检索结果-内蒙古大学图书馆

DRLO: Optimizing edge server placement in dynamic MEC scenarios using deep reinforcement learning

Computer Networks 2025年 268卷

作者： Guo, Yingya Chen, Cen College of Computer and Data Science Fuzhou University China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University China Engineering Research Center of Big Data Intelligence Ministry of Education Fujian China

As an emerging computing paradigm, Mobile Edge Computing (MEC) significantly enhances user experience and alleviates network congestion by strategically deploying edge servers in close proximity to mobile users. However, the effectiveness of MEC hinges on the precise placement of these edge servers, a critical factor in determining the Quality of Experience (QoE) for mobile users. While existing studies predominantly focus on optimizing edge server placement in static scenarios, they often fall short when faced with user mobility, resulting in a degradation of QoE. To address this challenge, we propose an adaptive edge server placement approach that leverages Deep Reinforcement Learning (DRL) to select the base stations for placing edge servers in a dynamic MEC environment. Our objective is to minimize access delay by optimizing edge server placement for adapting to dynamic environment. To tackle the vast action space associated with edge server placement, we introduce a novel activation function in the actor neural network for efficient exploration. Furthermore, to enhance the adaptability of the derived edge server placement strategy, we meticulously design a new reward function, which takes into account the minimization of total access delay within dynamic MEC scenarios. Finally, to validate the effectiveness of our proposed method, extensive experiments were conducted using the Shanghai Telecom dataset. The results demonstrate that our approach outperforms baseline methods in minimizing access delay for users in dynamic MEC scenarios. © 2025 Elsevier B.V.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Chirality-2 fermion induced Anti-Klein tunneling in 2D checkerboard lattice

arXiv

引用

arXiv 2024年

作者： Hua, Jiannan Wang, Z.F. Zhu, W. Chen, Weiwei Department of Physics School of Science Westlake University Zhejiang Hangzhou310024 China Institute of Natural Sciences Westlake Institute for Advanced Study Zhejiang Hangzhou310024 China Hefei National Research Center for Physical Sciences at the Microscale CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics Department of Physics University of Science and Technology of China Anhui Hefei230026 China Hefei National Laboratory University of Science and Technology of China Anhui Hefei230088 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province College of Science China Jiliang University Hangzhou310018 China

The quantum tunneling effect in the two-dimensional (2D) checkerboard lattice is investigated. By analyzing the pseudospin texture of the states in a 2D checkerboard lattice based on the low-energy effective Hamiltonian, we find that this system has a chiral symmetry with chirality equal to 2. Although compared to regular chiral fermions, its pseudospin orientation does not vary uniformly. This suggests that the perfect reflection chiral tunneling, also known as the anti-Klein tunneling, is expected to appear in checkerboard lattice as well. In order to verify the conjecture, we calculate the transmission probability and find that normally incident electron states can be perfectly reflected by the barrier with hole states inside, and vice versa. Furthermore, we also numerically calculate the tunneling conductance of the checkerboard nanotube using the recursive Green’s function method. The results show that a perfect on-off ratio can be achieved by confining the energy of the incident states within a certain range. It also suggests that, by tuning the barrier, the checkerboard nanotube is able to work as a perfect "band filter" or "tunneling field effect transistor", which transmits electrons selectively with respect to the pseudospin of the incident electrons. Copyright © 2024, The Authors. All rights reserved.

关键词： Nanotubes

来源：评论

学校读者我要写书评

暂无评论

A Recommendation Method for Highly Sparse dataset Based on Teaching Recommendation Factorization Machines

引用

Computers, Materials & Continua 2020年第9期64卷 1959-1975页

作者： Dunhong Yao Shijun Li Ang Li Yu Chen School of Computer Science and Engineering Huaihua UniversityHuaihua418000China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000China School of Computer Wuhan UniversityWuhan430072China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA School of Computer Science and Engineering Yulin Normal UniversityYulin537000China

There is no reasonable scientific basis for selecting the excellent teachers of the school’s *** solve the practical problem,we firstly give a series of normalization models for defining the key attributes of teachers’professional foundation,course difficulty coefficient,and comprehensive evaluation of ***,we define a partial weight function to calculate the key attributes,and obtain the partial recommendation ***,we construct a highly sparse Teaching Recommendation Factorization Machines(TRFMs)model,which takes the 5-tuples relation including teacher,course,teachers’professional foundation,course difficulty,teaching evaluation as the feature vector,and take partial recommendation value as the recommendation ***,we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse *** results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching *** recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse *** proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools,which can effectively improve the teaching quality.

