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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

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Efficient Brillouin frequency shift extraction method employing Brillouin gain spectrum fitting in the distributed BOTDA fiber sensor

Efficient Brillouin frequency shift extraction method employ...

引用

international conference on Photonics (ICP)

作者： Abdulwahhab Essa Hamzah Mustafa Essa Hamzah Intan Fatimah Sasila Ghadzali Mahmoud Muhanad Fadhel Nurfarhana Mohamad Sapiee Mohd Saiful Dzulkefly Zan Yosuke Tanaka Hisham Mohamad Sawal Hamid Md Ali Ahmad Ashrif A Bakar Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Selangor Malaysia Division of Advanced Electrical and Electronic Engineering Institute of Engineering Tokyo University of Agriculture and Technology Japan Civil & Environmental Engineering Department Universiti Teknologi PETRONAS Seri Iskandar Perak Malaysia

ISBN: (数字)9798350383164

ISBN: (纸本)9798350383171

This paper demonstrates the deployment of quadratic curve fitting (QCF) based on half-peak Brillouin gain spectrum (BGS) for fast and accurate Brillouin frequency shift (BFS) extraction. The method was analysed and compared with three other methods such as Lorentzian curve fitting (LCF), Gaussian curve fitting (GCF) and pseudo-Voigt curve fitting (pVCF). The QCF based on half-peak achieved an accuracy similar to other curve fitting methods. In addition, the QCF has a faster processing time by eight-fold than the others, allowing the system to handle a large amount of data with good performance. The results would provide some general ideas for deploying the QCF algorithm for the system on chip platform with direct detection for fast BFS measurement.

关键词： Semiconductor device measurement Optical fiber sensors Accuracy Fitting Scattering System-on-chip Velocity measurement Curve fitting Photonics

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Federated Learning for Autoencoder-based Condition Monitoring in the Industrial Internet of Things

Federated Learning for Autoencoder-based Condition Monitorin...

引用

ieee international conference on Big Data

作者： Soeren Becker Kevin Styp-Rekowski Oliver Vincent Leon Stoll Odej Kao Distributed and Operating Systems Research Group Technische Universität Berlin

ISBN: (纸本)9781665480468

Enabled by the increasing availability of sensor data monitored from production machinery, condition monitoring and predictive maintenance methods are key pillars for an efficient and robust manufacturing production cycle in the Industrial Internet of Things. The employment of machine learning models to detect and predict deteriorating behavior by analyzing a variety of data collected across several industrial environments shows promising results in recent works, yet also often requires transferring the sensor data to centralized servers located in the cloud. Moreover, although collaborating and sharing knowledge between industry sites yields large benefits, especially in the area of condition monitoring, it is often prohibited due to data privacy issues. To tackle this situation, we propose an Autoencoder-based Federated Learning method utilizing vibration sensor data from rotating machines, that allows for a distributed training on edge devices, located on-premise and close to the monitored machines. Preserving data privacy and at the same time exonerating possibly unreliable network connections of remote sites, our approach enables knowledge transfer across organizational boundaries, without sharing the monitored data. We conducted an evaluation utilizing two real-world datasets as well as multiple testbeds and the results indicate that our method enables a competitive performance compared to previous results, while significantly reducing the resource and network utilization.

关键词： Condition monitoring Training Vibrations Industries Federated learning Rotating machines Image edge detection

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Performance Analysis of Drone Assisted Multiple Antenna Backscatter IoT sensor Network 8

Performance Analysis of Drone Assisted Multiple Antenna Back...

引用

8th international conference on Internet of Things, systems, Management and Security (IOTSMS)

作者： Hayajneh, Ali M. Al-Obiedollah, Haitham Salameh, Haythem Bany Merenda, Massimo Hayajneh, Sofyan M. Zaidi, Syed Ali Raza McLernon, Des C. Hashemite Univ Dept Elect Engn Zarqa Jordan Al Ain Univ Coll Engn Al Ain U Arab Emirates Yarmouk Univ Telecommuniat Engn Dept Irbid Jordan Mediterranea Univ Delle Infrastrutture & Energia Sostenibile DIIES Reggio Di Calabria Italy Arab Open Univ Fac Comp Studies Amman Jordan Univ Leeds Sch Elect & Elect Engn Leeds W Yorkshire England

