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

共 30762 条记录，以下是721-730 订阅

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Q-SCALE: Quantum computing-based sensor Calibration for Advanced Learning and Efficiency 5

Q-SCALE: Quantum computing-based Sensor Calibration for Adva...

引用

2024 international conference on Quantum computing and Engineering

作者： Bergadano, Lorenzo Ceschini, Andrea Chiavassa, Pietro Giusto, Edoardo Montrucchio, Bartolomeo Panella, Massimo Rosato, Antonello Politecn Torino Turin Italy Univ Roma La Sapienza Rome Italy Univ Naples Federico II Naples Italy

ISBN: (纸本)9798331541378

In a world burdened by air pollution, the integration of state-of-the-art sensor calibration techniques utilizing Quantum computing (QC) and Machine Learning (ML) holds promise for enhancing the accuracy and efficiency of air quality monitoring systems in smart cities. This article investigates the process of calibrating inexpensive optical fine-dust sensors through advanced methodologies such as Deep Learning (DL) and Quantum Machine Learning (QML). The objective of the project is to compare four sophisticated algorithms from both the classical and quantum realms to discern their disparities and explore possible alternative approaches to improve the precision and dependability of particulate matter measurements in urban air quality surveillance. Classical Feed-Forward Neural Networks (FFNN) and Long Short-Term Memory (LSTM) models are evaluated against their quantum counterparts: Variational Quantum Regressors (VQR) and Quantum LSTM (QLSTM) circuits. Through meticulous testing, including hyperparameter optimization and cross-validation, the study assesses the potential of quantum models to refine calibration performance. Our analysis shows that: the FFNN model achieved superior calibration accuracy on the test set compared to the VQR model in terms of lower L1 loss function (2.92 vs 4.81);the QLSTM slightly outperformed the LSTM model (loss on the test set: 2.70 vs 2.77), despite using fewer trainable weights (66 vs 482).

关键词： Quantum computing Quantum Machine Learning sensor Calibration Air Pollution Monitoring Sequence Learning

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Adaptive Multi-Core Real-Time Scheduling Based on Reinforcement Learning 18

Adaptive Multi-Core Real-Time Scheduling Based on Reinforcem...

引用

ieee 18th international conference on Control and Automation (ICCA)

作者： Liang, Yonghui Li, Hui Shen, Fei Xu, Qimin Hua, Shuna Zhu, Shanying Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manag Shanghai 200240 Peoples R China Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol Key Lab Wireless Sensor Network & Commun Shanghai 200050 Peoples R China North Informat Control Res Acad Grp Co Ltd Nanjing 211153 Peoples R China

ISBN: (纸本)9798350354416;9798350354409

With the transformation towards industrial intelligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure execution of sensing, computing and actuating tasks under time constraints. However, existing scheduling methods result in either low CPU utilization or many missed task deadlines in dynamic systems. In this paper, we propose a two-layer scheduling architecture to address this issue by fully exploring the complex dependency between real-time tasks. To be specific, the local layer determines task execution priorities considering both dependency between tasks and deadline constraints by utilizing a reinforcement learning approach. Moreover, to better utilize the parallel capabilities of multi-core processors and reduce temporal collisions, this paper minimizes the requested core count for the task set based on a greedy strategy. The global layer designs a scheduling algorithm based on the preempt method and provides schedulability analysis of multiple task sets. Experimental results validate the correctness of the proposed scheduling approach, and efficiency is demonstrated through comparisons with baseline method.

关键词： Networked control systems

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Utilizing Blockchain Technology for Financial Services in Parallel, distributed, and Grid computing Frameworks

Utilizing Blockchain Technology for Financial Services in Pa...

引用

2024 international conference on computing and Intelligent Reality Technologies, ICCIRT 2024

作者： Chokkamreddy, Prakash Palagati, Anusha Rao, Akurathi Lakshmi Pathi Maheswari, P. Mahadevan, Vanitha Balan, Santhosh Kumar School of Management Studies Guru Nanak Institutions Technical Campus Ibrahimpatnam Hyderabad India Dept. of Computer Science and Engineering Guru Nanak Institute of Technology Ibrahimpatnam Hyderabad India Department of Computer Applications KSR College of Arts and Science for Women Tiruchengode India College of Engineering and Technology University of Technology and Applied Sciences Al Mussanah Oman

ISBN: (纸本)9798331510299

Application of blockchain in financial services has opened new ways of efficiency in transaction processing, assets management and security. The application of parallel, distributed, and grid computing with blockchain in improving the functionality of financial services like real time financial transactions, high frequency trading, portfolio and risk analysis is examined in this paper. It has been ascertained that namely parallel and distributed computing together with blockchain are the most suitable for facing increasing needs in data in the sphere of financial services. It also investigates the use of grid computing frameworks and their effects on the correspondingly balanced flows of medium amongst multiple systems. Various issues such as security, privacy violations, and adherence to the law are also reviewed, and existing prospects for developing through smart contracts and consensus mechanisms using blockchain. Exploring how some of the most successful pilot use-cases of blockchain are applicable for future growth in the financial services industry offers insights into how blockchain will soon enter mainstream as a disruptive technology in the broader global financial sector. © 2024 ieee.

