multiple-output(MIMO) SR communication systems including multiple PTs and massive BDs. We derive the achievable rate expressions of each PT and BD, as well as the sum rate expressions of primary and secondary communication, *** asymptotic analysis is given to derive the active and passive communication rates with a large number of BDs. Furthermore, for the general case with a finite number of BDs, we study the precoding optimization problem to maximize the sum rate of primary communication, while ensuring that the sum rate of secondary communication and the individual rate for each PT and BD in the prescribed active and passive user sets satisfy the specified thresholds. Simulation results are presented to verify the analytical studies.

关键词： multiuser MIMO SR backscattering massive backscatter devices asymptotic analysis active and passive communication

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Adaptive joint configuration optimization for collaborative inference in edge-cloud systems

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Science China(Information Sciences) 2024年第4期67卷 335-336页

作者： Zheming YANG Wen JI Zhi WANG Institute of Computing technology Chinese Academy of Sciences University of Chinese Academy of Sciences Peng Cheng laboratory Tsinghua Shenzhen International Graduate School Tsinghua University

With the rapid development of technologies such as deep learning and the internet of things(IoT), the deployment and application of various IoT devices are becoming increasingly widespread, resulting in the inference tasks generated increasing dramatically [1]. Many deep neural network(DNN) models are deployed on servers for performing inference tasks.

关键词： Inference engines

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A Survey of Edge Caching:key Issues and Challenges

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Tsinghua Science and technology 2024年第3期29卷 818-842页

作者： Hanwen Li Mingtao Sun Fan Xia Xiaolong Xu Muhammad Bilal School of Computer Science Nanjing University of Information Science and TechnologyNanjing 210044China Shandong Provincial University laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262700China Reading Academy Nanjing University of Information Science and TechnologyNanjing 210044China School of Software Nanjing University of Information Science and TechnologyNanjing 210044China Department of Computer Engineering Hankuk University of Foreign StudiesYongin-si 17035Republic of Korea

With the rapid development of mobile communication technology and intelligent applications,the quantity of mobile devices and data traffic in networks have been growing exponentially,which poses a great burden to networks and brings huge challenge to servicing user *** caching,which utilizes the storage and computation resources of the edge to bring resources closer to end users,is a promising way to relieve network burden and enhance user *** this paper,we aim to survey the edge caching techniques from a comprehensive and systematic *** first present an overview of edge caching,summarizing the three key issues regarding edge caching,i.e.,where,what,and how to cache,and then introducing several significant caching *** then carry out a detailed and in-depth elaboration on these three issues,which correspond to caching locations,caching objects,and caching strategies,*** particular,we innovate on the issue“what to cache”,interpreting it as the classification of the“caching objects”,which can be further classified into content cache,data cache,and service ***,we discuss several open issues and challenges of edge caching to inspire future investigations in this research area.

关键词： edge caching edge computing caching location caching object caching strategy 5G networkarchitecture internet of things(IoT)

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Mixed Deep Reinforcement Learning Considering Discrete-continuous Hybrid Action Space for Smart Home Energy Management

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Journal of Modern power Systems and Clean Energy 2022年第3期10卷 743-754页

作者： Chao Huang Hongcai Zhang Long Wang Xiong Luo Yonghua Song IEEE State key laboratory of internet of things for Smart City University of MacaoMacao S.A.R.China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School University of Science and Technology BeijingFoshan 528399China State key laboratory of internet of things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao S.A.R.China

This paper develops deep reinforcement learning(DRL)algorithms for optimizing the operation of home energy system which consists of photovoltaic(PV)panels,battery energy storage system,and household ***-free DRL algorithms can efficiently handle the difficulty of energy system modeling and uncertainty of PV ***,discretecontinuous hybrid action space of the considered home energy system challenges existing DRL algorithms for either discrete actions or continuous ***,a mixed deep reinforcement learning(MDRL)algorithm is proposed,which integrates deep Q-learning(DQL)algorithm and deep deterministic policy gradient(DDPG)*** DQL algorithm deals with discrete actions,while the DDPG algorithm handles continuous *** MDRL algorithm learns optimal strategy by trialand-error interactions with the ***,unsafe actions,which violate system constraints,can give rise to great *** handle such problem,a safe-MDRL algorithm is further *** studies demonstrate that the proposed MDRL algorithm can efficiently handle the challenge from discrete-continuous hybrid action space for home energy *** proposed MDRL algorithm reduces the operation cost while maintaining the human thermal comfort by comparing with benchmark algorithms on the test ***,the safe-MDRL algorithm greatly reduces the loss of thermal comfort in the learning stage by the proposed MDRL algorithm.

