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Federated Semi-Supervised Learning with Local and Global Updating Frequency Optimization 24

Federated Semi-Supervised Learning with Local and Global Upd...

引用

24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCgrid)

作者： Hang, Xin Xu, Yang Xu, Hongli Liao, Yunming Wang, Lun Univ Sci & Technol China Sch Comp Sci & Technol Hefei Peoples R China Univ Sci & Technol China Suzhou Inst Adv Study Suzhou Peoples R China

ISBN: (纸本)9798350395679;9798350395662

Federated learning (FL) has gained important attention for training deep learning models across clients in edge computing. The scarcity of labeled data poses critical challenges in professional fields (e.g., medical diagnosis) for FL, motivating the development of federated semi-supervised learning (FSSL) to exploit unlabeled data. The existing works of FSSL always assign fixed values for global updating frequency and/or local updating frequency during training. Though the previous works can make full use of unlabeled data, they may still hinder the improvement of model performance on heterogeneous clients, due to that the two hyper-parameters are coupled and have a joint impact on training process. To this end, we propose a novel FSSL framework, named LOGO, to enhance training efficiency by jointly optimizing local and global updating frequencies. We analyze the coupled impact of these two hyper-parameters on model training. Then, we develop a multi-armed bandit (MAB) based online algorithm to adaptively determine diverse local updating frequencies for heterogeneous clients as well as appropriate global updating frequency, so as to address system heterogeneity and improve training efficiency. The performance of LOGO is evaluated through extensive simulation experiments. The experimental results demonstrate that LOGO achieves the model training speedup by 2.3x and reduces communication cost by 44%, compared to the baselines.

关键词： edge computing Federated Learning Semi-supervised Learning System Heterogeneity.

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A Light-Weight Tool-Supported Method for Cyber Risk Assessment in the Planning of Cyber-Physical Smart grids

A Light-Weight Tool-Supported Method for Cyber Risk Assessme...

引用

2024 international conference on Communications Control and computing Technologies for Smart grids

作者： erdogan, Gencer Zerihunt, Tesfaye Amare Sperstadt, Her Bakken Gjerdet, Oddbjorn Sustainable Commun Technol SINTEF Digital Oslo Norway SINTEF Energi Energy Syst Trondheim Norway

ISBN: (纸本)9798350318562;9798350318555

A major challenge during grid planning is the identification of cybersecurity threats potentially introduced by active digital measures. This challenge arises because grid planning occurs at an early, conceptual stage, typically years ahead of realization, and often lacks concrete information about the active digital measures at this early phase. This highlights the need for simple, user-friendly cyber risk assessment methods that grid planners can use, even without detailed information about the final solutions. To address this need, we propose a lightweight, tool-supported, six-step method. This method employs the Customer Journey Modeling Language (CJML), which is comprehensible to various professional backgrounds, and which we have adapted to include the necessary cybersecurity concepts to help grid planners identify cybersecurity threats. The method is supported by our freely available, open-source risk modeling tool. Using a case based on a real-world electricity distribution grid, we demonstrate how our method supports grid planners in performing cyber-risk assessments with limited information about the final solutions and their vulnerabilities to cyber threats. Preliminary results indicate that our method is effective in enabling grid planners to assess potential cybersecurity risks during the planning phase, thereby enhancing the reliability and security of future electricity distribution systems.

关键词： cybersecurity risk assessment light-weight tool-supported method cyber-physical smart grid planning

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Distributed computing architecture and data communication implementation method of distribution network auxiliary planning platform 5

Distributed computing architecture and data communication im...

引用

5th international conference on Artificial Intelligence and electromechanical Automation, AIeA 2024

作者： Wang, Xiaobing Ding, Wenshu Jiang, Nian Yang, Kun Wang, Yuling Shen, Wenchang Wu, Qian State Grid Taizhou Power Supply Company Taizhou225300 China Science & Technology Co. Ltd. Department of Planning Center Hangzhou310012 China Science & Technology Co. Ltd. R&d Center Beijing102206 China

ISBN: (纸本)9798350366174

With the rise of big data, the planning and management of intelligent distribution networks have ushered in new development opportunities. Through the comprehensive integration, in-depth analysis, and effective mining of a large amount of heterogeneous data in the distribution network, various problems and challenges encountered in the planning process of intelligent distribution networks can be effectively addressed. However, this process relies on powerful computing power as support. This study focuses on exploring methods for deploying distributed computing communication in cluster environments to efficiently, flexibly, and reliably perform various tasks. By analysing the calculation time of actual power grid planning data, this study verifies the effectiveness and practicality of the proposed distributed computing architecture and communication design scheme. © 2024 ieee.

关键词： Power distribution planning

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Cyber Framework for Steering and Measurements Collection Over Instrument-computing ecosystems 9

Cyber Framework for Steering and Measurements Collection Ove...