关键词： Smart contract

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Method of Data Processing System Synthesis for Heterogeneous distributed Databases Based on Network-Centric Control 12

Method of Data Processing System Synthesis for Heterogeneous...

引用

12th ieee international conference on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications, IDAACS 2023

作者： Mukhin, Vadym Kornaga, Yaroslav Zavgorodnii, Valerii Bazaka, Yurii Zavgorodnya, Anna Mukhin, Oleg National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of System Design Kiev Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Information Systems and Technologies Kiev Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of the Artificial Intellect National Technical University of Ukraine Kiev Ukraine

ISBN: (纸本)9798350358056

The methodology for the synthesis of a distributed computer system that includes the database was developed. There are suggested the new models for the data processing parameters evaluation and along with the analysis and forecasting of the functional parameters. The proposed methods for the number of data processing nodes determining in the systems with dynamic structure based on a network-centric control mechanism allows increase the efficiency of the heterogeneous distributed databases. The implementation of the proposed methodology allows synthesizing a distributed data processing system for processing requests to heterogeneous databases, taking into account the parameters of the nodes and the bandwidth of the channels between the nodes. © 2023 ieee.

关键词： characteristic heterogeneous distributed database method methodology for the synthesis node parameter

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DQN Based distributed Cooperative Spectrum Sensing for Multiband Multiuser CRN 2

DQN Based Distributed Cooperative Spectrum Sensing for Multi...

引用

2nd ieee international conference on Device Intelligence, computing and Communication Technologies, DICCT 2024

作者： Kothari, Mayank Kurumbanshi, Suresh Department of Electronic and Telecommunication Engineering Shirpur India

ISBN: (纸本)9798350372847

While 5G networks are still being deployed and optimized worldwide, research and development efforts are underway for 6G technology. Massive machine-type communication of 5G has tremendously improved voice and data communication quality. However, it cannot meet future technology requirements in 2030 and beyond. To meet the future demands of users, 6G will provide a high data rate with high reliability and ultra-low latency by accommodating the large number of users in the network. However, the spectrum scarcity problem is one of the key restrictions in achieving future users' needs. Cognitive radio technology helps the 6G network to address the shortage of frequency bands for allocation of channels on dynamic basis. This paper gives detailed review cooperative multi-band spectrum sensing for centralized and distributed systems. It demonstrates that distributed cooperative multi-band sensing dominates over other centralized sensing techniques due to the non-requirement of fusion centers and would be more appropriate in applications like the Internet of Vehicles, unmanned aerial vehicles, Vehicular ad-hoc networks and Machine learning and Reinforcement learning-based cooperative multi-band spectrum sensing techniques determine spectrum holes with very high accuracy.. In proposed work, Multiband Multiuser CRN environment in created in python and performance of distributed cooperative spectrum sensing is determined using deep Q Networks. © 2024 ieee.

关键词： Vehicular ad hoc networks

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2024 11th international conference on Software Defined systems, SDS 2024

2024 11th International Conference on Software Defined Syste...

引用

11th ieee international conference on Software Defined systems, SDS 2024

ISBN: (纸本)9798331518325

The proceedings contain 27 papers. The topics discussed include: architecting a SDS for microservices-based distributed edge computing systems;holon programming model: a software-defined approach for system of systems;towards a metamorphic testing architecture for software-defined drone systems;mitigating security vulnerabilities in offline USSD payments in non-smartphones;towards a resilient multi-agent controller: securing and mitigating overhead in tactical SDN;resilient software defined satellite networks: combining clustering techniques with efficient routing protocols;toward automating Cooja experiment workflows for dataset generation;and software-defined support for the execution of task-graph-based applications on cloud environments.

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Data Clustering and Routing using Improved Water Wave Optimization in Wireless sensor Network 5

Data Clustering and Routing using Improved Water Wave Optimi...