关键词： Highly sparse dataset normalized models teaching recommendation factorization machines excellent teacher recommendation

来源：评论

学校读者我要写书评

暂无评论

TSC-ECFA:A Trusted Service Composition Scheme for Edge Cloud

TSC-ECFA:A Trusted Service Composition Scheme for Edge Cloud

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yu Jiang Xiaolong Xu Kunda Lin Weihua Duan Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781665408790

In order to select a composition scheme that meets user's needs and high performance from large-scale web services in the edge cloud, this paper proposes a trusted service composition optimization scheme called TSC-ECFA for edge cloud, which applies the predation strategy to the firefly algorithm (FA) and divides the services with the same input and output into one category, reducing the number of combinations to search for feasible solutions. The cotangent chaos theory is used to generate the initial firefly population and disturb the location of the individual to improve the overall search efficiency of FA. This paper also improves the step factor and attractiveness formula of FA to give full play to the detection ability of the step factor in the early stage of the algorithm, and balance the local search and the global search. Considering that the QoS attribute values of the service are vulnerable to be tampered with, the blockchain is used to store the QoS attribute values to ensure the tamper-proof and reliability of the QoS attribute value. Finally, simulation experiments compare the number of iterations and optimization of the three algorithms. The experimental results show that the comprehensive performance of TSC-ECFA is better than other algorithms.

关键词： Chaos Web services Conferences Sociology Quality of service Reliability theory Blockchains

来源：评论

学校读者我要写书评

暂无评论

A Recommender System Based on Model Regularization Wasserstein Generative Adversarial Network*

A Recommender System Based on Model Regularization Wasserste...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Qingxian Wang Qing Huang Kangkang Ma Xuerui Zhang School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China

ISBN: (纸本)9781665442084

A recommender system (RS) commonly adopts a High-dimensional and sparse (HiDS) matrix to describe user-item preferences. Collaborative Filtering (CF)-based models have been widely adopted to address such an HiDS matrix. However, a CF-based model is unable to learn the property distribution characteristic of user’s preference from an HiDS matrix, thereby its representation ability is limited. To address this issue, this paper proposes a Model Regularization Wasserstein GAN(MRWGAN) to extract the distribution of user’s preferences. Its main ideas are two-fold: a) adopting an auto-encoder to implement the generator model of GAN; b) proposing a model-regularized Wasserstein distance as an objective function to training a GAN model. Empirical studies on four HiDS matrices from industrial applications demonstrate that compared with state-of-the-art models, the proposed model achieves higher prediction accuracy for missing data of an HiDS matrix.

关键词： Training Analytical models Predictive models Generative adversarial networks Linear programming data models Sparse matrices

来源：评论

学校读者我要写书评

暂无评论

Array optimization for MIMO radar based on harmony search mechanism

Array optimization for MIMO radar based on harmony search me...

引用

IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Ling Jiang Yi Jiang Guimin Shi Zhongjie Xiao School of Mathematics and Computer Wuyi University Wuyishan China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan China Digital Fujian Tourism Big Data Institute Wuyishan China Big Data Development Administration of Anji County Huzhou China

ISBN: (纸本)9781728194202

In order to overcome the premarure risk of differential evolution algorithm, harmony search mechanism is introduced to optimize the pattern synthesis of multiple input and multiple output radar. Firstly, the memory of harmony search receives the optimizing results of differential evolution algorithm. And then it disturbs the local best to achieve better global optimization results. The advantage of novel method than standard differential evolution is tested with benchmark function while it can also maintain the diversity of population. What's more, several experiments are conducted to show that the optimal peak side lobe level and convergence performance have been achieved better through the proposed algorithm for multiple input and multiple output radar.

关键词： MIMO radar Sociology Education Radar Statistics Information technology Optimization

来源：评论

学校读者我要写书评

暂无评论

Dual-Channel Recalibration and Feature Fusion Method for Liver Image Classification 17th

Dual-Channel Recalibration and Feature Fusion Method for Liv...

