检索结果-南通市图书馆

Reliable data collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Computer Modeling in Engineering & Sciences 2024年第7期140卷 1077-1102页

作者： Haosong Gou Gaoyi Zhang RenêRipardo Calixto Senthil Kumar Jagatheesaperumal Victor Hugo C.de Albuquerque China Mobile Group Sichuan Co. Ltd.Chengdu640041China Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical ***,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission *** paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale *** primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical *** approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding ***,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple *** systematic improvements are designed to optimize the overall performance of the WSN in real-world *** results of the proposed protocol validate its exceptional performance compared to other prominent data transmission *** evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data *** systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in *** prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

关键词： Wireless sensor networks reliable data transmission medical emergencies cluster data collection routing scheme

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Flight Time Minimization of UAV for Cooperative data collection in Probabilistic LoS Channel

引用

China Communications 2024年第2期21卷 210-226页

作者： Yan Li Shaoyi Xu Yunpu Wu Dongji Li School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Electrical Engineering and Electronic Information Xihua UniversityChengdu 610039China

This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight(LoS) channel. Especially, access points(APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors’ scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation(SCA) scheme is applied to solve each non-convex subproblem. Finally,the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.

关键词： data collection flight time probabilistic line-of-sight channel unlicensed band unmanned aerial vehicle

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Actor-Critic-Based UAV-Assisted data collection in the Wireless Sensor Network

引用

China Communications 2024年第4期21卷 163-177页

作者： Huang Xiaoge Wang Lingzhi He Yong Chen Qianbin School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible ***,WSN data collection encounters challenges in scenarios lacking communication *** aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high *** this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the ***,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial *** ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the *** aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for ***,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of ***,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with ***,simulation results verify the effectiveness of the proposed algorithms.

关键词： actor critic data collection deep reinforcement learning unmanned aerial vehicle wireless sensor network

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

data collection Capacity of Random-Deployed Wireless Sensor Networks under Physical Models

引用

Tsinghua Science and Technology 2012年第5期17卷 487-498页

作者： Siyuan Chen Yu Wang Department of Computer Science University of North Carolina at Charlotte Charlotte NC 28223 USA

data collection is one of the most important functions provided by wireless sensor networks. In this paper, we study the theoretical limitations of data collection in terms of capacity for a wireless sensor network where n sensors are randomly deployed. We first consider data collection under physical model We show that the capacity of data collection is in order of ⊙（W） where W is the fixed data-rate on individual links. Particularly, we give a simple collection method based on interference blocks and theoretically prove that the method can achieve the optimal capacity in order. If each sensor can aggregate its receiving packets into a single packet to send, the capacity of data collection increases to ⊙（ n/log n W ）. We then derive a lower bound and an upper bound of data collection capacity under generalized physical model where the data rate depends on the signal to interference plus noise ratio.

关键词： data collection capacity physical model wireless sensor networks

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

引用

Chinese Journal of Aeronautics 2022年第9期35卷 95-105页

作者： Xiao TANG Wei WANG Hongliang HE Ruonan ZHANG School of Electronics and Information Northwestern Polytechinical UniversityXi'an 710072China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Information Science and Technology College of Cyber SecurityJinan UniversityGuangzhou 510632China

Internet of Things(IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energyefficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle(UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying largesystem analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.

关键词： Block coordinate descent data collection Dinkelbach method Energy efficiency Internet of Things(IoT) Unmanned aerial vehicle

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Uncertainties in stormwater runoff data collection from a small urban catchment, Southeast China

引用

Journal of Environmental Sciences 2010年第11期22卷 1703-1709页

作者： Jinliang Huan Zhenshun Tu Pengfei Du Jie Lin Qingsheng Li Environmental Science Research Center Xiamen University Xiamen 361005 China. Department of Environmental Science and Engineering Tsinghua University Beijing 100084 China Fujian Institute of Oceanography Xiamen 361012 China

Monitoring data are often used to identify stormwater runoff characteristics and in stormwater runoff modelling without consideration of their inherent uncertainties. Integrated with discrete sample analysis and error propagation analysis, this study attempted to quantify the uncertainties of discrete chemical oxygen demand （COD）, total suspended solids （TSS） concentration, stormwater flowrate, stormwater event volumes, COD event mean concentration （EMC）, and COD event loads in terms of flow measurement, sample collection, storage and laboratory analysis. The results showed that the uncertainties due to sample collection, storage and laboratory analysis of COD from stormwater runoff are 13.99%, 19.48% and 12.28%. Meanwhile, flow measurement uncertainty was 12.82%, and the sample collection uncertainty of TSS from stormwater runoff was 31.63%. Based on the law of propagation of uncertainties, the uncertainties regarding event flow volume, COD EMC and COD event loads were quantified as 7.03%, 10.26% and 18.47%.

