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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

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Dual-Hop Robust distributed Collaborative Beamforming Over Nominally Rectangular WSNs in Slightly to Moderately Scattered Environments 19

Dual-Hop Robust Distributed Collaborative Beamforming Over N...

引用

19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Ben Smida, Oussama Affes, Sofiene Univ Qubec INRS EMT Montreal PQ H5A 1K6 Canada

ISBN: (纸本)9798350333398

We propose a new distributed collaborative beam-forming (DCB) solution that is robust (i.e., RDCB) against major channel estimation impairments over dual-hop transmissions through a wireless sensor network (WSN) of K nodes with a nominally deterministic geometry, presumably rectangular (or a fortiori square). the source S first sends its signal to the WSN. then, each node forwards its received signal to the destination D after multiplying it by a properly selected beamforming weight. the latter aims to minimize the received noise power while maintaining the desired one equal to unity at the destination D. these weights depend on some channel state information (CSI) parameters. Hence, they have to be estimated locally at each node or fed back to it;resulting in either case in channel parameter estimation or feedback errors that could severely hinder DCB performance. Due to lack of space, we only account here for nodes location placement errors which would always amount to some additional phase error. Accounting for the massive connectivity characterizing new 5G and future 5G+/6G wireless technologies and the Internet of things (IoT), we develop alternative RDCB solutions that properly adapt both to monochromatic [i.e., line-of-sight (LoS)] and bichromatic (i.e., slightly to moderately scattered) propagation scenarios over the first hop while always assuming a LoS link over the second;referred to hereafter as MM-RDCB and BM-RDCB, respectively. We do so by exploiting i) very efficient asymptotic approximations at large numbers K of the WSN nodes and ii) the nominal geometric symmetries of their deterministic (rectangular or square) grid shapes. Furthermore, our new MM-RDCB and BM-RDCB solutions are distributed since their weights can be locally computed at every terminal, thereby dramatically improving both spectral and power efficiencies of the WSN. Simulation results show considerable gains and robustness of the proposed techniques in terms of achieved signal-to-nois

关键词： collaborative beamforming (CB) distributed CB (DCB) robust DCB (RDCB) wireless sensor network (WSN) deterministic WSN positions square and rectangular grids low to moderate angular spread channel mismatch nodes location placement errors synchronization localization direction-of-arrival (DoA)

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Energy Efficiency in Blockchain Networks: Analyzing Power Consumption of Consensus Mechanisms and Hash Functions 6

Energy Efficiency in Blockchain Networks: Analyzing Power Co...

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6th international conference on Blockchain computing and Applications, BCCA 2024

作者： Sengupta, Souvik Sengupta, Banhirup Sinaeepourfard, Amir Shaik, Shehenaz IONOS SE Germany Department of Mathematics IISC Bangalore India Norway East Tennessee State University United States

ISBN: (纸本)9798350351538

Organizations worldwide are under pressure to reduce their use of non-renewable energy sources and carbon emissions due to their increasing negative impact on the ongoing climate crisis. Blockchain technology, popularized by its use in Bitcoin, has been adopted for various use cases but is criticized for its high energy consumption, depending on the consensus mechanism used. Consensus mechanisms are vital for securing blockchain networks by ensuring all nodes agree on the ledger’s state, but they often trade-off between low energy consumption and high security. this paper analyzes the critical factors contributing to power consumption in blockchain networks, focusing on consensus mechanisms and hashing techniques. through a comprehensive State-of-the-Art (SOTA) review and algorithmic analysis, we examine how various consensus algorithms impact energy usage and detail the computational and space complexities of different hashing algorithms. We also investigate the energy profiles and reduction strategies of major blockchain platforms. Our findings highlight the potential to enhance blockchain energy efficiency without compromising security or performance, providing a foundation for future research in sustainable blockchain technologies. © 2024 ieee.

关键词： distributed ledger

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Challenges and Opportunities of DevOps in Cyber-Physical Production systems Engineering 6

Challenges and Opportunities of DevOps in Cyber-Physical Pro...

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ieee 6th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Koren, Istvan Rinker, Felix Meixner, Kristof Matevska, Jasminka Walter, Joerg Rhein Westfal TH Aachen Chair Proc & Data Sci Aachen Germany TU Wien Inst Informat Syst Engn Christian Doppler Lab SQI Vienna Austria City Univ Appl Sci Sch Elect Engn & Comp Sci Bremen Germany OFFIS Inst Informat Technol Distributed Comp & Commun Oldenburg Germany

ISBN: (纸本)9798350311259

DevOps is a set of practices that combines software development and operations to enable a continuous software product life cycle to improve the quality of software systems. Although DevOps is considered successful for typical software systems, it has not yet been widely adopted in the area of CyberPhysical Production systems (CPPSs) that integrate physical components with computer-based control and communication systems. Related to industrial settings, many new challenges arise, like long-term investments, missing flexibility in asset-heavy production environments, and the inherent physicality of hardware. this paper examines the use of the DevOps methodology in the manufacturing domain. It identifies and discusses the unique challenges and describes first solution proposals to overcome those challenges, based on literature and experiences from the industry. the article provides useful guidance to researchers and practitioners on potential pitfalls and exciting opportunities.

