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IEEE Wireless Communications and Networking Conference (IEEE WCNC)

作者： Xu, Fang Yang, Hong-Chuan Univ Victoria Dept Elect & Comp Engn Victoria BC Canada

ISBN: (纸本)9781665442664

With its low cost and high implementation flexibility, unmanned aerial vehicle (UAV) serves as an attractive solution for data collection from remote sensors. UAV can also power the transmission of resource-limited sensors through wireless energy transfer. In this article, we study the UAV energy consumption minimization during an individual sensor charging and data collection session. Specifically, considering the operation of the UAV at a particular sensor, we derive the closed-form expressions of optimal transmission parameters with/without latency constraint. We also analyze the probability of data collection failure due to poor channel condition. The validity of our theoretical analysis is verified by comparing with the results from exhaustive search. According to these results, optimal duration for sensor data transmission should be as short as possible for negligible circuit power, and latency constraint does not have significant impacts on minimum energy consumption for nonnegligible circuit power and channel gain.

关键词： Internet of Things sensor data collection unmanned aerial vehicle wireless energy transfer energy efficiency

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Optimal Control of Air Conditioning System based on data Mining: from sensor data collection to Visualization Algorithms 6

Optimal Control of Air Conditioning System based on Data Min...

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6th International Conference on Trends in Electronics and Informatics (ICOEI)

作者： Xu, Jian Sun, Li Zhejiang Univ Hangzhou 310027 Peoples R China Jiehua Holdings Co Ltd Haining 314419 Peoples R China

ISBN: (纸本)9781665483285;9781665483292

Optimal control of air conditioning system based on data mining from sensor data collection to visualization algorithms is studied in the paper. Firstly, this research study combines the methods of core spatial fusion and spatio-temporal cooperative evaluation to realize the adaptive optimization control in the process of wireless sensor network routing detection, and use the grey correlation prediction method to analyze the autocorrelation feature allocation set of the core wireless sensor network routing transmission. Wireless sensor network is a new generation of sensor network, its development and application will bring far-reaching influence to all fields of human life and production. Detecting remote signals and realizing network tracking is the inevitable trend of the development of electrical detection technology, and the effective implementation of this technology needs to use computers and databases and hence the visualization algorithms are applied into the system and further the application scenarios will be selected as the control of air conditioning system. After the verifying test, the performance of the model is validated.

关键词： Visualization Algorithm Optimal Control Air Conditioning System data Mining sensor data collection

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Median Access Control Protocols for sensor data collection: A Review

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IEEE ACCESS 2020年 8卷 160078-160098页

作者： Zhao, Wenbo Li, Yifan Yan, Bo Xu, Luping Xidian Univ Sch Aerosp Sci & Technol Xian 710071 Peoples R China Wuhan Univ Technol Sch Logist Engn Wuhan 430070 Peoples R China

Median Access Control (MAC) protocols are designed to mitigate collisions and enhance the energy efficiency for sensor data collection. This paper reviews two basic categories of MAC protocols. The first class is the contention-based protocols, where nodes randomly compete for channel access. The second class is the schedule-based MAC protocols, in which nodes access the channel on the basis of the predetermined schedules. We focus on discussing the Time Division Multiple Access (TDMA) protocols and classify different TDMA schedulings into three categories according to the communication patterns in the network, i.e., the link scheduling, aggregate scheduling and non-aggregate scheduling. Link scheduling deals with the peer to peer communication pattern, where there is no central node in the network. In comparison, both the aggregate and non-aggregate schedulings handle the convergecast communication pattern, in which all traffic are destined to the sink. This survey provides a comprehensive overview of these three categories and provided a detailed briefing on how the TDMA schedules handle the network traffic dynamics in the network. Compared with other surveys in this domain, this review does not confine itself to deal with collecting a particular form of data, but provides a unified framework to integrate the data semantics in a broader sense into the design of TDMA scheduling algorithms.

关键词： Time division multiple access Peer-to-peer computing Media Access Protocol Schedules Scheduling data collection TDMA scheduling sensor data collection wireless sensor networks survey

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data Sweeper A Proactive Filtering Framework for Error-Bounded sensor data collection

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2016年第4期4卷 487-501页

作者： Wang, Dan Liu, Jiangchuan Xu, Jianliang Jiang, Hongbo Wang, Chonggang Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada Hong Kong Baptist Univ Dept Comp Sci Hong Kong Hong Kong Peoples R China Huazhong Univ Sci & Technol Dept Elect & Informat Engn Wuhan 430074 Peoples R China InterDigital Commun Princeton NJ 08540 USA

This paper presents data sweeper a novel framework that attempts to reduce network traffic for error-bounded data collection in wireless sensor networks. Unlike existing passive filters, a data sweeper migrates in the network and proactively suppresses data updates while maintaining the user-defined error bound. Intuitively, the migration of a data sweeper learns the data change of each sensor node on the fly, which helps to maximize the filtering capacity. We design the data sweeper framework in such a way that it can accommodate diverse query specifications and be easily incorporated into the existing sensor network protocols. Moreover, we develop efficient strategies for query precision maintenance, sweeper migration, and data suppression within the framework. In particular, in order to maximize traffic reduction and adapt to online data updates, a Lagrangian relaxation-based algorithm is proposed for data suppression. Extensive simulations based on real-world traces show that the data sweeper significantly reduces the network traffic and extends the system lifetime under various network configurations.

