检索结果-内蒙古大学图书馆

COMPRESSO: Latency-Aware Transmission of Compressed IoT Measurement Data Over SDN

IEEE Internet of Things Journal 2025年第12期12卷 20462-20472页

作者： Feng, Wendi Dou, Xintan Taherkordi, Amirhosein Cheng, Bo Zhang, Wei State Key Laboratory of Networking and Switching Technology China University of Oslo College of Computer Science Dept. of Informatics Norway State Key Laboratory of Networking and Switching Technology China

Measurement data obtained from "things"in the Internet of Things (IoT) faces challenges in efficient transmission due to the low-bandwidth data transmission *** observe that measurement data are fixed in size and format, and low-entropy in the time domain, indicating that compression can be benefited. Rather than employing a single compression algorithm as advocated in existing literature, we argue that optimal transmission can be achieved by jointly considering compression overheads and network status, where software-defined networking (SDN) is employed to enforce network statistics and packet forwarding. This paper presents a new paradigm that achieves optimal transmission of SDN-empowered compressed measurement data. We formulate the problem as an optimization problem and prove its non-polynomial hardness time complexity. Due to this complexity, we introduce COMPRESSO, a heuristic algorithm that efficiently solves the problem. We conduct rigorous simulations, and the results demonstrate the efficiency of the new paradigm and COMPRESSO, i.e., attaining comparable performance to the optimal solution with 50% time usage reduction. © 2014 IEEE.

关键词： Data transfer

来源：评论

学校读者我要写书评

暂无评论

Knowledge-enhanced semantic communication system with OFDM transmissions

引用

science China(Information sciences) 2023年第7期66卷 266-282页

作者： Xiaodong XU Huachao XIONG Yining WANG Yue CHE Shujun HAN Bizhu WANG Ping ZHANG State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Department of Broadband Communication Peng Cheng Laboratory

As a promising technology to enable effective multi-modal transmission over wireless channels,semantic communication has attracted a lot of attention from academics and industries. Different from Shannon's information theory, based on common background knowledge provided by the knowledge base, the goal of semantic communication is transmitting intended useful information from the transmitter and recovered by the receiver at the semantic level. However, the existing studies on semantic communication rarely emphasize the essence and the usage of the knowledge base. In this paper, we propose a knowledge-enhanced semantic communication(KESC) system, where the knowledge base is cloud-edge-device collaborative cached. To solve the problem that float-type symbols are difficult to transmit directly through a radio frequency(RF)system, we adopt orthogonal frequency division multiplexing(OFDM) to transmit semantic vectors directly without some traditional signal processing techniques in semantic information transmission, and the semantic pilot is designed to assist semantic reception. Furthermore, we formulate a multi-encoder transformer based neural network model for the KESC system to support text transmission(KESC-T), where the decoder is implemented with a knowledge graph to enhance the performance of semantic decoding. Besides, we define knowledge-enhanced efficiency(KEE) to measure the gain in semantic recovery accuracy brought by per unit of knowledge. Simulation results demonstrate that the recovery accuracy of our proposed KESC outperforms the compared scheme, especially in low signal-to-noise ratio(SNR) or resource-constrained scenarios.

关键词： semantic communication knowledge graph OFDM transformer deep learning

来源：评论

学校读者我要写书评

暂无评论

IncEFL:a sharing incentive mechanism for edge-assisted federated learning in industrial IoT

引用

Digital Communications and Networks 2025年第1期11卷 106-115页

作者： Jiewei Chen Shaoyong Guo Tao Shen Yan Feng Jian Gao Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Post and TelecommunicationsBeijing 100087China Kunming University of Science and Technology Kunming 650031China Yunnan Provincial Academy of Science and Technology Kunming 650228China

As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artificial Intelligence(AI)***,most users are reluctant to disclose their data due to network bandwidth limitations,device energy consumption,and privacy *** address this issue,this paper introduces an Edge-assisted Federated Learning(EFL)framework,along with an incentive mechanism for lightweight industrial data *** order to reduce the information asymmetry between data owners and users,an EFL model-sharing incentive mechanism based on contract theory is *** addition,a weight dispersion evaluation scheme based on Wasserstein distance is *** study models an optimization problem of node selection and sharing incentives to maximize the EFL model consumers'profit and ensure the quality of training *** incentive-based EFL algorithm with individual rationality and incentive compatibility constraints is ***,the experimental results verify the effectiveness of the proposed scheme in terms of positive incentives for contract design and performance analysis of EFL systems.