ISBN: (纸本)9781665458689

In this paper, we investigate the idea of drone-assisted multiple antenna ambient backscatter communication (AmBC) based internet of things (IoT) sensor network (SN). We consider a scenario where a drone is used to collect the data from distributed multiple antenna SNs at which the drone is working as an ambient power emitter and a reader. The sensor nodes passively modulate the transmitted pure carrier by implementing load impedance modulation which results in an amplitude shift keying modulation. In order to quantify the performance of the studied network, we aim to find a closed-form expression for the coverage probability for the AmBC double-Rayleigh dyadic fading channel. Our model also incorporates Line of Sight (LoS) and Non-LoS (NLoS) propagation states for accurately modeling large-scale path-loss between drone and SN. We also investigate the use of the method of the moments in finding the probability density function (PDF) for the overall fading channel by matching it to a Log-Normal distribution to ease the mathematical manipulations. Finally, numerical results are compared to Monte-Carlo simulations to verify the effectiveness of the derived system model analysis and to characterize the optimal selection of the network parameters in maximizing the coverage probability.

关键词： Drone Backscatter communication Dyadic fading IoT Coverage probability

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distributed Energy Optimization for Mobile Networks Using Potential Games

Distributed Energy Optimization for Mobile Networks Using Po...

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ieee Internatonal conference on Mobile Adhoc and sensor systems (MASS)

作者： Zhizongkai Wang Hanfei Wang Zhongji Wang Yilin Xiao Yunzhi Zhao Xiaowen Li Xufeng Chen Lin Gao Fen Hou Jianwei Huang School of Electronics and Information Engineering and the Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology Shenzhen Guangdong P.R. China School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network and CSIJRI Joint Research Centre on Smart Energy Storage The Chinese University of Hong Kong Shenzhen Guangdong P.R. China Department of Electrical and Computer Engineering State Key Laboratory of IoT for Smart City University of Macau Macau SAR P.R. China Huawei Technologies P.R. China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

The rapid advancement of information and communication technology (ICT) has made the industry a significant contributor to global carbon emissions. As the foundation of ICT, next-generation mobile communication networks aim to be more powerful and energy-efficient. However, optimizing energy efficiency in real networks is challenging due to large-scale, multi-layer control variables and the dynamic environment. This paper addresses the energy efficiency optimization problem from a network perspective by controlling cross-layer variables including both cell activation status and cell priority, to minimize overall network energy consumption while ensuring user quality-of-experience, which poses an NP-hard mixed-integer nonlinear programming problem. To tackle this, we propose a non-cooperative game where each cell acts as a player, optimizing its activation status and reference signal transmission power (determining its priority). We show that the game is a potential game, guaranteeing the existence of Nash equilibrium and the convergence of simple distributed algorithms towards Nash equilibrium. We further show that the Nash equilibrium points of the game can (but not always) reach the global optimal energy efficiency. Simulation results show that our proposed method can reduce the total system cost (including both energy consumption cost and user experience loss) by up to 28% compared to existing methods in the literature. Moreover, the performance loss of our proposed method, compared to the global optimal solution, is less than 13.7%. In summary, this work offers a realistic network model, introduces a novel game-based method, and provides extensive performance evaluation, making a significant contribution to both industry and academia.

关键词： Industries Energy consumption Costs Simulation Games Nash equilibrium Energy efficiency Information and communication technology distributed algorithms Optimization

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Tributary Water Depth and Velocity Remote Monitoring System using Arduino and LoRa

Tributary Water Depth and Velocity Remote Monitoring System ...

引用

international conference on computing, Engineering, and Design (ICCED)

作者： Ammar Azizi Jasni Yasser Asrul Ahmad Teddy Surya Gunawan Mashkuri Yaacob Nanang Ismail Abdul Wasik Electrical and Computer Engineering Dept. International Islamic University Malaysia Kuala Lumpur Malaysia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Indonesia Religious Study Department UIN Sunan Gunung Djati Bandung Indonesia

ISBN: (纸本)9781665453905

Currently, monitoring tributary water depths and velocity is divided into two distinct setups, and the majority of data extraction is performed manually. This paper aims to develop a real-time remote monitoring system capable of measuring the depth and velocity of tributary water in real-time. The system measures and records the water flow speed using the YS-F201 Hall-effect water flow sensor and the water depth using the HC-SR04 ultrasonic sensor. The Arduino Uno R3 microcontroller is used to process raw data using a set of computational functions to generate final depth and velocity values. For remote monitoring and data communication, the LoRa SX1278 module is integrated with the microcontroller. At -102dBm, the LoRa modules detect a minimum RSSI. The ultrasonic sensor has a 97.72 % accuracy in measuring water depths up to 1.5 meters and a 98.19 % accuracy in measuring water velocity. The experimental results established the system's utility.