关键词： urban stormwater runoff in-situ monitoring data uncertainty data collection

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Energy efficient approximate self-adaptive data collection in wireless sensor networks

引用

Frontiers of Computer Science 2016年第5期10卷 936-950页

作者： Bin WANG Xiaochun YANG Guoren WANG Ge YU Wanyu ZANG Meng YU School of Computer Science and Engineering Northeastern University Shenyang 110819 China Department of Accounting Computing and Finance Texas A&M University at San Antonio San Antonio TX 78363 USA Computer Science Department The University of Texas at San Antonio San Antonio TX 78249 USA

To extend the lifetime of wireless sensor net- works, reducing and balancing energy consumptions are main concerns in data collection due to the power constrains of the sensor nodes. Unfortunately, the existing data collec- tion schemes mainly focus on energy saving but overlook bal- ancing the energy consumption of the sensor nodes. In ad- dition, most of them assume that each sensor has a global knowledge about the network topology. However, in many real applications, such a global knowledge is not desired due to the dynamic features of the wireless sensor network. In this paper, we propose an approximate self-adaptive data col- lection technique （ASA）, to approximately collect data in a distributed wireless sensor network. ASA investigates the spatial correlations between sensors to provide an energy- efficient and balanced route to the sink, while each sensor does not know any global knowledge on the network. We also show that ASA is robust to failures. Our experimental results demonstrate that ASA can provide significant communica- tion （and hence energy） savings and equal energy consump- tion of the sensor nodes.

关键词： wireless sensor networks data collection energy efficient self-adaptive

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Time and energy efficient data collection via UAV

引用

Science China(Information Sciences) 2022年第8期65卷 182-196页

作者： Tianhao WANG Xiaowei PANG Jie TANG Nan ZHAO Xiuyin ZHANG Xianbin WANG School of Information and Communication Engineering Dalian University of Technology Department of Electrical and Computer Engineering Western University School of Electronic and Information Engineering South China University of Technology

Using unmanned aerial vehicles(UAVs) for data collection has emerged as a promising technique to achieve both time-and energy-efficient data gathering while keeping data fresh. In this study, two schemes are proposed for flight cycle minimization and energy efficiency maximization to collect data from ground sensors. We first minimize the flight cycle by jointly optimizing the wake-up scheduling of sensors, the trajectory,and the time slot, which is a mixed-integer non-convex problem and difficult to solve directly. To this end,we propose an iterative algorithm based on block coordinate descent and successive convex approximation to decouple the original non-convex problem into two sub-problems and the constraints are turned to be convex approximately. Furthermore, the energy efficiency is maximized since the limited energy is a critical issue in UAV communication systems. We approximate the two subproblems as convex optimizations by introducing slack variables and applying SCA. The approximate energy efficiency is a fractional expression, and we use Dinkelbach’s method to solve it. Numerical results show that the flight cycle is minimized in the first scheme with the data requirement satisfied, while in the second scheme, the energy efficiency is maximized with the trade-off between the transmission data and the propulsion power consumption.

关键词： data collection energy efficiency maximization time minimization trajectory optimization unmanned aerial vehicle (UAV)

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

NOMA Empowered Energy Efficient data collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

引用

China Communications 2023年第8期20卷 17-31页

作者： Cong Zhou Shuo Shi Chenyu Wu Zhenyu Xu School of Electronic and Information Engineering Harbin Institute of TechnologyHarbin 150001China Peng Cheng Laboratory Shenzhen 518055China Department of Intelligent Engineering Huizhou Engineering Vocational CollegeHuizhou 516023China

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical ***,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds *** propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT *** extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT *** to the coupling between variables,the resulting problem is *** first decouple the variables and split the original problem into four ***,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack ***,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.

关键词： NOMA Space-Air-Ground Integrated Networks data collection wireless power transfer resource allocation trajectory optimization

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Towards Task-Free Privacy-Preserving data collection

引用

China Communications 2022年第7期19卷 310-323页

作者： Zhibo Wang Wei Yuan Xiaoyi Pang Jingxin Li Huajie Shao School of Cyber Science and Engineering Wuhan University430072 China School of Cyber Science and Technology Zhejiang University310027 China State Key Laboratory of Integrated Services Networks Xidian University710071 China Department of Computer Science College of William and MaryWilliamsburgVA23186 USA

With the rapid developments of Internet of Things(IoT)and proliferation of embedded devices,large volume of personal data are collected,which however,might carry massive private information about attributes that users do not want to *** privacy-preserving methods have been proposed to prevent privacy leakage by perturbing raw data or extracting task-oriented features at local ***,they would suffer from significant privacy leakage and accuracy drop when applied to other tasks as they are designed and optimized for predefined *** this paper,we propose a novel task-free privacy-preserving data collection method via adversarial representation learning,called TF-ARL,to protect private attributes specified by users while maintaining data utility for unknown downstream *** this end,we first propose a privacy adversarial learning mechanism(PAL)to protect private attributes by optimizing the feature extractor to maximize the adversary’s prediction uncertainty on private attributes,and then design a conditional decoding mechanism(ConDec)to maintain data utility for downstream tasks by minimizing the conditional reconstruction error from the sanitized *** the joint learning of PAL and ConDec,we can learn a privacy-aware feature extractor where the sanitized features maintain the discriminative information except *** experimental results on real-world datasets demonstrate the effectiveness of TF-ARL.

关键词： IoT privacy protection data collection adversarial learning deep learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：