检索结果-内蒙古大学图书馆

Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

Journal of computer science & Technology 2023年第4期38卷 773-792页

作者：田文洪徐敏贤周光耀吴逵须成忠 Rajkumar Buyya School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science University of VictoriaVictoriaBCV8W 3P6Canada State Key Laboratory of Internet of Things for Smart City University of MacaoMacao 999078China School of Computing and Information Systems University of MelbourneMelbourne 3010Australia

Load balancing is vital for the efficient and long-term operation of cloud data *** virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consoli***,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring ***,we provide a new approach,called Prepartition,for load *** partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM *** this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained *** with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_*** also extend Prepartition to online load *** results show that our proposed approach also outperforms state-of-the-art online algorithms.

关键词： cloud computing physical machine(PM) virtual machine(VM) reservation load balancing Prepartition

来源：评论

学校读者我要写书评

暂无评论

On the System Performance of Mobile Edge computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

引用

IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 668-685页

作者： Van-Truong Truong Van Nhan Vo Dac-Binh Ha Chakchai So-In the Faculty of Electrical-Electronic Engineering Duy Tan University the Institute of Research and Development Duy Tan University the Faculty of Information Technology Duy Tan University IEEE the Applied Network Technology(ANT)Laboratory Department of Computer ScienceCollege of ComputingKhon Kaen University

In this paper,we study the system performance of mobile edge computing(MEC)wireless sensor networks(WSNs)using a multiantenna access point(AP)and two sensor clusters based on uplink nonorthogonal multiple access(NOMA).Due to limited computation and energy resources,the cluster heads(CHs)offload their tasks to a multiantenna AP over Nakagami-m *** proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining(SC)or maximal ratio combining(MRC)and each cluster selects a CH to participate in the communication process by employing the sensor node(SN)*** derive the closed-form exact expressions of the successful computation probability(SCP)to evaluate the system performance with the latency and energy consumption constraints of the considered *** results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas,number of SNs in each cluster,task length,working frequency,offloading ratio,and transmit power ***,to determine the optimal resource parameters,i.e.,the offloading ratio,power allocation of the two CHs,and MEC AP resources,we proposed two algorithms to achieve the best system *** approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar *** use Monte Carlo simulations to confirm the validity of our analysis.

关键词： Mobile edge computing(MEC) Nakagami-m fading offloading selection combining(SC)/maximal ratio combining(MRC) successful computation probability(SCP) uplink nonortho-gonal multiple access(NOMA) wireless sensor networks(WSNs)

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Probabilistic Semantic Communication over SAGIN

Energy Efficient Probabilistic Semantic Communication over S...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhao, Zhouxiang Yang, Zhaohui Chen, Mingzhe Gan, Xu Huang, Chongwen Xu, Wei Zhang, Zhaoyang Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Hangzhou China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States Southeast University National Mobile Communications Research Laboratory Nanjing China

ISBN: (纸本)9798350351255

In this paper, the energy efficiency maximization problem in space-air-ground integrated network (SAGIN)-enabled probabilistic semantic communication (PSC) is investigated. In the considered model, a satellite needs to transmit data to multiple ground terminals (GTs) via an unmanned aerial vehicle (UAV) acting as a relay. During transmission, the satellite and the UAV can use PSC technique to compress the transmitted data, while the GTs can automatically recover the original data. In the considered PSC system, shared probability graphs serve as a common knowledge base among the transceivers, allowing for resource-saving communication at the expense of increased computation resource. Therefore, it is important to study the trade-off between communication and computation to achieve optimal energy efficiency. The joint communication and computation problem is formulated as an optimization problem aiming to minimize the total communication and computation energy consumption of the network under latency, semantic compression ratio, and UAV location constraints. To solve this non-convex problem, we propose an alternating algorithm. Numerical results show the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Correlation assisted in-line holographic imaging through scattering medium 13

Correlation assisted in-line holographic imaging through sca...

引用

Holography, Diffractive Optics, and Applications XIII 2023

作者： Vinu, R.V. Melath, Rathinn Nair Raghav, Sahmita Gopakumar, G. Chen, Ziyang Pu, Jixiong College of Information Science and Engineering Fujian Provincial Key Laboratory of Light Propagation and Transformation Huaqiao University Fujian Xiamen361021 China Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Kerala Amritapuri India

ISBN: (纸本)9781510667853

We propose and experimentally demonstrate a technique for the single-shot imaging through a scattering medium based on speckle correlation assisted digital in-line holography. The proposed method enables the reconstruction of the complex amplitude information of the object located at any arbitrary planes behind the scattering medium by retrieving the digital in-line hologram. The technique exploits the potential of speckle correlation approaches and machine learning schemes for the efficient reconstruction of complex amplitude information from the digital in-line hologram scrambled in the speckle pattern. The complex amplitude imaging capability of the proposed technique is theoretically introduced and experimentally validated by imaging various standard and unknown objects. © 2023 SPIE.

