期刊文献+
共找到68,965篇文章
< 1 2 250 >
每页显示 20 50 100
240 nm AlGaN-based deep ultraviolet micro-LEDs:size effect versus edge effect 被引量:2
1
作者 Shunpeng Lu Jiangxiao Bai +6 位作者 Hongbo Li Ke Jiang Jianwei Ben Shanli Zhang Zi-Hui Zhang Xiaojuan Sun Dabing Li 《Journal of Semiconductors》 EI CAS CSCD 2024年第1期55-62,共8页
240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge ef... 240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge effects.Here,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μm.Thereinto,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light extraction.Most notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector design.However,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized ones.The underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further shrinking.Moreover,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa edge.These findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs. 展开更多
关键词 ALGAN deep ultraviolet micro-LEDs light extraction efficiency size effect edge effect
下载PDF
Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities 被引量:1
2
作者 Qin Zhen He Shoushuai +5 位作者 Wang Hai Qu Yuben Dai Haipeng Xiong Fei Wei Zhenhua Li Hailong 《China Communications》 SCIE CSCD 2024年第5期1-16,共16页
By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-grow... By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC. 展开更多
关键词 air-ground architecture COLLABORATIVE mobile edge computing
下载PDF
Edge enhanced depth perception with binocular meta-lens 被引量:2
3
作者 Xiaoyuan Liu Jingcheng Zhang +5 位作者 Borui Leng Yin Zhou Jialuo Cheng Takeshi Yamaguchi Takuo Tanaka Mu Ku Chen 《Opto-Electronic Science》 2024年第9期4-13,共10页
The increasing popularity of the metaverse has led to a growing interest and market size in spatial computing from both academia and industry.Developing portable and accurate imaging and depth sensing systems is cruci... The increasing popularity of the metaverse has led to a growing interest and market size in spatial computing from both academia and industry.Developing portable and accurate imaging and depth sensing systems is crucial for advancing next-generation virtual reality devices.This work demonstrates an intelligent,lightweight,and compact edge-enhanced depth perception system that utilizes a binocular meta-lens for spatial computing.The miniaturized system comprises a binocular meta-lens,a 532 nm filter,and a CMOS sensor.For disparity computation,we propose a stereo-matching neural network with a novel H-Module.The H-Module incorporates an attention mechanism into the Siamese network.The symmetric architecture,with cross-pixel interaction and cross-view interaction,enables a more comprehensive analysis of contextual information in stereo images.Based on spatial intensity discontinuity,the edge enhancement eliminates illposed regions in the image where ambiguous depth predictions may occur due to a lack of texture.With the assistance of deep learning,our edge-enhanced system provides prompt responses in less than 0.15 seconds.This edge-enhanced depth perception meta-lens imaging system will significantly contribute to accurate 3D scene modeling,machine vision,autonomous driving,and robotics development. 展开更多
关键词 metasurfaces meta-lenses deep learning depth perception edge detection
下载PDF
Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing 被引量:1
4
作者 Zhang Cui Xu Xiao +4 位作者 Wu Qiong Fan Pingyi Fan Qiang Zhu Huiling Wang Jiangzhou 《China Communications》 SCIE CSCD 2024年第8期1-17,共17页
In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amount... In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model. 展开更多
关键词 asynchronous federated learning byzantine attacks vehicle selection vehicular edge computing
下载PDF
Graph CA: Learning From Graph Counterfactual Augmentation for Knowledge Tracing
5
作者 Xinhua Wang Shasha Zhao +3 位作者 Lei Guo Lei Zhu Chaoran Cui Liancheng Xu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2023年第11期2108-2123,共16页
