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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 emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This 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 WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By 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

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

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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 installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The 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 UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,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

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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

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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

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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 sensing.When collecting large-scale vehicle-provided data,the data transmitted via autonomous networks are publicly accessible to all attackers,which increases the risk of vehicle exposure.So we need to ensure data aggregation security.In addition,low aggregation efficiency will lead to insufficient sensing data,making the data unable to provide data mining services.Aiming 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 consumption.It selects sub mechanism 1 when there exist very few vehicles or the coalition cannot be formed,otherwise selects sub mechanism 2.Single aggregation is used to collect data in sub mechanism 1.In sub mechanism 2,cooperative vehicles are selected by using coalition formation strategy and auction cooperation agreement,and multi aggregation is used to collect data.Two sub mechanisms use Paillier homomorphic encryption technology to ensure the security of data aggregation.In addition,mechanism supplements the data update and scoring steps to increase the amount of available data.The performance analysis shows that the mechanism proposed in this paper can safely aggregate data and reduce consumption.The 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

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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)

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Towards Task-Free Privacy-Preserving data collection

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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 share.Many privacy-preserving methods have been proposed to prevent privacy leakage by perturbing raw data or extracting task-oriented features at local devices.Unfortunately,they would suffer from significant privacy leakage and accuracy drop when applied to other tasks as they are designed and optimized for predefined tasks.In 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 tasks.To 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 features.With the joint learning of PAL and ConDec,we can learn a privacy-aware feature extractor where the sanitized features maintain the discriminative information except privacy.Extensive experimental results on real-world datasets demonstrate the effectiveness of TF-ARL.

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

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

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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 issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,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

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Energy-Efficient data collection over Underwater MI-Assisted Acoustic Cooperative MIMO WSNs

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中国通信:英文版 2023年第11期20卷 96-110页

作者： Qingyan Ren Yanjing Sun Song Li Bin Wang Zhengda Yu School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Department of Information Technology and Electrical Engineering ETH ZurichZurich 8092Switzerland School of Communication and Information Engineering Xi’an University of Science and TechnologyXi’an 710054China Xuzhou Engineering Research Center of Intelligent Industry Safety and Emergency Collaboration Xuzhou 221000China

Underwater magnetic induction(MI)-assisted acoustic cooperative multiple-input-multipleoutput(MIMO) has been recently proposed as a promising technique for underwater wireless sensor networks(UWSNs).For the more,the energy utilization of energy-constrained sensor nodes is one of the key issues in UWSNs,and it relates to the network lifetime.In this paper,we present an energy-efficient data collection for underwater MI-assisted acoustic cooperative MIMO wireless sensor networks(WSNs),including the formation of cooperative MIMO and relay link establishment.Firstly,the cooperative MIMO is formed by considering its expected transmission range and the energy balance of nodes with it.Particularly,from the perspective of the node’s energy consumption,the expected cooperative MIMO size and the selection of master node(MN) are proposed.Sequentially,to improve the coverage of the networks and prolong the network lifetime,relay links are established by relay selection algorithm that using matching theory.Finally,the simulation results show that the proposed data collection improves its efficiency,reduces the energy consumption of the master node,improves the networks’ coverage,and extends the network lifetime.

关键词： cooperative MIMO cooperative MIMO size data collection heterogeneous UWSNs relay link establishment

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AUV-Aided data collection Considering Adaptive Ocean Currents for Underwater Wireless Sensor Networks

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China Communications 2023年第4期20卷 356-367页

作者： Yunyun Li Yanjing Sun Qingyan Ren Song Li School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Autonomous underwater vehicle(AUV)-assisted data collection is an efficient approach to implementing smart ocean.However,the data collection in time-varying ocean currents is plagued by two critical issues:AUV yaw and sensor node movement.We propose an adaptive AUV-assisted data collection strategy for ocean currents to address these issues.First,we consider the energy consumption of an AUV in conjunction with the value of information(VoI)over the sensor nodes and formulate an optimization problem to maximize the VoI-energy ratio.The AUV yaw problem is then solved by deriving the AUV's reachable region in different ocean current environments and the optimal cruising direction to the target nodes.Finally,using the predicted VoI-energy ratio,we sequentially design a distributed path planning algorithm to select the next target node for AUV.The simulation results indicate that the proposed strategy can utilize ocean currents to aid AUV navigation,thereby reducing the AUV's energy consumption and ensuring timely data collection.

关键词： underwater sensor networks data collection ocean currents value of information energy consumption

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