关键词： DevOps Continuous Integration Digital Transformation Cyber-Physical Production systems Engineering Research Challenges

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Simulation Research on the Natural Gas Flow sensor Based the MEMS Technology 6

Simulation Research on the Natural Gas Flow Sensor Based the...

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6th international conference on Communications, Information System and Computer Engineering, CISCE 2024

作者： Zhang, Jie Zhang, Peng Gu, Lingfeng Zhang, Yanfang Zhao, Lina Cao, Qiang Intelligent Manufacturing and Automobile School Chongqing College of Electronic Engineering Chongqing China School of Artificial Intelligence and Big Data Chongqing College of Electronic Engineering Chongqing China

ISBN: (纸本)9798350353174

Due to its unique advantages, the MEMS technology exhibits obvious interdisciplinary characteristics, and is crossly applied with the sensor technology that yields the MEMS sensor technology. the emerging MEMS sensor technology then gained many unique advantages, such as small volume, light weight, high precision, and high integration etc. In this paper, the temperature field distribution and the flow field distribution of the thermal gas flow sensor based on the MEMS technology are simulated and discussed. the simulation results show that the temperature near the area of the heating resistor is the highest when there is no gas flow, and that the temperature field is symmetrically distributed along the x-axis. However, when the gas flows passing through, the symmetry of the temperature field is destroyed, and the farther away from the heating resistor, the more seriously the symmetry is destroyed. At the same time, the greater the vertical height above from the surface of the heating resistor, the more serious the asymmetry of the temperature field. In the y-direction, the fluid velocity distribution in the area that far away from the surface of the heating resistor is very uniform and basically with no fluctuation. However, in the area that near the surface of the heating resistor, the velocity field distribution fluctuates greatly, especially at the corners of the edges of the resistors. the main reason is the local influence caused by the geometric structure of the resistor. © 2024 ieee.

关键词： Microchannels

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Proceedings - 6th ieee international conference on Fog and Edge computing, ICFEC 2022

Proceedings - 6th IEEE International Conference on Fog and E...

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6th ieee international conference on Fog and Edge computing, ICFEC 2022

ISBN: (纸本)9781665495240

the proceedings contain 15 papers. the topics discussed include: good shepherds care for their cattle: seamless pod migration in geo-distributed Kubernetes;edge workload trace gathering and analysis for benchmarking;SIMORA: simulating open routing protocols for application interoperability on edge devices;high-level metrics for service level objective-aware autoscaling in Polaris: a performance evaluation;specification and operation of privacy models for data streams on the edge;evaluation of control over the edge of a configurable mid-band 5G base station;efficient runtime profiling for black-box machine learning services on sensor streams;optimal timing for bandwidth reservation for time-sensitive vehicular applications;and SDN-based service discovery and assignment framework to preserve service availability in telco-based multi-access edge computing.

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Cross-sensor Maritime Target Recognition Algorithm Based on Heterogeneous sensor Shared Representation Learning 6

Cross-sensor Maritime Target Recognition Algorithm Based on ...

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6th ieee international conference on Pattern Recognition and Artificial Intelligence, PRAI 2023

作者： Liu, Yihai Jiangsu Automation Research Institute First Research Department Lianyungang China

ISBN: (纸本)9798350325485

We investigate a cross-sensor recognition algorithm for heterogeneous sensors based on shared representation learning to address the difficulty of non-cooperative object recognition in C4ISR systems due to modal barriers, imbalanced data distribution, and few-shot labeled samples. First, deep multiset canonical correlation analysis is used to learn the shared space among heterogeneous sensors by only unlabeled spatiotemporal correlation data from sensors. Second, scattered labeled data from multiple sensors are concentrated in shared space, which removes the modality barrier of each sensor and produces big data samples for training the classification network. Finally, the classification model is trained and directly used to classify the new observations for each sensor in the shared space, which constitutes a general-purpose cross-sensor target recognition. Experiments based on target recording data show that the proposed algorithm can achieve 60-78% accuracy in cross-sensor recognition for radar, ESM, optical, and sonar sensors, indicating a significant engineering value. © 2023 ieee.

关键词： Object recognition

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Empirically Investigating the Impact of Antenna Polarization and Modulation Parameters on Subsoil Communication Range in LoRa Networks 19

Empirically Investigating the Impact of Antenna Polarization...