引用

17th International Conference on intelligent Computing, ICIC 2021

作者： Niu, Tingting Zhang, Xiaolong Deng, Chunhua Chen, Ruoqin School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan China Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan China Tianyou Hospital Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9783030845285

Aiming at the problem of poor medical image recognition accuracy caused by the large individual differences in liver pathological images and the large single feature size, a liver image classification method based on dual-channel recalibration and feature fusion is proposed. Firstly, we construct a dual-channel recalibration model based on attention mechanism, suppress useless features and calculate different feature channel weights, and embed them into the Inception_ResNet_V2 network structure. Secondly, we design fully connected layers on the basis of two-dimensional and three-dimensional convolutional neural networks, then add feature fusion layers to obtain deep semantic information in different dimensions. Finally, we use pre-training models to initialize the network structure and input the fused features into the XGBoost classifier for classification prediction. Experiments have been carried out with liver cancer race imaging datasets and a hospital patient dataset. Experimental results show that this method is superior to previous ones. © 2021, Springer Nature Switzerland AG.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Blockchain-Based Identity Authentication Scheme for Mobile Crowd Sensing

SSRN

引用

SSRN 2022年

作者： Taochun, Wang Huimin, Shen Jian, Chen Fulong, Chen Qingshan, Wu Dong, Xie School of Computer and Information Anhui Normal University Wuhu241002 China Anhui Engineering Research Centers of Medical Big Data Intelligent System Anhui Normal University Wuhu241002 China Anhui Key Laboratory of Network and Information Security Anhui Normal University Wuhu241002 China

With the continuous innovation and popularization of mobile smart devices, the application of Mobile Crowd Sensing (MCS) has been widely studied. However, the existing centralized MCS applications that use servers for task publishing and data collection have common problems such as a single point of failure and privacy protection. Based on this, we proposes a hybrid blockchain-based identity authentication scheme for MCS named HBIA, which uses blockchain technology to solve the single point failure problem of MCS. HBIA builds a cluster structure based on factors such as geographical location and balance, and uses this to build a hybrid blockchain, with the cluster head node and the node within the cluster authenticating on the public chain and the private chain respectively, and the use of Zero-knowledge proof(ZKP) to ensure the identity privacy of participants, thus balancing the contradiction between blockchain transparency and participant identity privacy. In addition, HBIA uses zero-knowledge succinct non-interactive argument of knowledge(zk-SNARKs) technology to implement off-chain computing and on-chain verification, further reducing the workload of the blockchain. Finally, the HBIA scheme was tested on the Ethereum public test network Ropsten, and the test results showed that the identity authentication scheme proposed in this paper has advantages in execution time and throughput. © 2022, The Authors. All rights reserved.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

RETRACTED ARTICLE: Innovation in Rural Finance: Microfinance’s Impact on Prosperity and Efficiency in China

引用

Journal of the Knowledge Economy 2024年第1期16卷 5-5页

作者： Shen, Jumei Lu, Yali School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan China

来源：评论

学校读者我要写书评

暂无评论

A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN 17th

A Stepwise Path Selection Scheme Based on Multiple QoS Param...

引用

17th EAI International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2021

作者： Liu, Lin Zhou, Jian-Tao Xing, Hai-Feng Guo, Xiao-Yong College of Computer Science Ecological Big Data Engineering Research Center of the Ministry of Education Cloud Computing and Service Software Engineering Laboratory of Inner Mongolia Autonomous Region National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Social Computing and Data Processing Key Laboratory of Inner Mongolia Autonomous Region Big Data Analysis Technology Engineering Research Center of Inner Mongolia Autonomous Region Inner Mongolia University Inner Mongolia Hohhot China College of Computer Science and Technology Inner Mongolia Normal University Inner Mongolia Hohhot China College of Computer Information and Management Inner Mongolia University of Finance and Economics Inner Mongolia Hohhot China

ISBN: (纸本)9783030926342

Nowadays, the best-effort service can not guarantee the quality of service (QoS) for all kinds of services. QoS routing is an important method to guarantee QoS requirements. It involves path selection for flows based on the current network status and the performance criteria of the service requirements. However, it is difficult for proposed solutions to obtain all the available paths owing to not fully considering all the QoS parameters of paths. In this paper, we propose SWQoS, a novel, universal, and stepwise QoS guarantee scheme based on multiple QoS parameter evaluation for selecting the available paths including preferred paths, satisfied paths and reluctant paths in SDN. The experiments show that SWQoS can select all the available paths that meet the performance criteria of the service requirements and have better QoS parameter performance compared with other path selection methods. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：