关键词： Federated learning Data sharing Edge intelligence Incentives Contract theory

来源：评论

学校读者我要写书评

暂无评论

DTAIS:Distributed trusted active identity resolution systems for the Industrial Internet

引用

Digital Communications and Networks 2024年第4期10卷 853-862页

作者： Tao Huang Renchao Xie Yuzheng Ren F.Richard Yu Zhuang Zou Lu Han Yunjie Liu Demin Cheng Yinan Li Tian Liu State Key Lab.of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijingChina Department of Systems and Computer Eng. Carleton UniversityOttawaONCanada

In recent years,the Industrial Internet and Industry 4.0 came into *** the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are also *** applications apply architectures such as distributed learning,resource sharing,and arithmetic trading,which make high demands on identity authentication,asset authentication,resource addressing,and service ***,an efficient,secure,and trustworthy Industrial Internet identity resolution system is ***,most of the traditional identity resolution systems follow DNS architecture or tree structure,which has the risk of a single point of failure and DDoS *** they cannot guarantee the security and privacy of digital identity,personal assets,and device *** we consider a decentralized approach for identity management,identity authentication,and asset *** this paper,we propose a distributed trusted active identity resolution system based on the inter-planetary file system(IPFS)and non-fungible token(NFT),which can provide distributed identity resolution *** we have designed the system architecture,identity service process,load balancing strategy and smart contract *** addition,we use Jmeter to verify the performance of the system,and the results show that the system has good high concurrent performance and robustness.

关键词： Industrial Internet NFT IPFS Trust Identity resolution system

来源：评论

学校读者我要写书评

暂无评论

FRACTAL: Data-aware Clustering and Communication Optimization for Decentralized Federated Learning

引用

IEEE Transactions on Big Data 2024年 1-16页

作者： Ma, Qianpiao Liu, Jianchun Xu, Hongli Jia, Qingmin Xie, Renchao Purple Mountain Laboratories Nanjing Jiangsu China School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Decentralized federated learning (DFL) is a promising technique to enable distributed machine learning over edge nodes without relying on a centralized parameter server. However, existing DFL network topologies, such as fully connected, partially connected, or lower-tier hierarchical topology often struggle to effectively address the unique challenges presented by edge networks, including edge heterogeneity, communication resource constraint, and data Non-IID. In order to tackle these challenges, we propose a data-aware clustering algorithm, called FRACTAL, to construct a multi-tier hierarchical topology in a bottomup manner taking into consideration both data distribution and communication efficiency for DFL. We theoretically explore the quantitative relationship between the convergence bound of multi-tier FL and the data distribution among each-tier servers. To further improve communication efficiency and address edge heterogeneity, we deploy a time-sharing communication scheduling algorithm within each fractal unit (the basic structure in FRACTAL consisting of multiple nodes and an aggregator), called magic mirror method (MMM), to determine the optimal order of model distributing and uploading for nodes. We conduct extensive experiments on the classical models and datasets to evaluate the performance of FRACTAL, and the results show that FRACTAL can significantly accelerate the DFL model training by 48.6%- 72.3% compared with the state-of-the-art solutions. IEEE

关键词： Network topology

来源：评论

学校读者我要写书评

暂无评论

Delay and Energy Consumption Oriented UAV Inspection Business Collaboration Computing Mechanism in Edge Computing Based Electric Power IoT

引用

Chinese Journal of Electronics 2023年第1期32卷 13-25页

作者： SHAO Sujie LI Yi GUO Shaoyong WANG Chenhui CHEN Xingyu QIU Xuesong State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Blockchain Research Department China Electronics Standardization Institute

With the development of Internet of things(IoT) technology and smart grid infrastructure,edge computing has become an effective solution to meet the delay requirements of the electric power IoT. Due to the limitation of battery capacity and data transmission mode of IoT terminals, the business collaboration computing must consider the energy consumption of the terminals. Since delay and energy consumption are the optimization goals of two co-directional changes, it is difficult to find a business collaboration computing mechanism that simultaneously minimizes delay and energy *** paper takes the unmanned aerial vehicle(UAV) inspection business scenario in the electric power IoT based on edge computing as the representative, and proposes a two-stage business collaboration computing mechanism including resources allocation and task allocation to optimize the business delay and energy consumption of UAV by decoupling the complex correlation between resource allocation and task allocation. A steepest descent resource allocation algorithm is proposed. On the basis of resource allocation, an improved multiobjective evolutionary algorithm based on decomposition by dynamically adjusting the size of neighborhood and the cross distribution index is proposed as a task allocation algorithm to minimize energy consumption and business delay. Simulation results show that our algorithms can respectively reduce the business delay and energy consumption by more than6.4% and 9.5% compared with other algorithms.

关键词： Energy consumption Heuristic algorithms Collaboration Autonomous aerial vehicles Delays Power systems Resource management

来源：评论

学校读者我要写书评

暂无评论

CSNet:A Count-Supervised Network via Multiscale MLP-Mixer for Wheat Ear Counting

引用

植物表型组学（英文） 2024年第4期6卷 995-1009页

作者： Yaoxi Li Xingcai Wu Qi Wang Zhixun Pei Kejun Zhao Panfeng Chen Gefei Hao State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationGuiyang 550025China

Wheat is the most widely grown crop in the world,and its yield is closely related to global food *** number of ears is important for wheat breeding and yield ***,automated wheat ear counting techniques are essential for breeding high-yield varieties and increasing grain ***,all existing methods require position-level annotation for training,implying that a large amount of labor is required for annotation,limiting the application and development of deep learning technology in the agricultural *** address this problem,we propose a count-supervised multiscale perceptive wheat counting network(CSNet,count-supervised network),which aims to achieve accurate counting of wheat ears using quantity *** particular,in the absence of location information,CSNet adopts MLP-Mixer to construct a multiscale perception module with a global receptive field that implements the learning of small target attention maps between wheat ear *** conduct comparative experiments on a publicly available global wheat head detection dataset,showing that the proposed count-supervised strategy outperforms existing position-supervised methods in terms of mean absolute error(MAE)and root mean square error(RMSE).This superior performance indicates that the proposed approach has a positive impact on improving ear counts and reducing labeling costs,demonstrating its great potential for agricultural counting *** code is available at .