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19th Annual international conference on distributed computing in Smart systems and the Internet of things, DCOSS-IoT 2023

作者： Nguyen, Nhan D.T. Le, Duc V. Havinga, Paul J.M. University of Twente Pervasive Group Enschede Netherlands

ISBN: (纸本)9798350346497

the Long Range (LoRa) network has been widely acknowledged for its efficiency and reliability in terrestrial sensing applications. However, building a robust LoRa network in the subsoil environment, which presents challenges for radio communication, remains challenging. this study evaluates the impact of antenna polarization and LoRa modulation parameters, such as bandwidth and spreading factor, on subsoil communication ranges. Based on the results of our experiments, we propose practical LoRa network configurations for the seamless transmission of subsoil sensory data to the surface. © 2023 ieee.

关键词： sensor networks

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Fast distributed Stochastic Gradient Descent for Big Data Classification 23

Fast Distributed Stochastic Gradient Descent for Big Data Cl...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Xiao, Mingfei Wang, Huihui School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781665494571

Large-scale classification is an important task of machine learning, especially in the smart city field, which is a big data environment. In recent years, single-threaded optimization algorithms can no longer meet the needs of big data applications. When a single machine is trained, it will face the problem of insufficient memory and limited computing capacity. therefore, distributed algorithms have been proposed to solve big data classification, and have received much attention. Particularly, distributed gradient descent (GD) is a widely-used algorithm for solving big data problem. However, distributed algorithms based on GD always converge slowly and suffer from expensive time in the training process. To alleviate this problem, we propose a novel fast distributed stochastic gradient descent algorithm for big data classification in this paper. By formulating the original optimization problem as a series of subproblems for classification in each machine. In particular, we exploit a fast stochastic method combined with the Nesterov acceleration method for sub-problem optimization in parallel to improve the convergence speed, and thus reduce the training time. the experimental results on some public and benchmark data sets show that our proposed distributed algorithm can converge faster with the competitive accuracy performance compared with distributed GD-based methods, which is suitable to big data classification. © 2021 ieee.

关键词： Training Machine learning algorithms Smart cities Big Data Benchmark testing Classification algorithms distributed algorithms

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A Last Line Naval Defense System Based on Underwater Wireless sensor Network 6

A Last Line Naval Defense System Based on Underwater Wireles...

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6th international conference on Green Energy and Applications (ICGEA)

作者： Tani, Lamia Fatiha Kazi Kadri, Benamar Univ Tlemcen STIC Lab Tilimsen Algeria

ISBN: (纸本)9781665420525

Similar to wireless sensor networks underwater wireless sensor Networks (UWSNs) are composed of hundreds to thousands of tiny sensor nodes;static or dynamic usually communicate using acoustic link this kind of networks has the capacity of acting as similar sensor and detects environment measures such as temperature or pressure as well as movement under water which makes them an ideal tool for underwater radars and remote detection systems for naval forces. In our paper we are going to propose a security mechanism to ensure authentication and confidentiality for a last line defense system. In which an UWSN will be used as platform for last line radar system intended to detect and destroy military targets. the proposed system will act as a rescue system launched when the traditional radar and sonar systems are in the incapacity to detect and destroy targets due to the high technology of the enemy or the destruction of the traditional naval system.

关键词： UWSN radar sonar routing security defense system

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AI Powered COVID-19 Detection System using Non -Contact Sensing Technology and Deep Learning Techniques 18

AI Powered COVID-19 Detection System using Non -Contact Sens...

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18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Kogilavani, S., V Sathishkumar, V. E. Subramanian, Malliga Kongu Engn Coll Dept Comp Sci & Engn Erode Tamil Nadu India Hanyang Univ Dept Ind Engn 222 Wangsimini Ro Seoul 04763 South Korea

ISBN: (纸本)9781665495127

the SARS-CoV-2 virus causes coronary artery disease (COVID-19). the majority of persons who are infected with the virus will have mild to severe respiratory illness and recover without the need for therapy. Some, on the other hand, will become critically unwell and require medical assistance. People over the age of 65, as well as those with underlying medical diseases such as cardiovascular disease, diabetes, chronic respiratory disease, or cancer, are at a higher risk of developing serious illness. Being thoroughly informed on the disease and how it spreads is the best strategy to avoid and slow down transmission. Stay at least 1 metre apart from other people to avoid infection. In this research work, we focus on how non-contact sensing technology and deep learning technique are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. the proposed system captures images from the patient using non -contact sensing technologies and feeds the data into deep learning convolutional neural network architectures such as VGG16, VGG19, ResNet101, NASNet, DenseNet121, MobileNet, Xception, EfficientNet, and InceptionV3. In comparison to other architectures, the VGG16 architecture delivers superior accuracy.

关键词： Non-Contact sensor Deep Learning COVID-19 Health Care Respiratory System VGG16

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