关键词： Meters Ultrasonic variables measurement Microcontrollers Current measurement Real-time systems Acoustics Velocity measurement

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Boosting Bandwidth Convergence: Optimizing Resource Allocation in Satellite-Terrestrial Integrated Networks

Boosting Bandwidth Convergence: Optimizing Resource Allocati...

引用

international conference on Communication Technology (ICCT)

作者： Dongbo Li Jiajun Zhang Puyang Tian Zhisheng Yin Siyao Cheng Jie Liu IoT and Ambient Intelligence Research Center Faculty of Computing Harbin Institute of Technology Harbin China Cyber-Physical Systems Research Center International Research Institute for AI Harbin Institute of Technology Shenzhen Shenzhen China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China School of Communication Engineering Xidian University Xi'an China International Research Institute for AI Harbin Institute of Technology Shenzhen Shenzhen China

Satellite-Terrestrial Integrated Network (STIN) is a multidimensional network that integrates satellites and terrestrial netwoks, providing information services globally. However, facing time-varying network topology and transmission resources, STIN is limited by the uneven network resources in each network segment. Therefore, it is difficult for STIN to achieve optimal network performance during data transmission. In response to the above challenges, this paper proposes a soft-defined STIN based multipath selection and resource allocation method. We build a soft-defined network architecture for STIN, establish satellite-terrestrial dynamic network topology, and deploy distributed controller nodes. The proposed method models multiple factors that affect throughput performance in the network as a link transmission cost matrix, defining bandwidth resources, computing resources, and latency parameters for modeling. Finally, construct the optimal resource objective function for soft-defined STIN. Meanwhile, we propose a Boosting Bandwidth Convergence (BBC) method. This method merges all transmission paths using a recursive method, and obtains the optimal objective function solution. STK, Mininet, and Ryu are adopted as a joint simulation platform to simulate the three-layer network architecture of soft-defined STIN. The simulation results show that the proposed method outperforms default Ryu switch algorithm and Shortest Path Bridging (SPB) algorithm in terms of throughput, even in the presence of network interference. It exhibits comparable average delay but maintains consistent delay throughout the transmission process, unlike the fluctuating delays observed in the other two algorithms due to buffer accumulation.

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Towards Bat Bio-inspired Decision-making for Task Allocation in Vehicular Fogs

Towards Bat Bio-inspired Decision-making for Task Allocation...

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international conference on distributed computing in sensor systems (DCOSS)

作者： Matheus S. Quessada Douglas D. Lieira Robson E. De Grande Rodolfo I. Meneguette São Paulo State University (UNESP) SP Brazil Brock University (BrockU) St. Catharines Canada Federal Institute of São Paulo (IFSP) SP Brazil University of São Paulo (USP) SP Brazil

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

Technological evolutions in intelligent transportation have enabled smart and connected vehicles to support novel safety and infotainment services. The provision of such services is guaranteed with effective sharing and allocation of resources for task offloading and processing. The use of vehicular fogs also helps this process by lowering the latency in communications and the resource share among the fog members. However, allocation in Fogs introduces challenges related to the intermittency of Fog vehicle nodes, clustering, topology changes, and resource allocation problems. The use of metaheuristic algorithms has been explored in several works to solve these optimization problems, such as resource allocation, clustering, task allocation, and network communications, especially regarding efficiency. We thus propose a bat bio-inspired decision-making algorithm for task allocation in vehicular fogs called AEGIS. AEGIS uses the cluster members and task parameters to do the decision-making process in the task allocation process that helps to choose the best vehicle of the fog to allocate a determined task. The AEGIS was compared to a GWO approach (meta-heuristic), Greedy, and Random (traditional) approaches. We considered allocated, denied, and lost tasks for the simulation criteria. AEGIS lost fewer tasks than the other algorithms and allocated more tasks than the traditional algorithms.