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ieee international conference on Smart computing (SMARTCOMP)

作者： Al-Najjar, Anees Rao, Nageswara S. V. Sankaran, Ramanan Zandi, Helia Mukherjee, Debangshu Ziatdinov, Maxim Bridges, Craig Oak Ridge Natl Lab Oak Ridge TN 37830 USA

ISBN: (纸本)9798350322811

We propose a framework to develop cyber solutions to support remote steering of science instruments and measurements collection over instrument-computing ecosystems. It is based on provisioning separate data and control connections at the network level, and developing software modules consisting of Python wrappers for instrument commands and Pyro server-client codes that make them available across the ecosystem network. We demonstrate automated measurement transfers and remote steering operations in a microscopy use case for materials research over an ecosystem of Nion microscopes and computing platforms connected over site networks. The proposed framework is currently under further refinement and being adopted to science workflows with automated remote experiments steering for autonomous chemistry laboratories and smart energy grid simulations.

关键词： science workflows science instrument ecosystems

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Intelligent Monitoring Technology of Two-ticket System for Safety Production in Power grid enterprise 4

Intelligent Monitoring Technology of Two-ticket System for S...

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4th international conference on New energy and Power engineering, ICNePe 2024

作者： Huang, Chengwei Zeng, Jia Zhang, Fayan Zhang, Wenxiao Lai, Zhaoyang Hezhou Power Supply Bureau Guangxi Power Grid Co. Ltd. Province Guangxi China Guangxi Power Grid Co. Ltd. Province Guangxi China Hohai University College of Information Science and Engineer Changzhou China

ISBN: (纸本)9798331516086

This paper studies the advancement of intelligent monitoring methods of the two-ticket system for power grid operations. It is known that the manual monitoring strategies are inadequate for addressing the sophisticated demands of contemporary power grid safety. To bridge this gap, this paper introduces an innovative smart surveillance system that leverages the prowess of artificial intelligence (AI) and edge computing. This system is designed to provide real-time oversight of the two-ticket execution process, ensuring that all safety protocols are adhered to without delay. By integrating AI for pattern recognition and edge computing for on-site data processing, the proposed system enhances the efficiency and reliability of power grid operations, thereby fortifying the overall safety management framework. © 2024 ieee.

关键词： Power grids

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Complex Graph Laplacian Regularizer for Inferencing grid States 14

Complex Graph Laplacian Regularizer for Inferencing Grid Sta...

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14th ieee international conference on Communications, Control, and computing Technologies for Smart grids, SmartgridComm 2023

作者： Dinesh, Chinthaka Wang, Junfei Cheung, Gene Srikantha, Pirathayini York University Department of Electrical Engineering and Computer Science TorontoON Canada

ISBN: (纸本)9781665455541

To maintain stable grid operations, system monitoring and control processes require the computation of grid states (e.g., voltage magnitude and angles) at high granularity. It is necessary to infer these grid states from measurements generated by a limited number of sensors like phasor measurement units (PMUs) that can be subjected to delays and losses due to channel artefacts, and/or adversarial attacks (e.g. denial of service, jamming, etc.). We propose a novel graph signal processing (GSP) based algorithm to interpolate states of the entire grid from observations of a small number of grid measurements. It is a two-stage process, where first an underlying Hermitian graph is learnt empirically from existing grid datasets offline. Then, the graph is used to interpolate missing grid signal samples online in linear time. With our proposal, we can reconstruct grid signals with significantly smaller number of observations when compared to traditional approaches (e.g. state estimation). In contrast to existing GSP approaches, we do not require knowledge of the underlying grid structure and parameters and are able to guarantee fast spectral optimization. We demonstrate the computational efficacy and accuracy of our proposal via practical studies conducted on the ieee 118 bus system. © 2023 ieee.

关键词： Phasor measurement units

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The Use of Power IoT Technology in Power grid enterprises: Technological Methods and empirical Research for enhancing New Quality Productivity 5

The Use of Power IoT Technology in Power Grid Enterprises: T...

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5th international conference on Smart grid and energy engineering, SGee 2024

作者： Li, Meng Wang, Yibo Ma, Jiaxin Zuo, Jing Chen, Junshu Li, Xiaotian Guangdong Power Grid Co. Ltd. Guangzhou China Management Science Research Institute Guangdong Power Grid Corporation Guangzhou China

ISBN: (纸本)9798331530686

In the pursuit of new quality productivity within power grid enterprises, Power Internet of Things (IoT) technology has been widely adopted as a core tool. This work first analyzes the technological needs of power grid enterprises in enhancing new quality productivity, highlighting the roles of key technologies such as big data, edge computing, and intelligent devices. It then constructs a Power IoT architecture based on technologies like big data, edge computing, and cloud computing to improve the new quality productivity of power grid enterprises. An empirical study of a power grid enterprise is conducted to validate the effectiveness of this Power IoT architecture. The results indicate that after implementing Power IoT, the enterprise's energy efficiency improvement rate increases by 146.2%, equipment failure rate decreases by 52.3%, operation and maintenance costs are reduced by 30%, and load control response time is shortened by 46.7%. These outcomes demonstrate the significant impact of Power IoT technology on enhancing new quality productivity in power grid enterprises. The findings provide a solid basis for implementing intelligent technologies in power grid enterprises and promote the development of power systems towards greater efficiency and intelligence. © 2024 ieee.