With the popularity of online learning in educational settings, knowledge tracing(KT) plays an increasingly significant role. The task of KT is to help students learn more effectively by predicting their next mastery ... With the popularity of online learning in educational settings, knowledge tracing(KT) plays an increasingly significant role. The task of KT is to help students learn more effectively by predicting their next mastery of knowledge based on their historical exercise sequences. Nowadays, many related works have emerged in this field, such as Bayesian knowledge tracing and deep knowledge tracing methods. Despite the progress that has been made in KT, existing techniques still have the following limitations: 1) Previous studies address KT by only exploring the observational sparsity data distribution, and the counterfactual data distribution has been largely ignored. 2) Current works designed for KT only consider either the entity relationships between questions and concepts, or the relations between two concepts, and none of them investigates the relations among students, questions, and concepts, simultaneously, leading to inaccurate student modeling. To address the above limitations,we propose a graph counterfactual augmentation method for knowledge tracing. Concretely, to consider the multiple relationships among different entities, we first uniform students, questions, and concepts in graphs, and then leverage a heterogeneous graph convolutional network to conduct representation learning.To model the counterfactual world, we conduct counterfactual transformations on students’ learning graphs by changing the corresponding treatments and then exploit the counterfactual outcomes in a contrastive learning framework. We conduct extensive experiments on three real-world datasets, and the experimental results demonstrate the superiority of our proposed Graph CA method compared with several state-of-the-art baselines. 展开更多
关键词 Contrastive learning counterfactual representation graph neural network knowledge tracing
下载PDF
基于Solid Edge自动生成数控加工图的二次开发研究
6
作者 吴事谱 陆祉好 阳开应 《锅炉技术》 北大核心 2024年第4期21-26,共6页
基于Solid Edge软件平台,利用C#进行二次开发,设计出一款利用三维设计模型和组件图生成数控加工工艺图纸的批量设计软件,并详细展示了软件的工作流程、原理和关键技术。经应用验证,该软件具有出图快、信息匹配度高、适用模型范围广、操... 基于Solid Edge软件平台,利用C#进行二次开发,设计出一款利用三维设计模型和组件图生成数控加工工艺图纸的批量设计软件,并详细展示了软件的工作流程、原理和关键技术。经应用验证,该软件具有出图快、信息匹配度高、适用模型范围广、操作灵活、界面友好等优点,以此实现了车间的无纸化高效数据传输和敏捷生产。 展开更多
关键词 Solid edge 二次开发 数控加工图 轮廓图 C# 工程图 三维设计
下载PDF
基于KubeEdge的全国气象监视数据采集软件设计
7
作者 白金婷 罗飞 +5 位作者 孙超 张喜 罗谦 徐达 郭聪 段明静 《计算机技术与发展》 2024年第8期67-72,共6页
为解决气象综合业务实时监控系统(简称“天镜”)对全国气象监视数据采集汇聚安全性、高效性、灵活可管控能力不足的问题,更好地满足全国气象业务集中监视需求,基于“云边协同”的边缘计算KubeEdge架构设计并实现了“天镜”全国气象监视... 为解决气象综合业务实时监控系统(简称“天镜”)对全国气象监视数据采集汇聚安全性、高效性、灵活可管控能力不足的问题,更好地满足全国气象业务集中监视需求,基于“云边协同”的边缘计算KubeEdge架构设计并实现了“天镜”全国气象监视数据采集汇聚软件。国家级“天镜”采用KubeEdge内部通道传递应用程序的控制命令和状态信息,采用气象国省宽带网传输监视数据;采用脚本实现云边端离线自动部署;采用Harbor管理和分发镜像;基于KubeEdge的命令和状态信息实现节点、设备和任务的可视化管控,一体化管控全国边缘节点和采集任务,支持监视任务和数据上传的动态调整。实验结果表明,基于KubeEdge的全国气象监视数据采集汇聚软件有效提高了全国气象监视数据采集汇聚效率和灵活可管控能力,保障了数据传输的安全性。目前该软件已应用于各省(区、市)气象高质量发展通信网络指标评估、全国“天擎”集中监视、全国空间天气全链路状态监视,并取得了良好的业务效益。 展开更多
关键词 边缘计算 Kubeedge 云边协同 数据采集汇聚 灵活可管控 数据传输
下载PDF
gEdge:基于容器技术的云边协同的异构计算框架
8
作者 汪沄 汤冬劼 +2 位作者 郭开诚 戚正伟 管海兵 《计算机学报》 EI CAS CSCD 北大核心 2024年第8期1883-1900,共18页
由于按需灵活配置、高可用性、高资源利用率等优点,云计算技术成为过去十年的主流计算范式.随着万物互联时代的到来,单独依赖云计算技术已经无法满足数以亿计的IoT设备及其数据流量的需求.边缘计算可以被看作是云计算的进化,它因5G网络... 由于按需灵活配置、高可用性、高资源利用率等优点,云计算技术成为过去十年的主流计算范式.随着万物互联时代的到来,单独依赖云计算技术已经无法满足数以亿计的IoT设备及其数据流量的需求.边缘计算可以被看作是云计算的进化,它因5G网络和物联网的崛起而诞生.随着云游戏、VR技术以及人工智能技术在日常生活中的广泛运用,对计算资源的需求也在日渐增长.然而,受体积与功耗限制,处于边缘的节点设备算力较弱.本文提出了gEdge:一种基于容器技术的云边协同的异构计算框架.该框架通过GPU虚拟化技术,将云端的物理GPU资源分为多块虚拟GPU资源,按需为边缘节点提供GPU算力资源,并且对用户容器无感知.实验表明,使用gEdge框架使边缘节点使用的容器镜像体积降低了48.8%,容器启动时间降低了35.5%,平均相对运行速度提高了213%. 展开更多
关键词 图形处理器 虚拟化技术 容器技术 边缘计算 云边协同
下载PDF
Security Implications of Edge Computing in Cloud Networks 被引量:1
9
作者 Sina Ahmadi 《Journal of Computer and Communications》 2024年第2期26-46,共21页