关键词： systems operation Simulation Decision making Metaheuristics Transportation sensor systems Performance analysis

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Performance Evaluation of Spatial Data Management systems Using GeoSpark

Performance Evaluation of Spatial Data Management Systems Us...

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ieee international conference on Big Data and Smart computing (BigComp)

作者： Shin, Hansub Lee, Kisung Kwon, Hyuk-Yoon Seoul Natl Univ Sci & Technol Dept Ind & Syst Engn Seoul South Korea Louisiana State Univ Div Comp Sci & Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781728160344

In this paper, we evaluate the performance of spatial data management systems in distributed computing environments. Given that GeoSpark outperforms other spatial systems in many scenarios as reported in several studies, we choose spatial data management systems using GeoSpark for this evaluation. Even though GeoSpark supports various storage engines as its underlying data store, the effects of the storage engines for spatial data processing have not been well studied. To address this limitation, we evaluate the performance of GeoSpark using two underlying data stores: 1) HDFS and 2) MongoDB. We first design and build distributed experimental environments based on Amazon EC2 and EMR using up to 10 nodes. Through the extensive experiments on three synthetic and real data sets, we show that the overall performance of both HDFS- and MongoDB-based GeoSpark improves as we increase the number of nodes. We also show that HDFS-based GeoSpark generally outperforms MongoDB-based GeoSpark, especially for large-scale data sets. In addition, we demonstrate that the proper use of caching on HDFS-based GeoSpark can improve the overall query processing performance by up to three orders of magnitude.

关键词： Large-scale spatial data GeoSpark Performance evaluation distributed environments

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Latency, Capacity, and distributed Minimum Spanning Tree 40

Latency, Capacity, and Distributed Minimum Spanning Tree

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40th ieee international conference on distributed computing systems (ICDCS)

作者： Augustine, John Gilbert, Seth Kuhn, Fabian Robinson, Peter Sourav, Suman Indian Inst Technol Madras Chennai Tamil Nadu India Natl Univ Singapore Singapore Singapore Univ Freiburg Freiburg Germany City Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781728170022

We study the cost of distributed MST construction in the setting where each edge has a latency and a capacity, along with the weight. Edge latencies capture the delay on the links of the communication network, while capacity captures their throughput (the rate at which messages can be sent). Depending on how the edge latencies relate to the edge weights, we provide several tight bounds on the time and messages required to construct an MST. When edge weights exactly correspond with the latencies, we show that, perhaps interestingly, the bottleneck parameter in determining the running time of an algorithm is the total weight W of the MST (rather than the total number of nodes n, as in the standard CONGEST model). That is, we show a tight bound of (Theta) over tilde (D +root W/c) rounds, where D refers to the latency diameter of the graph, W refers to the total weight of the constructed MST and edges have capacity c. The proposed algorithm sends (O) over tilde (m + W) messages, where m, the total number of edges in the network graph under consideration, is a known lower bound on message complexity for MST construction. We also show that Omega(W) is a lower bound for fast MST constructions. When the edge latencies and the corresponding edge weights are unrelated, and either can take arbitrary values, we show that (unlike the sub-linear time algorithms in the standard CONGEST model, on small diameter graphs), the best time complexity that can be achieved is (Theta) over tilde (D + n/c). However, if we restrict all edges to have equal latency and capacity c while having possibly different weights (weights could deviate arbitrarily from), we give an algorithm that constructs an MST in (O) over tilde (D + root nl/c) time. In each case, we provide nearly matching upper and lower bounds.

关键词： Complex networks

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distributed computing framework of intelligent sensor network for electric power internet of things 9

Distributed computing framework of intelligent sensor networ...

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9th ieee Joint international Information Technology and Artificial Intelligence conference, ITAIC 2020

作者： Li, Dawei Yu, Ruimo Song, Chunhe Li, Shu Jia, Gengtao Zhou, Xiaoli Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

The power IoT terminal environment is complex, and current smart sensor sensors have problems such as poor networking capabilities and large processing delays, and few specific edge-side automatic networking capabilities. This paper analyzes and elaborates the distributed intelligent sensor computing framework from the perspective of edge intelligent networking, designs a computing model for intelligent sensors of power Internet of Things terminals, and gives the edge-based deployment of convolutional neural network architecture, data aggregation, model training, and intelligent reasoning. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 ieee.

关键词： Internet of things

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