关键词： Speckle

来源：评论

学校读者我要写书评

暂无评论

Local and Global Feature-Aware Dual-Branch Networks for Plant Disease Recognition

引用

植物表型组学（英文） 2024年第4期6卷 828-840页

作者： Jianwu Lin Xin Zhang Yongbin Qin Shengxian Yang Xingtian Wen Tomislav Cernava Quirico Migheli Xiaoyulong Chen Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China School of Biological Sciences Faculty of Environmental and Life SciencesUniversity of SouthamptonSouthampton S017 1BJUK Dipartimento di Agraria and NRD-Nucleo di Ricerca sulla Desertificazione Università degli Studi di SassariSassariItaly Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Life Sciences Guizhou UniversityGuiyang 550025China

Accurate identification of plant diseases is important for ensuring the safety of agricultural *** neural networks(CNNs)and visual transformers(VTs)can extract effective representations of images and have been widely used for the intelligent recognition of plant disease ***,CNNs have excellent local perception with poor global perception,and VTs have excellent global perception with poor local *** makes it difficult to further improve the performance of both CNNs and VTs on plant disease recognition *** this paper,we propose a local and global feature-aware dual-branch network,named LGNet,for the identification of plant *** specifically,we first design a dual-branch structure based on CNNs and VTs to extract the local and global ***,an adaptive feature fusion(AFF)module is designed to fuse the local and global features,thus driving the model to dynamically perceive the weights of different ***,we design a hierarchical mixed-scale unit-guided feature fusion(HMUFF)module to mine the key information in the features at different levels and fuse the differentiated information among them,thereby enhancing the model's multiscale perception ***,extensive experiments were conducted on the Al Challenger 2018 dataset and the self-collected corn disease(SCD)*** experimental results demonstrate that our proposed LGNet achieves state-of-the-art recognition performance on both the Al Challenger 2018 dataset and the SCD dataset,with accuracies of 88.74％and 99.08％,respectively.

关键词： global plant disease dual-branch feature-aware local networks recognition

来源：评论

学校读者我要写书评

暂无评论

Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

引用

computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

来源：评论

学校读者我要写书评

暂无评论

Federated Meta Continual Learning for Efficient and Autonomous Edge Inference 24th

Federated Meta Continual Learning for Efficient and Autono...

引用

24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Li, Bingze Ho, Stella Qu, Youyang Xu, Chenhao Luan, Tom H. Gao, Longxiang Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Department of Biomedical Engineering The University of Melbourne VIC Melbourne Australia School of Information Technology Deakin University VIC Geelong Australia School of Cyber Engineering Xidian University Xi’an China

ISBN: (纸本)9789819615476

With an increasing volume of data being collected and processed on edge, Federated Learning (FL) has become a dominant approach to train shared global models on distributed data held by diverse edge clients without exposing privacy. However, with expectations of high-quality user experience, instantaneous intelligent decisions must be made at the network edge to meet performance, security, and latency requirements. Intuitively, this challenge becomes more daunting as edge devices are constrained by limited computing and storage resources. Furthermore, edge clients need to continuously acquire, update, accumulate, and apply knowledge in domains requiring the processing of sensitive data and long-term model training. It has been proven that edge clients often forget previous tasks knowledge after learning new tasks, resulting in catastrophic forgetting. To mitigate this, we propose a Federated Meta Continual Learning (FMCL) approach. It requires edge clients not only to learn new tasks quickly but also to memorize rapidly. Specifically, we adopted a MAML (Model-Agnostic Meta-Learning) framework with memory replay, setting up buffers at edge clients to consolidate old tasks. In such a way, the model learns optimal initialization to quickly adapt to all seen tasks while preventing catastrophic forgetting. Extensive evaluation results indicate that FMCL performs well in alleviating catastrophic forgetting and achieves a good balance between learning new tasks and remembering existing tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

引用

computer Systems science & engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud Mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed Mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

引用

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

来源：评论

学校读者我要写书评

暂无评论

Large Scale Model Enabled Semantic Communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ding, Kuiyuan Liu, Fangfang Yang, Yang Chen, Mingzhe Guo, Caili Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering The Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9798350351255

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC. © 2024 IEEE.

关键词： Channel coding

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：