Security issues in cloud networks and edge computing have become very common. This research focuses on analyzing such issues and developing the best solutions. A detailed literature review has been conducted in this r... Security issues in cloud networks and edge computing have become very common. This research focuses on analyzing such issues and developing the best solutions. A detailed literature review has been conducted in this regard. The findings have shown that many challenges are linked to edge computing, such as privacy concerns, security breaches, high costs, low efficiency, etc. Therefore, there is a need to implement proper security measures to overcome these issues. Using emerging trends, like machine learning, encryption, artificial intelligence, real-time monitoring, etc., can help mitigate security issues. They can also develop a secure and safe future in cloud computing. It was concluded that the security implications of edge computing can easily be covered with the help of new technologies and techniques. 展开更多
关键词 edge Computing Cloud Networks Artificial Intelligence Machine Learning Cloud Security
下载PDF
IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks 被引量:1
10
作者 Ying Zhang Weiming Niu Leibing Yan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第1期885-902,共18页
In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of ... In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes. 展开更多
关键词 Mobile edge computing(MEC) unmanned aerial vehicle(UAV) intelligent reflecting surface(IRS) zero forcing(ZF)
下载PDF
A review on edge analytics:Issues,challenges,opportunities,promises,future directions,and applications
11
作者 Sabuzima Nayak Ripon Patgiri +1 位作者 Lilapati Waikhom Arif Ahmed 《Digital Communications and Networks》 SCIE CSCD 2024年第3期783-804,共22页
Edge technology aims to bring cloud resources(specifically,the computation,storage,and network)to the closed proximity of the edge devices,i.e.,smart devices where the data are produced and consumed.Embedding computin... Edge technology aims to bring cloud resources(specifically,the computation,storage,and network)to the closed proximity of the edge devices,i.e.,smart devices where the data are produced and consumed.Embedding computing and application in edge devices lead to emerging of two new concepts in edge technology:edge computing and edge analytics.Edge analytics uses some techniques or algorithms to analyse the data generated by the edge devices.With the emerging of edge analytics,the edge devices have become a complete set.Currently,edge analytics is unable to provide full support to the analytic techniques.The edge devices cannot execute advanced and sophisticated analytic algorithms following various constraints such as limited power supply,small memory size,limited resources,etc.This article aims to provide a detailed discussion on edge analytics.The key contributions of the paper are as follows-a clear explanation to distinguish between the three concepts of edge technology:edge devices,edge computing,and edge analytics,along with their issues.In addition,the article discusses the implementation of edge analytics to solve many problems and applications in various areas such as retail,agriculture,industry,and healthcare.Moreover,the research papers of the state-of-the-art edge analytics are rigorously reviewed in this article to explore the existing issues,emerging challenges,research opportunities and their directions,and applications. 展开更多
关键词 edge analytics edge computing edge devices Big data Sensor Artificial intelligence Machine learning Smart technology Healthcare
下载PDF
Edge modes in finite-size systems with different edge terminals
12
作者 Huiping Wang Li Ren +1 位作者 Xiuli Zhang Liguo Qin 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第10期381-387,共7页