关键词： empirical Research New Quality Productivity Power grid enterprises Power IoT

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Power grid encrypted Data Range Filtering Scheme Based on Order-revealing encryption 21

Power Grid Encrypted Data Range Filtering Scheme Based on Or...

引用

21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big Data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Qiao, Hongyi Peng, Cong Luo, Min Wu, Po He, Debiao Wuhan University School of Cyber Science & Engineering Wuhan China Electric Power Research Institute State Grid Henan Electric Power Company Zhengzhou China

ISBN: (纸本)9798350329223

As the power Internet of Things (IoT) system accelerates, the IoT end devices within the power grid show an explosive growth, and generate massive electricity consumption data. While the diverse encryption technologies currently employed in the existing power grid system offer a degree of data privacy protection, they also make it difficult to filter and screen the data of the original node in the link. In addition, the traditional cryptographic technology can not resist the attack of uploading invalid data from the malicious terminal in the case that the power terminal is controlled by a malicious adversary. To address this issue, this paper presents an efficient bilinear pairing-free order-revealing encryption scheme (r-ORe) based on the modified GQ protocol, and constructs a power grid encrypted data range filtering scheme to realize the comparison of ciphertext without disclosing plaintext information. The scheme allows the IoT terminals in the power grid, such as smart meters, to encrypt the electricity consumption data before sending it to the edge server, and to filter the range of encrypted data through the query range ciphertext generated by the data center. The experimental evaluation shows that our r-ORe surpasses Cash et al.'s scheme in terms of execution costs, and its extended scheme is practical in the power grid environment. © 2023 ieee.

关键词： Internet of things

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Real-time and Scalability of Smart Two Ticket System Based on edge computing in Power grid Management 2

Real-time and Scalability of Smart Two Ticket System Based o...

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2nd international conference on Data science and Information System, ICDSIS 2024

作者： Huang, Chengwei Zeng, Jia Zhang, Fayan Zhang, Yubo Zhang, Wei Power Supply Bureau Of Guangxi Hezhou Power Grid Co. Ltd. Hezhou China Jia Zeng Guangxi Power Grid Co. Ltd. Nanning China Electric Power Research Institute Of Guangxi Power Grid Co. Ltd. Guangxi Key Laboratory Of Intelligent Control And Operation And Maintenance Of Power Equipment Nanning China

ISBN: (纸本)9798350381665

With the continuous development of Internet of Things (IoT) technology, edge processing platforms for power system characteristics have become an important technology. At present, many professional information systems of State grid Corporation of China are faced with the problem that information cannot be shared and collected. It is urgent to use the idea of the Internet of Things, high-performance edge computing and other methods to build an intelligent Internet of Things system. In this paper, a new intelligent Internet of Things system based on edge computing was studied according to the application requirements of smart grid for dynamic control, strategy management, data preprocessing, etc., aiming to reduce network transmission capacity, reduce operating costs, and further optimize equipment maintenance costs. Simulation experiments have shown that when the number of Centralized Unit of execution and Heterogeneous Unit of execution in the network was increased to 70 and 100, respectively, the unloading completion times of the schemes 'HUe Cloud edge' and 'HUe-Cloud edge GM' were between 0.25-0.45 and 0.2-0.4, respectively, which were lower than those of cloud and HUeCloud Randomness. © 2024 ieee.

关键词： edge computing

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Advancements in Smart grids: Harnessing AI, IoT, and 5G Integration for Sustainable energy Management 1

Advancements in Smart Grids: Harnessing AI, IoT, and 5G Inte...

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1st ieee international conference on Advances in Signal Processing, Power, Communication, and computing, ASPCC 2024

作者： Mishra, Debani Prasad Preyaadarshini, Barsa Mishra, Kriti Kumar, Ayush Lenka, Rakesh Kumar International Institute of Information Techonology Electrical and Electronics Engineering Bhubaneswar India Central University of Odisha Department of Computer Science Odisha Koraput India

ISBN: (纸本)9798350355093

The conventional smart grid, while enhancing electricity networks, lacks advanced features such as automatic decision-making, security, scalability, and real-time monitoring. The integration of Artificial Intelligence (AI) and Machine to Machine (M2M) communication, supported by the evolving communication infrastructure, promises a transformative next-generation smart grid. This paper provides a comprehensive review of emerging trends and technological foundations, envisioning a future smart grid propelled by AI and empowered by the Internet of Things (IoT) and 5G. Addressing integration challenges, it proposes solutions and discusses standards crucial for optimal smart grid architecture. Future work will focus on implementing this integration using tools like Matlab, NS2/NS3, Open Daylight, and Mininet, comparing outcomes with existing literature. © 2024 ieee.

关键词： Smart power grids

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