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5th ieee international conference on Communication, computing and Industry 6.0, C2I6 2024

作者： Sivakami, K. Arunkumar, S. Usharani, Ms. P. Dhanasekar, J. Kokilamani, S. Revathi, N. Nehru Institute of Engineering and Technology Department of Ece Coimbatore India J.J College Engineering and Technology Department of Ece Coimbatore India Sri Eshwar College of Engineering Department of Ece Coimbatore India Dr. Mahalingam College of Engineering and Technology Department of Ece Coimbatore India

ISBN: (纸本)9798350379884

Wireless sensor Networks (WSNs) are pivotal in various applications where data collection from distributed sensors is essential. However, optimizing data collection efficiency while preserving energy resources remains a challenge. A data clustering model proposed in this paper implements the concept of Water Wave Optimization (WWO) methodology. The purpose of using Water Wave Optimization in this paper is to improve the accuracy of data grouping. We have suggested a grouping model using WWO, the recommended method aims to improve the accuracy of data clustering. We have demonstrated the validity of the proposed idea through the Friedman test and statistical analysis. Experiments revealed that the suggested grouping model works, as evidenced by its higher accuracy rate. In the past decade, routing in Wireless sensor Networks has emerged as the focus of most research. Implementing a routing model that can determine the most beneficial path depending on an assortment of performance parameters is an extensive task. Then it has been demonstrated that after being compared to the currently employed clustering approach, the accuracy and F-score rates of the proposed WWO techniques improved by an average of 4% and 7%, respectively. © 2024 ieee.

关键词： Data accuracy

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Routing Drones Being Aware of Wind Conditions: a Case Study 17

Routing Drones Being Aware of Wind Conditions: a Case Study

引用

17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Palazzetti, Lorenzo Univ Florence Dept Comp Sci Florence Italy

ISBN: (纸本)9781665439299

In this paper, we investigate the manner in which energy consumption in drone deliveries is affected by windy environmental conditions. We know in fact that the energy consumption of the drone will depend on the static and dynamic parameters of the scenario where it moves and according to these it decides, during the mission, to detour from the originally planned path to take advantage of the wind changes. In order to validate this, we simulate possible deliveries among fixed destinations relying on a real data-set of recorded winds obtained from different weather stations in Corsica, France. For our analysis, we will mainly concentrate on the evaluation of the delivery scheme proposed in the literature, where completing a delivery means finding a cycle for the drone that is feasible, i.e., that can be completed with the available energy autonomy of the drone.

关键词： Wind Energy consumption Routing sensor systems Batteries distributed computing Drones

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Analysis of the Influence of distributed Photovoltaic Dynamic Characteristics on Energy Measurement 5

Analysis of the Influence of Distributed Photovoltaic Dynami...

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5th ieee international conference on Power, Intelligent computing and systems, ICPICS 2023

作者： Liu, Li Sun, Zhimin Chen, Xueyan Zhong, Licai Guo, Jianghong Lanzhou Resources and Environment Voc-Tech University Lanzhou China

ISBN: (纸本)9798350333442

In response to the issue of adapting to the dynamic characteristics of distributed photovoltaics and their impact on energy metering, this article first simulates and analyzes the harmonic and voltage fluctuations caused by photovoltaic grid connection based on a universal 400 kW distributed photovoltaic grid connection system model, and summarizes the characterization formula of distributed photovoltaic grid connection dynamic characteristics;Then, based on the characteristics of harmonics and voltage fluctuations, the error characteristics of electricity metering were quantitatively analyzed through simulation;Finally, in view of the impact of the microgrid access of distributed generation to the power system on electric energy measurement, this paper summarizes the function problem of two-way electric energy measurement and the accuracy of electric energy measurement devices, and discusses the rationality of electric energy measurement. © 2023 ieee.

关键词： Harmonic analysis

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Auto-Scaling Service Strategy for distributed Satellite System 6

Auto-Scaling Service Strategy for Distributed Satellite Syst...

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6th ieee international conference on Electronics and Communication Engineering, ICECE 2023

作者： Jin, Yifeng Liu, Wei Tao, Ying Zhang, Lei Gao, Zihe Shi, Yulin China Academy of Space Technology Institute of Telecommunication and Navigation Satellites Beijing China

ISBN: (纸本)9798350328721

In this paper, we investigate a scenario where a distributed satellite system (DSS) serves as a distributed computing platform within the space-terrestrial integrated network (STIN), catering to ground users. To enhance the scalability of the distributed computing system and adapt to variations in user request traffic, we propose an auto-scaling service strategy based on traffic prediction. The prediction is implemented using the long short-term memory recurrent neural network (LSTM-RNN) method. Numerical results are presented to demonstrate the superiority of our proposed traffic prediction algorithm compared to existing approaches, while experimental findings confirm that our auto-scaling service strategy effectively enhances system performance in terms of service quality. © 2023 ieee.

关键词： distributed computer systems

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