We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q... We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q-…”and type II:“…=P-Q=P-Q=…”),where P and Q represent crystal lines(CLs),while the symbols“-”and“=”denote the distance between the nearest neighbor(NN)CLs.Based on the lattice model Hamiltonian with LR hopping,the existence of edge modes is determined analytically by using the transfer matrix method(TMM)when different edge terminals are taken into consideration.Our findings are consistent with the numerical results obtained by the exact diagonalization method.We also notice that edge modes can exhibit different behaviors under different edge terminals.Our result is helpful in solving novel edge modes in honeycomb crystalline graphene and transition metal dichalcogenides with different edge terminals. 展开更多
关键词 edge modes long-range hopping different edge terminals
下载PDF
Task Offloading in Edge Computing Using GNNs and DQN
13
作者 Asier Garmendia-Orbegozo Jose David Nunez-Gonzalez Miguel Angel Anton 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第6期2649-2671,共23页
In a network environment composed of different types of computing centers that can be divided into different layers(clod,edge layer,and others),the interconnection between them offers the possibility of peer-to-peer t... In a network environment composed of different types of computing centers that can be divided into different layers(clod,edge layer,and others),the interconnection between them offers the possibility of peer-to-peer task offloading.For many resource-constrained devices,the computation of many types of tasks is not feasible because they cannot support such computations as they do not have enough available memory and processing capacity.In this scenario,it is worth considering transferring these tasks to resource-rich platforms,such as Edge Data Centers or remote cloud servers.For different reasons,it is more exciting and appropriate to download various tasks to specific download destinations depending on the properties and state of the environment and the nature of the functions.At the same time,establishing an optimal offloading policy,which ensures that all tasks are executed within the required latency and avoids excessive workload on specific computing centers is not easy.This study presents two alternatives to solve the offloading decision paradigm by introducing two well-known algorithms,Graph Neural Networks(GNN)and Deep Q-Network(DQN).It applies the alternatives on a well-known Edge Computing simulator called PureEdgeSimand compares them with the two defaultmethods,Trade-Off and Round Robin.Experiments showed that variants offer a slight improvement in task success rate and workload distribution.In terms of energy efficiency,they provided similar results.Finally,the success rates of different computing centers are tested,and the lack of capacity of remote cloud servers to respond to applications in real-time is demonstrated.These novel ways of finding a download strategy in a local networking environment are unique as they emulate the state and structure of the environment innovatively,considering the quality of its connections and constant updates.The download score defined in this research is a crucial feature for determining the quality of a download path in the GNN training process and has not previously been proposed.Simultaneously,the suitability of Reinforcement Learning(RL)techniques is demonstrated due to the dynamism of the network environment,considering all the key factors that affect the decision to offload a given task,including the actual state of all devices. 展开更多
关键词 edge computing edge offloading fog computing task offloading
下载PDF
Digital Twin-Assisted Semi-Federated Learning Framework for Industrial Edge Intelligence
14
作者 Wu Xiongyue Tang Jianhua Marie Siew 《China Communications》 SCIE CSCD 2024年第5期314-329,共16页