关键词： data sweeper sensor data collection

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sensor data collection experiments with Chaoster in the Fed4FIRE federated testbeds 10

Sensor data collection experiments with Chaoster in the Fed4...

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10th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Pataki, Balazs E. Kovacs, Laszlo Hungarian Acad Sci Inst Comp Sci & Control Dept Distributed Syst MTA SZTAKI DSD Budapest Hungary

ISBN: (纸本)9781479950416

ChaosFIRE is an experiment to evaluate the performance and usability of peer-to-peer mobile technologies as an alternative mean to central service based solutions to collect and distribute sensor information in an urban area. The Project runs under the 1st Open Call of Fed4FIRE IP under FP7 and is based on the technology developed in the Chaoster project of MTA SZTAKI DSD. Chaoster is a DTN-PSN (Delay Tolerant Networking - Pocket Switched Network) based adaptive, context-aware collaboration platform supporting emergent interoperability for crisis/chaos management. DTN-PSN communication layer of Chaoster is used in this experiment together with the ChaosONE simulator, an extended version of the ONE simulator originally developed for the evaluation of DTN communication protocols.

关键词： opportunistic networking delay tolerant networking crisis management sensor data collection

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Trajectory Synthesis for a UAV Swarm Based on Resilient data collection Objectives

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2023年第1期20卷 138-151页

作者： Jakaria, A. H. M. Rahman, Mohammad Ashiqur Asif, Muneeba Khalil, Alvi Ataur Kholidy, Hisham A. Anderson, Matthew Drager, Steven Tennessee Technol Univ Dept Comp Sci Cookeville TN 38505 USA Elect Power Res Inst Distributed Energy Resources Grp Knoxville TN 37932 USA Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA State Univ New York Polytech Inst Dept Networks & Comp Secur Utica NY 13502 USA Air Force Res Lab Informat Directorate Rome NY 13441 USA

The use of Unmanned Aerial Vehicles (UAVs) for collecting data from remotely located sensor systems is emerging. The data can be time-sensitive and require to be transmitted to a data processing center. However, planning the trajectory for a swarm of UAVs depends on multi-fold constraints, such as data collection requirements, UAV maneuvering capacities, and budget limitations. Since a UAV may fail or be compromised, it is important to provide necessary resilience to such contingencies, thus ensuring data security. It is important to provide the UAVs with efficient spatio-temporal trajectories so that they can efficiently cover necessary data sources. In this work, we present Synth4UAV, a formal approach for automated synthesis of efficient trajectories for a UAV swarm by logically modeling the aerial space and data point topology, UAV moves, and associated constraints in terms of the turning and climbing angle, fuel usage, data collection point coverage, data freshness, and resiliency properties. We use efficient, logical formulas to encode and solve the complex model. The solution to the model provides the routing and maneuvering plan for each UAV, including the time to visit the points on the paths and corresponding fuel usage such that the necessary data points are visited while satisfying the resiliency requirements. We evaluate the proposed trajectory synthesizer, and the results show that the relationship among different parameters follows the requirements while the tool scales well with the problem size.

关键词： Trajectory Autonomous aerial vehicles data collection Three-dimensional displays Resilience Planning Fuels UAV swarm sensor data collection trajectory design formal model resiliency

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PriviAware: Exploring data Visualization and Dynamic Privacy Control Support for data collection in Mobile Sensing Research 24

PriviAware: Exploring Data Visualization and Dynamic Privacy...

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ACM CHI Conference on Human Factors in Computing Sytems (CHI)

作者： Lee, Hyunsoo Jung, Yugyeong Law, Hei Yiu Bae, Seolyeong Lee, Uichin Korea Adv Inst Sci & Technol Daejeon South Korea GIST Gwangju South Korea

ISBN: (纸本)9798400703300

With increased interest in leveraging personal data collected from 24/7 mobile sensing for digital healthcare research, supporting user-friendly consent to data collection for user privacy has also become important. This work proposes PriviAware, a mobile app that promotes flexible user consent to data collection with data exploration and contextual filters that enable users to turn off data collection based on time and places that are considered privacy-sensitive. We conducted a user study (N = 58) to explore how users leverage data exploration and contextual filter functions to explore and manage their data and whether our system design helped users mitigate their privacy concerns. Our findings indicate that offering fine-grained control is a promising approach to raising users' privacy awareness under the dynamic nature of the pervasive sensing context. We provide practical privacy-by-design guidelines for mobile sensing research.