关键词： network counting csnet mlp-mixer multiscale supervised wheat

来源：评论

学校读者我要写书评

暂无评论

A quantum federated learning framework for classical clients

引用

science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 1-10页

作者： Yanqi Song Yusen Wu Shengyao Wu Dandan Li Qiaoyan Wen Sujuan Qin Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 00876China Department of Physics The University of Western AustraliaPerthWA 6009Australia School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing100876China

Quantum federated learning(QFL)enables collaborative training of a quantum machine learning(QML)model among multiple clients possessing quantum computing capabilities,without the need to share their respective local ***,the limited availability of quantum computing resources poses a challenge for each client to acquire quantum computing *** raises a natural question:Can quantum computing capabilities be deployed on the server instead?In this paper,we propose a QFL framework specifically designed for classical clients,referred to as CC-QFL,in response to this *** each iteration,the collaborative training of the QML model is assisted by the shadow tomography technique,eliminating the need for quantum computing capabilities of ***,the server constructs a classical representation of the QML model and transmits it to the *** clients encode their local data onto observables and use this classical representation to calculate local *** local gradients are then utilized to update the parameters of the QML *** evaluate the effectiveness of our framework through extensive numerical simulations using handwritten digit images from the MNIST *** framework provides valuable insights into QFL,particularly in scenarios where quantum computing resources are scarce.

关键词： client server quantum

来源：评论

学校读者我要写书评

暂无评论

DBT-PDP:Provable data possession with outsourced data batch transfer based on blockchain

引用

High-Confidence Computing 2024年第2期4卷 62-72页

作者： Chengming Yi Hua Zhang Weiming Sun Jun Ding State key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Zhe Jiang Computer Network Emergency Response Technical Team Hangzhou 310052China

In the scenario of large-scale data ownership transactions,existing data integrity auditing schemes are faced with security risks from malicious third-party auditors and are inefficient in both calculation and communication,which greatly affects their *** paper proposes a data integrity audit scheme based on blockchain where data ownership can be traded in batches.A data tag structure which supports data ownership batch transaction is adopted in our *** update process of data tag does not involve the unique information of each data,so that any user can complete ownership transactions of multiple data in a single transaction through a single transaction auxiliary *** the same time,smart contract is introduced into our scheme to perform data integrity audit belongs to third-party auditors,therefore our scheme can free from potential security risks of malicious third-party *** analysis shows that our scheme is proved to be safe under the stochastic prediction model and k-CEIDH *** with similar schemes,the experiment shows that communication overhead and computing time of data ownership transaction in our scheme is ***,the communication overhead and computing time of our scheme is similar to that of similar schemes in data integrity audit.

关键词： Data integrity Cloud outsourcing audit Data ownership batch transaction Blockchain Smart contract

来源：评论

学校读者我要写书评

暂无评论

Stochastic programming based multi-arm bandit offloading strategy for internet of things

引用

Digital Communications and Networks 2023年第5期9卷 1200-1211页

作者： Bin Cao Tingyong Wu Xiang Bai State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu611731China China Electrics Technology Cyber Security Co..Ldt Chengdu611731China

In order to solve the high latency of traditional cloud computing and the processing capacity limitation of Internet of Things(IoT)users,Multi-access Edge Computing(MEC)migrates computing and storage capabilities from the remote data center to the edge of network,providing users with computation services quickly and *** this paper,we investigate the impact of the randomness caused by the movement of the IoT user on decision-making for offloading,where the connection between the IoT user and the MEC servers is *** uncertainty would be the main obstacle to assign the task ***,if the assigned task cannot match well with the real connection time,a migration(connection time is not enough to process)would be *** order to address the impact of this uncertainty,we formulate the offloading decision as an optimization problem considering the transmission,computation and *** the help of Stochastic Programming(SP),we use the posteriori recourse to compensate for inaccurate ***,in heterogeneous networks,considering multiple candidate MEC servers could be selected simultaneously due to overlapping,we also introduce the Multi-Arm Bandit(MAB)theory for MEC *** extensive simulations validate the improvement and effectiveness of the proposed SP-based Multi-arm bandit Method(SMM)for offloading in terms of reward,cost,energy consumption and *** results showthat SMMcan achieve about 20%improvement compared with the traditional offloading method that does not consider the randomness,and it also outperforms the existing SP/MAB based method for offloading.

关键词： Multi-access computing Internet of things Offloading Stochastic programming Multi-arm bandit

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：