The rapid development of emerging technologies,such as edge intelligence and digital twins,have added momentum towards the development of the Industrial Internet of Things(IIo T).However,the massive amount of data gen... The rapid development of emerging technologies,such as edge intelligence and digital twins,have added momentum towards the development of the Industrial Internet of Things(IIo T).However,the massive amount of data generated by the IIo T,coupled with heterogeneous computation capacity across IIo T devices,and users’data privacy concerns,have posed challenges towards achieving industrial edge intelligence(IEI).To achieve IEI,in this paper,we propose a semi-federated learning framework where a portion of the data with higher privacy is kept locally and a portion of the less private data can be potentially uploaded to the edge server.In addition,we leverage digital twins to overcome the problem of computation capacity heterogeneity of IIo T devices through the mapping of physical entities.We formulate a synchronization latency minimization problem which jointly optimizes edge association and the proportion of uploaded nonprivate data.As the joint problem is NP-hard and combinatorial and taking into account the reality of largescale device training,we develop a multi-agent hybrid action deep reinforcement learning(DRL)algorithm to find the optimal solution.Simulation results show that our proposed DRL algorithm can reduce latency and have a better convergence performance for semi-federated learning compared to benchmark algorithms. 展开更多
关键词 digital twin edge association industrial edge intelligence(IEI) semi-federated learning
下载PDF
Mobility edges and localization characteristics in one-dimensional quasiperiodic quantum walk
15
作者 崔鑫辉 王慧敏 李志坚 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第6期156-160,共5页
We construct a one-dimensional quasiperiodic quantum walk to investigate the localization–delocalization transition.The inverse participation ratio and Lyapunov exponent are employed as two indexes to determine the m... We construct a one-dimensional quasiperiodic quantum walk to investigate the localization–delocalization transition.The inverse participation ratio and Lyapunov exponent are employed as two indexes to determine the mobility edge, a critical energy to distinguish the energy regions of extended and localized states. The analytical solution of mobility edge is obtained by the Lyapunov exponents in global theory, and the consistency of the two indexes is confirmed. We further study the dynamic characteristics of the quantum walk and show that the probabilities are localized to some specific lattice sites with time evolution. This phenomenon is explained by the effective potential of the Hamiltonian which corresponds to the phase in the coin operator of the quantum walk. 展开更多
关键词 quantum walk mobility edges QUASIPERIODICITY
下载PDF
Real-Time Monitoring Method for Cow Rumination Behavior Based on Edge Computing and Improved MobileNet v3
16
作者 ZHANG Yu LI Xiangting +4 位作者 SUN Yalin XUE Aidi ZHANG Yi JIANG Hailong SHEN Weizheng 《智慧农业(中英文)》 CSCD 2024年第4期29-41,共13页
[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been propo... [Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings. 展开更多
关键词 cow rumination behavior real-time monitoring edge computing improved MobileNet v3 edge intelligence model Bi-LSTM
下载PDF
For Mega-Constellations: Edge Computing and Safety Management Based on Blockchain Technology
17
作者 Zhen Zhang Bing Guo Chengjie Li 《China Communications》 SCIE CSCD 2024年第2期59-73,共15页
In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of sate... In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication.While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed. 展开更多
关键词 blockchain consensus mechanism edge computing mega-constellation reputation management
下载PDF
Computing Resource Allocation for Blockchain-Based Mobile Edge Computing
18
作者 Wanbo Zhang Yuqi Fan +2 位作者 Jun Zhang Xu Ding Jung Yoon Kim 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期863-885,共23页