关键词： Mobile Sensing Research sensor data collection Usable Privacy

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FDRF: Fault Detection and Recovery Framework for Seamless data Transmission in Remote Health Monitoring Using WBAN

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WIRELESS PERSONAL COMMUNICATIONS 2022年第1期123卷 325-356页

作者： Karmakar, Koushik Saif, Sohail Das, Priya Neogy, Sarmistha Biswas, Suparna Narula Inst Technol Dept Comp Sci & Engn Kolkata India Maulana Abul Kalam Azad Univ Technol Dept Comp Sci & Engn Nadia W Bengal India Chakdaha Coll Dept Comp Sci Nadia W Bengal India Jadavpur Univ Dept Comp Sci & Engn Kolkata India

Health monitoring systems based on sensors, IoT and Cloud server have gained popularity in recent time. In this work patient either wear small sensors or they are placed inside their body through the surgical means. They will sense health vitals and transmit them to central server for processing and storage. Doctors can remotely access the data at his convenience. Such sensor based monitoring system should be reliable and fault-free since it involves health data. However, it may be affected by several factors at different places and levels, like hardware failure, software problems, as well as errors during transmission. Health monitoring system should be fault preventive so that it can function properly and ensure seamless data transmission even in the presence of some faulty sensor nodes. In the present context we have designed a Fault Detection and Recovery Framework for sensor based remote health monitoring system which can detect faulty sensor nodes and can accordingly select alternative set of nodes to continue with the data transmission. Faulty nodes are restrained from taking part in data sensing and transmission till they behave properly or are replaced by other nodes. We have used Libelium MySignals HW (eHealth Medical Development Shield used in Arduino) v2 sensors, patient vitals are collected through three different sensors such as ECG, SpO2 and temperature sensor. Additionally arduino board Model UNO R3 is used as microcontroller device. Acquired sensor data are analyzed using proposed algorithm and simulated using MATLAB to detect node level faults and our proposed framework ensures reliable, seamless, accurate and timely data transmission.

关键词： WBAN sensor data collection Hardware test bed ECG sensor SpO2 sensor Pulse rate Fault detection

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Energy Consumption Minimization for data collection From Wirelessly-Powered IoT sensors: Session-Specific Optimal Design With DRL

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IEEE sensorS JOURNAL 2022年第20期22卷 19886-19896页

作者： Xu, Fang Yang, Hong-Chuan Alouini, Mohamed-Slim Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 2Y2 Canada King Abdullah Univ Sci & Technol KAUST CEMSE Div Thuwal 23955 Saudi Arabia

Reliable and energy-efficient data collection from resource-limited sensors is essential to the success of future Internet of Things (IoT). In this article, we study the energy consumption minimization problem during the data collection from a generic wirelessly-powered sensor. Specifically, we determine the optimal data collection parameters, in terms of charging duration and charging power as well as sensor transmission rate, in real time according to the instantaneous channel condition while satisfying a certain latency constraint. For the scenario of ideal rate-adaptive transmission with linear energy harvesting, we derive closed-form expressions for optimal transmission parameters. We also establish the condition on channel quality for successful data collection under a latency constraint. For the more practical case of finite block-length transmission with nonlinear energy harvesting, we develop a deep reinforcement learning (DRL) solution for efficient online implementation. We also propose an online tuning scheme to cater for model inaccuracy and environment variation. The accuracy and effectiveness of our proposed approaches are verified by comparing with benchmark schemes. Our DRL-based approach has broad applicability and can solve other real-time optimal design problems in wireless communications.

关键词： sensors data collection Energy harvesting Energy consumption Wireless sensor networks Wireless communication Minimization Energy efficiency finite block length Internet of Things (IoT) nonlinear energy harvesting sensor data collection unmanned aerial vehicle (UAV) wireless energy transfer

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Practical Opportunistic data collection in Wireless sensor Networks with Mobile Sinks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2017年第5期16卷 1420-1433页

作者： Yang, Shusen Adeel, Usman Tahir, Yad McCann, Julie A. Xi An Jiao Tong Univ Sch Math & Stat Xian 710049 Peoples R China Intel Labs Europe Santa Clara CA 95054 USA Imperial Coll London Dept Comp London SW7 2AZ England

Wireless sensor Networks with Mobile Sinks (WSN-MSs) are considered a viable alternative to the heavy cost of deployment of traditional wireless sensing infrastructures at scale. However, current state-of-the-art approaches perform poorly in practice due to their requirement of mobility prediction and specific assumptions on network topology. In this paper, we focus on low-delay and high-throughput opportunistic data collection in WSN-MSs with general network topologies and arbitrary numbers of mobile sinks. We first propose a novel routing metric, Contact-Aware ETX (CA-ETX), to estimate the packet transmission delay caused by both packet retransmissions and intermittent connectivity. By implementing CA-ETX in the defacto TinyOS routing standard CTP and the IETF IPv6 routing protocol RPL, we demonstrate that CA-ETX can work seamlessly with ETX. This means that current ETX-based routing protocols for static WSNs can be easily extended to WSN-MSs with minimal modification by using CA-ETX. Further, by combing CA-ETX with the dynamic backpressure routing, we present a throughput-optimal scheme Opportunistic Backpressure collection (OBC). Both CA-ETX and OBC are lightweight, easy to implement, and require no mobility prediction. Through test-bed experiments and extensive simulations, we show that the proposed schemes significantly outperform current approaches in terms of packet transmission delay, communication overhead, storage overheads, reliability, and scalability.

关键词： Opportunistic networks sensor data collection delay tolerant sensing queueing networks

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