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data collection of wireless sensor network based on trajectory optimization of laser-charged UAV

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High-Confidence Computing

High-Confidence Computing 2024年第2期4卷 116-128页

作者： Chuanwen Luo Jian Zhang Jin Qian Yi Hong Zhibo Chen Yunan Hou Xiujuan Zhang Yuqing Zhu School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing 100083China College of Information Engineering Taizhou UniversityTaizhou 225300China School of Computer Science Qufu Normal UniversityRizhao 276826China Research Center of Applied Mathematics and Machine Intelligence Zhejiang LabHangzhou 311121China Department of Computer Science California State UniversityCA 90032USA

Unmanned Aerial Vehicle(UAV)can be used as wireless aerial mobile base station for collecting data from sensors in UAV-based Wireless Sensor Networks(WSNs),which is crucial for providing seamless services and improving the performance in the next generation wireless ***,since the UAV are powered by batteries with limited energy capacity,the UAV cannot complete data collection tasks of all sensors without energy replenishment when a large number of sensors are deployed over large monitoring *** overcome this problem,we study the Real-time data collection with Lasercharging UAV(RDCL)problem,where the UAV is utilized to collect data from a specified WSN and is recharged using Laser Beam Directors(LBDs).This problem aims to collect all sensory data from the WSN and transport it to the base station by optimizing the flight trajectory of UAV such that realtime data performance is ensured It has been proven that the RDCL problem is *** address this,we initially focus on studying two sub-problems,the Trajectory Optimization of UAV for data collection(TODC)problem and the Charging Trajectory Optimization of UAV(CTO)problem,whose objectives are to find the optimal flight plans of UAV in the data collection areas and charging areas,*** we propose an approximation algorithm to solve each of them with the constant ***,we present an approximation algorithm that utilizes the solutions obtained from TODC and CTO problems to address the RDCL ***,the proposed algorithm is verified by extensive simulations.

关键词： Wireless sensor networks Laser-charged UAV Trajectory optimization data collection

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

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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

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

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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

Time and energy efficient data collection via UAV

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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)

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

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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

Artificial Intelligence-Enabled Cooperative Cluster-Based data collection for Unmanned Aerial Vehicles

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Computers, Materials & Continua 2022年第11期73卷 3351-3365页

作者： R.Rajender C.S.S.Anupama G.Jose Moses E.Laxmi Lydia Seifedine Kadry Sangsoon Lim Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied data Science Noroff University CollegeKristiansand4612Norway Department of Computer Engineering Sungkyul UniversityAnyang14097Korea

In recent times,sixth generation(6G)communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile *** encompasses several heterogeneous resource and communication standard in ensuring incessant availability of *** the same time,the development of 6G enables the Unmanned Aerial Vehicles(UAVs)in offering cost and time-efficient solution to several applications like healthcare,surveillance,disaster management,*** UAV networks,energy efficiency and data collection are considered the major process for high quality network *** these procedures are found to be challenging because of maximum mobility,unstable links,dynamic topology,and energy restricted *** issues are solved by the use of artificial intelligence(AI)and energy efficient clustering techniques for UAVs in the 6G *** this inspiration,this work designs an artificial intelligence enabled cooperative cluster-based data collection technique for unmanned aerial vehicles(AECCDC-UAV)in 6G *** proposed AECCDC-UAV technique purposes for dividing the UAV network as to different clusters and allocate a cluster head(CH)to each cluster in such a way that the energy consumption(ECM)gets *** presented AECCDC-UAV technique involves a quasi-oppositional shuffled shepherd optimization(QOSSO)algorithm for selecting the CHs and construct *** QOSSO algorithm derives a fitness function involving three input parameters residual energy of UAVs,distance to neighboring UAVs,and degree of *** performance of the AECCDC-UAV technique is validated in many aspects and the obtained experimental values demonstration promising results over the recent state of art methods.

关键词： 6G unmanned aerial vehicles resource allocation energy efficiency artificial intelligence clustering data collection

VDCM: A data collection Mechanism for Crowd Sensing in Vehicular Ad Hoc Networks

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Big data Mining and Analytics 2023年第4期6卷 391-403页

作者： Juli Yin Linfeng Wei Zhiquan Liu Xi Yang Hongliang Sun Yudan Cheng Jianbin Mai the College of Cyber Security Jinan UniversityGuangzhou 510632China the Guangdong Provincial Key Laboratory of Cyber and Information Security Vulnerability Research Guangzhou 510643China the College of Information Science Technology Jinan UniversityGuangzhou 510632China

With the rapid development of mobile devices,aggregation security and efficiency topics are more important than past in crowd *** collecting large-scale vehicle-provided data,the data transmitted via autonomous networks are publicly accessible to all attackers,which increases the risk of vehicle *** we need to ensure data aggregation *** addition,low aggregation efficiency will lead to insufficient sensing data,making the data unable to provide data mining *** at the problem of aggregation security and efficiency in large-scale data collection,this article proposes a data collection mechanism(VDCM)for crowd sensing in vehicular ad hoc networks(VANETs).The mechanism includes two mechanism assumptions and selects appropriate methods to reduce *** selects sub mechanism 1 when there exist very few vehicles or the coalition cannot be formed,otherwise selects sub mechanism *** aggregation is used to collect data in sub mechanism *** sub mechanism 2,cooperative vehicles are selected by using coalition formation strategy and auction cooperation agreement,and multi aggregation is used to collect *** sub mechanisms use Paillier homomorphic encryption technology to ensure the security of data *** addition,mechanism supplements the data update and scoring steps to increase the amount of available *** performance analysis shows that the mechanism proposed in this paper can safely aggregate data and reduce *** simulation results indicate that the proposed mechanism reduces time consumption and increases the amount of available data compared with existing mechanisms.

关键词： vehicular ad hoc networks(VANETs) crowd sensing data collection data aggregation security

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

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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

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

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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