Users and edge servers are not fullymutually trusted inmobile edge computing(MEC),and hence blockchain can be introduced to provide trustableMEC.In blockchain-basedMEC,each edge server functions as a node in bothMEC a... Users and edge servers are not fullymutually trusted inmobile edge computing(MEC),and hence blockchain can be introduced to provide trustableMEC.In blockchain-basedMEC,each edge server functions as a node in bothMEC and blockchain,processing users’tasks and then uploading the task related information to the blockchain.That is,each edge server runs both users’offloaded tasks and blockchain tasks simultaneously.Note that there is a trade-off between the resource allocation for MEC and blockchain tasks.Therefore,the allocation of the resources of edge servers to the blockchain and theMEC is crucial for the processing delay of blockchain-based MEC.Most of the existing research tackles the problem of resource allocation in either blockchain or MEC,which leads to unfavorable performance of the blockchain-based MEC system.In this paper,we study how to allocate the computing resources of edge servers to the MEC and blockchain tasks with the aimtominimize the total systemprocessing delay.For the problem,we propose a computing resource Allocation algorithmfor Blockchain-based MEC(ABM)which utilizes the Slater’s condition,Karush-Kuhn-Tucker(KKT)conditions,partial derivatives of the Lagrangian function and subgradient projection method to obtain the solution.Simulation results show that ABM converges and effectively reduces the processing delay of blockchain-based MEC. 展开更多
关键词 Mobile edge computing blockchain resource allocation
下载PDF
IoT Task Offloading in Edge Computing Using Non-Cooperative Game Theory for Healthcare Systems
19
作者 Dinesh Mavaluru Chettupally Anil Carie +4 位作者 Ahmed I.Alutaibi Satish Anamalamudi Bayapa Reddy Narapureddy Murali Krishna Enduri Md Ezaz Ahmed 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1487-1503,共17页
In this paper,we present a comprehensive system model for Industrial Internet of Things(IIoT)networks empowered by Non-Orthogonal Multiple Access(NOMA)and Mobile Edge Computing(MEC)technologies.The network comprises e... In this paper,we present a comprehensive system model for Industrial Internet of Things(IIoT)networks empowered by Non-Orthogonal Multiple Access(NOMA)and Mobile Edge Computing(MEC)technologies.The network comprises essential components such as base stations,edge servers,and numerous IIoT devices characterized by limited energy and computing capacities.The central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy consumption.The system operates in discrete time slots and employs a quasi-static approach,with a specific focus on the complexities of task partitioning and the management of constrained resources within the IIoT context.This study makes valuable contributions to the field by enhancing the understanding of resourceefficient management and task allocation,particularly relevant in real-time industrial applications.Experimental results indicate that our proposed algorithmsignificantly outperforms existing approaches,reducing queue backlog by 45.32% and 17.25% compared to SMRA and ACRA while achieving a 27.31% and 74.12% improvement in Qn O.Moreover,the algorithmeffectively balances complexity and network performance,as demonstratedwhen reducing the number of devices in each group(Ng)from 200 to 50,resulting in a 97.21% reduction in complexity with only a 7.35% increase in energy consumption.This research offers a practical solution for optimizing IIoT networks in real-time industrial settings. 展开更多
关键词 Internet of Things edge computing OFFLOADING NOMA
下载PDF
A Fully-Integrated Memristor Chip for Edge Learning
20
作者 Yanhong Zhang Liang Chu Wenjun Li 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第9期123-127,共5页
It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning... It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning as artificial neural networks with functionality of synapses,dendrites,and somas.A crossbar-array memristor chip facilitated edge learning including hardware realization,learning algorithm,and cycle-parallel sign-and threshold-based learning(STELLAR)scheme.The motion control and demonstration platforms were executed to improve the edge learning ability for adapting to new scenarios. 展开更多
关键词 Computing in memory edge learning Fully-integrated chip
下载PDF
上一页 1 2 250 下一页 到第
使用帮助 返回顶部