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Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 613-624页

作者： WU Zhihai XIE Linbo engineering Research Center of internet of things Technology Applications of the Ministry of Education School of Internet of Things EngineeringJiangnan UniversityWuxiJiangsu214122China

Double-integrator multi-agent systems(MASs)might not achieve dynamical consensus,even if only partial agents suffer from self-sensing function failures(SSFFs).SSFFs might be asynchronous in real engineering *** existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous *** by these facts,this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous ***,multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal ***,a fault-tolerant dynamical consensus protocol is designed for double-integrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set ***,it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously,double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical ***,comparison numerical simulations are given to illustrate the effectiveness of the theoretical results.

关键词： double-integrator multi-agent systems asynchronous self-sensing function failures fault-tolerant dynamical consensus network topology connectivity recovery

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A Correlation-Based Stochastic Model for Massive MIMO Channel

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China Communications 2024年第1期21卷 175-187页

作者： Yang Liu Gang Li Chengxiang Wang National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast UniversityNanjing 211189China school of internet of things engineering Jiangnan UniversityWuxi 214122China Pervasive Communication Research Center Purple Mountain LaboratoriesNanjing 211111China

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the *** measurements were carried out to evaluate the performance of this proposed ***,the physical implications of this model were illustrated and the capacities are *** addition,the azimuthal power spectrum(APS)of several models was ***,the channel hardening effect was simulated and *** showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger ***,the proposed model can provide better tradeoff between accuracy and complexity in channel *** CIRM model can be used for massive MIMO design in the future communication system design.

关键词： CBSM channel capacity channel hardening channel modeling massive MIMO

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Multi-user reinforcement learning based task migration in mobile edge computing

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Frontiers of Computer Science 2024年第4期18卷 161-173页

作者： Yuya CUI Degan ZHANG Jie ZHANG Ting ZHANG Lixiang CAO Lu CHEN Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of TechnologyTianjin 300384China school of internet of things engineering Jiangsu Vocational College of Information TechnologyWuxi 214153China school of Electronic and information engineering Beijing Jiaotong UniversityBeijing 100044China school of Sports Economics and Management Tianjin University of SportTianjin 301617China

Mobile Edge Computing(MEC)is a promising *** service migration is a key technology in *** order to maintain the continuity of services in a dynamic environment,mobile users need to migrate tasks between multiple servers in real *** to the uncertainty of movement,frequent migration will increase delays and costs and non-migration will lead to service ***,it is very challenging to design an optimal migration *** this paper,we investigate the multi-user task migration problem in a dynamic environment and minimizes the average service delay while meeting the migration *** order to optimize the service delay and migration cost,we propose an adaptive weight deep deterministic policy gradient(AWDDPG)*** distributed execution and centralized training are adopted to solve the high-dimensional *** show that the proposed algorithm can greatly reduce the migration cost and service delay compared with the other related algorithms.

关键词： mobile edge computing mobility service migration deep reinforcement learning deep deterministic policy gradient

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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua Song Ge Chen Hongcai Zhang State Key Laboratory of internet of things for Smart City and Department of Electrical and Computer engineering University of MacaoMacao 999078China school of Electrical and Computer engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

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Integrated Clustering and Routing Design and Triangle Path Optimization for UAV-Assisted Wireless Sensor Networks

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China Communications 2024年第4期21卷 178-192页

作者： Shao Liwei Qian Liping Wu Mengru Wu Yuan College of information engineering Zhejiang University of TechnologyHangzhou 310014China State Key Laboratory of internet of things for Smart City University of MacaoMacaoChina Department of Computer and information Science University of MacaoMacaoChina

With the development of the internet of things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower ***,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery *** this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this ***,we use UAVs to assist the WSN in collecting *** the current UAV-assisted WSN,the clustering and routing schemes are determined ***,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and *** efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing *** the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing ***,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution *** point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor *** avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are *** emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of *** with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.