关键词： Demand response deep reinforcement learning discrete-continuous action space home energy management safe reinforcement learning

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Frequency-Self-Adaptive Radio Frequency power Harvester Enabled by Shape-Reconfigurable Liquid Metal

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Electromagnetic Science 2024年第2期2卷 91-103页

作者： Cheng Zhang Yuchao Wang Zebin Zhu Hai Lin Kun Wang Xintong Shi Yi Du Chaoyun Song Long Ren Qiang Cheng key laboratory of Materials for High-power Laser Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China College of Physical Science and technology Central China Normal UniversityWuhan 430000China Center of Quantum and Matter Science and School of Physics Beihang UniversityBeijing 100191China Department of Engineering King’s College LondonLondon WC2R 2LSUK State key laboratory of Radio Frequency Heterogeneous Integration College of Electronics and Information EngineeringShenzhen UniversityShenzhen 518000China State key laboratory of Advanced technology for Materials Synthesis and Processing International School of Materials Science and EngineeringWuhan University of TechnologyWuhan 430000China State key laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

Radio frequency(RF)energy harvester as an efficient tool for capturing and converting the flourishing ambient RF energy provides a promising solution for long-term powering the wireless sensor networks and the internet of things(IoTs).However,the actual distribution of the environmental RF signals is dynamically frequency-dependent due to the diverse wireless terminals only interacting with specified *** take full advantage of the RF energy carrying this characteristic,an intelligent RF energy harvester is in demand to automatically sense the frequency information of an incident signal and conduct the corresponding RF-to-direct current transformation ***,to the best of my knowledge,a frequency-self-adaptive RF harvester is first presented with the help of the shape-reconfigurable liquid metal,which can precisely identify and efficiently convert an arbitrary signal from the frequency span of 1.8 to 2.6 *** with a microcontroller unit and a tensile system,the dynamic functionality of the entire system is comprehensively demonstrated,showing promising potential to significantly advance various fields,including sustainable IoT applications,green wearable technologies,and self-powered devices.

关键词： Liquid metal Radio frequency power harvesting Frequency-self-adaptive Broadband rectification

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Highly Efficient Back‑End‑of‑Line Compatible Flexible Si‑Based Optical Memristive Crossbar Array for Edge Neuromorphic Physiological Signal Processing and Bionic Machine Vision

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Nano-Micro Letters 2024年第11期16卷 323-339页

作者： Dayanand Kumar Hanrui Li Dhananjay D.Kumbhar Manoj Kumar Rajbhar Uttam Kumar Das Abdul Momin Syed Georgian Melinte Nazek El‑Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer EngineeringComputer Electrical Mathematical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)23955‑6900 ThuwalSaudi Arabia

The emergence of the internet-of-things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and advanced *** 3D integration,edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy ***,we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications,including electroencephalogram(EEG)-based seizure prediction,electromyography(EMG)-based gesture recognition,and electrocardiogram(ECG)-based arrhythmia *** experiments on three biomedical datasets,we observe the classification accuracy improvement for the pretrained model with 2.93%on EEG,4.90%on ECG,and 7.92%on EMG,*** optical programming property of the device enables an ultralow power(2.8×10^(-13) J)fine-tuning process and offers solutions for patient-specific issues in edge computing ***,the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions,making it promising for neuromorphic vision *** display the benefits of these intricate synaptic properties,a 5×5 optoelectronic synapse array is developed,effectively simulating human visual perception and memory *** proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.

关键词： Neuromorphic computing Electrophysiological signal Artificial vision system Image recognition Memristor

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Truncated Strategy Based Dynamic Network Pricing for Energy Storage

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Journal of Modern power Systems and Clean Energy 2023年第2期11卷 544-552页

作者： Xiaohe Yan Hongcai Zhang Chenghong Gu Nian Liu Furong Li Yonghua Song State key laboratory of Alternate Electrical power System with Renewable Energy Sources(North China Electric power University) BeijingChina State key lab of internet of things for Smart City University of MacaoMacaoChina Department of Electronic and Electrical Engineering University of BathBathU.K.

With the increasing penetration of local renewable energy and flexible demand,the system demand is more unpredictable and causes network overloading,resulting in costly system *** the energy storage(ES)helps reduce the system peak power flow,the incentive for ES operation is not sufficient to reflect its value on the system investment deferral resulting from its *** paper designs a dynamic pricing signal for ES based on the truncated strategy under robust operation corresponding to the network charge ***,the operation strategy is designed for ES to reduce the total network investment cost considering the uncertainties of flexible load and renewable *** nodal uncertainties are converted into branch power flow uncertainties by the cumulant and Gram-Charlier expansion ***,a time of use(ToU)pricing scheme is designed to guide the ES operation reflecting its impact on network investment based on the longrun investment cost(LRIC)pricing *** proposed To U LRIC method allocates the investment costs averagely to network users over the potential curtailment periods,which connects the ES operation with network *** curtailment amount and the distribution of power flow are assessed by the truncated strategy considering the impact of *** demonstrated in a Grid Supply Point(GSP)distribution network in the UK,the network charges at the peak time reduce more than 20%with ES *** proposed method is cost-reflective and ensures the fairness and efficiency of the pricing signal for ES.

关键词： Energy storage network investment renewable energy robust optimization uncertainty

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UAV-assisted cooperative offloading energy efficiency system for mobile edge computing

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Digital Communications and Networks 2024年第1期10卷 16-24页

作者： Xue-Yong Yu Wen-Jin Niu Ye Zhu Hong-Bo Zhu Jiangsu key laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003China Engineering Research Centerof Health Service System Based on Ubiquitous Wireless Networks Ministry of EducationNanjng Universityof Posts and Telecommunications Nanjing210003China

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground *** this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the internet of things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still *** to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of *** the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy ***,the resulting optimization problem is originally nonconvex and thus,difficult to solve *** tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex ***,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser *** results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

关键词： Computation offloading internet of things(IoT) Mobile edge computing(MEC) Block coordinate descent(BCD)

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