关键词： Monte-Las search strategy triangle path optimization unmanned aerial vehicles wireless sensor networks

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HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

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Computers, Materials & Continua 2024年第4期79卷 1089-1103页

作者： Wuyan Liang Xiaolong Xu school of internet of things Nanjing University of Posts and TelecommunicationsNanjing210023China school of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210023China

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input ***, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, *** specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

关键词： Gesture action recognition multi-dimensional attention pseudo-3D skeletal heatmap

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A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua Song College of Electrical engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of internet of things for Smart City and Department of Electrical and Computer engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow

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AI-Driven Energy Optimization in UAV-Assisted Routing for Enhanced Wireless Sensor Networks Performance

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Computers, Materials & Continua 2024年第9期80卷 4085-4110页

作者： Syed Kamran Haider Abbas Ahmed Noman Mujeeb Khan Ali Nauman Sung Won Kim College of internet of things(IoT)engineering Hohai UniversityChangzhou213001China Department of Electrical and Electronics engineering Beaconhouse International CollegeIslamabad44000Pakistan school of Computer Science and engineering Yeungnam UniversityGyeongsan38428Republic of Korea

In recent advancements within wireless sensor networks(WSN),the deployment of unmanned aerial vehicles(UAVs)has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network *** research introduces a sophisticated framework,driven by computational intelligence,that merges clustering techniques with UAV mobility to refine routing strategies in *** proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads(CHs).This system is primarily aimed at reducing energy consumption through meticulously planned routing and path *** a greedy algorithm for inter-cluster dialogue,our framework orchestrates CHs into an efficient communication *** comparative analysis,the proposed model demonstrates a marked improvement over traditional methods such as the cluster chain mobile agent routing(CCMAR)and the energy-efficient cluster-based dynamic algorithms(ECCRA).Specifically,it showcases an impressive 15%increase in energy conservation and a 20%reduction in data transmission time,highlighting its advanced ***,this paper investigates the impact of various network parameters on the efficiency and robustness of the WSN,emphasizing the vital role of sophisticated computational strategies in optimizing network operations.

关键词： UAV trajectory clustering next-generation wireless sensor network(NGWSN) energy efficiency mobile sink

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Mechanism analysis of foam penetration in EPB shield tunnelling with a focus on FER and soil particle size

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Underground Space 2024年第4期17卷 170-187页

作者： He Huang Quan Sun Tao Xu Wanhuan Zhou State Key Laboratory of internet of things for Smart City and Department of Civil and Environmental engineering University of MacaoMacao 999078China Department of Civil and Environmental engineering University of MacaoMacao 999078China school of Transportation Southeast UniversityNanjing 210000China

Parameters of foam penetration in earth pressure balance(EPB)shield tunnelling,such as permeability coefficients and penetration distances,significantly impact tunnel face ***,existing studies have faced inaccuracies in analysing these parameters due to imitations in experimental *** study addresses this issue by employing enhanced methods for a more precise analysis of foam *** involving three distinct sand types(coarse,medium,and fine)and three foam expansion ratios(FER)(10,15,and 20)are conducted using a modified model test *** from a novel computer vision-based method,the model test outcomes unveil two distinct foam penetration paths:liquid migration(L_(w))and bubble migration(L_(f)).Three penetration phases-namely,injection,blockage&drainage,and breakage—are identified based on L_(w)and L_(f)*** initial"injection"phase conforms to Darcy’s law and is amenable to mathematical *** foam with FER of 15 has the maximum viscosity and,hence the L_(f)and permeability in the penetration tests with FER of 15 are the lowest in the same *** bubble size distribution of foam with different FER shows minor ***,the characteristics of foam penetration vary due to the distinct particle size distribution(PSD)of different *** penetration creates low-permeability layers in both medium and fine sands due to the larger bubble size of the foam compared to the estimated pore sizes of medium and fine *** the coarse sand results in a different situation due to its large pore *** distinctive characteristics of foam penetration in different sand strata are notably shaped by FER,PSD,and pore size *** insights shed light on the complex interactions during foam penetration at the tunnel face,contributing valuable knowledge to EPB shield tunnelling practices.

关键词： EPB Soil conditioning Foam penetration Permeability Tunnel face

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Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

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Digital Communications and Networks 2024年第1期10卷 109-116页

作者： Xiaoming He Yingchi Mao Yinqiu Liu Ping Ping Yan Hong Han Hu The College of Computer and information Hohai UniversityNanjingChina The Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing China The school of Computer Science and engineering Nanyang Technological UniversitySingapore The College of Textile and Clothing engineering Soochow UniversitySuzhouChina The College of internet of things Nanjing University of Posts and TelecomurunicationsNanjingChina

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference ***,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable *** the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign ***,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power ***,agents in the collection stage slow down,which hinders the learning of other ***,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler *** experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

关键词： B5G Heterogeneous edge networks PPO Channel assignment Power allocation Throughput

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