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Big Data Economy and Information Management (BDEIM), international conference on

作者： Dongge Zhu Rui Ma Yufeng Chai Bing Cai Liang Han Electric Power Research Institute of State Grid Ningxia Electric Power Co. Ltd Yinchuan China

ISBN: (纸本)9781665482899

With the vigorous development of the electric power industry, the large amount of data generated has also brought tremendous pressure to information security. Data desensitization model is limited by the computing efficiency and memory capacity of a single computing node, which is difficult to meet the desensitization needs of massive data. Based on Spark parallel computing framework, an automatic desensitization model of energy big data is proposed. Depending on the regular dependence between data sets, the elastic distributed data set is established, and the big data parallel processing framework is established by using Spark framework, which decomposes the single node processing task into multi node data blocks. The distributed anonymization algorithm is designed to divide the buffer tuple to complete the anonymization before desensitization. The reserved number of generalized nodes is determined, and a distributed desensitization model based on cooperative computing of multiple computing nodes is established. The experimental results show that the privacy protection strength of this model is 0.0763 and 0.1007 higher than that of the data desensitization model based on centralized anonymization algorithm and regular specific format when the data set size reaches the maximum of 60G. Therefore, the designed model has good data desensitization ability, and can ensure the privacy of data under the condition of large amount of data.

关键词： Data privacy Computational modeling distributed databases Clustering algorithms Web pages Big Data parallel processing

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Adaptive Load Frequency Control in Multi-area Power Systems with distributed Traffic Attacks Based on Deterministic Network Calculus 7th

Adaptive Load Frequency Control in Multi-area Power Systems ...

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7th international conference on Life System Modeling and Simulation, LSMS 2021, and 7th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2021

作者： Zhang, Yajian Peng, Chen Niu, Yuqing Zheng, Min Department of Automation School of Mechatronic Engineering and Automation Shanghai University Shanghai China Key Laboratory of Smart Grid of Ministry of Education School of Electrical Automation and Information Engineering Tianjin University Tianjin China

ISBN: (纸本)9789811672095

This paper investigates an adaptive load frequency control (LFC) strategy in multi-area power systems with malicious distributed traffic attacks. Based on the deterministic network calculus theory, the analytical relationship between transmission delay and key network parameters is established under different attack levels. Secondly, constraints of controller gain under each attack level are derived by constructing a Lyapunov function. Finally, the most matching controller gain is switched into the controller loop by taking the actual packet transmission delay as the decision variable. Simulation results show that the proposed method can effectively resist the malicious traffic attacks while enhance the reliability of physical-cyber coupling power systems. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Lyapunov functions

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ALLOCATION OF computing TASKS IN distributed MEC SERVERS CO-POWERED BY RENEWABLE SOURCES AND THE POWER grid

ALLOCATION OF COMPUTING TASKS IN DISTRIBUTED MEC SERVERS CO-...

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IEEE international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Cecchinato, Davide Berno, Michele Esposito, Flavio Rossi, Michele Univ Padua Dept Informat Engn Padua Italy St Louis Univ Dept Comp Sci St Louis MO 63103 USA

ISBN: (纸本)9781509066315

We consider a Multiaccess Edge computing (MEC) network where distributed servers have energy harvesting (e.g., solar) and storage (e.g., batteries) capabilities. Energy from a connected power grid is also available, in case that harvested from ambient sources is scarce or absent. Network processors are deployed according to a given network topology, across two tiers, and computing tasks are flexibly allocated depending on considerations related to load balancing, energy consumption (for communication and computing) and energy purchases from the power grid. Specifically, an on-line optimization problem, exploiting a predictive control approach, is formulated to minimize the monetary cost incurred in the energy purchases from the power grid, by dispatching the computation jobs to those servers that have enough energy and computation resources. Our proposed framework uses forecasts of exogenous processes, such as the amount of energy harvested and job arrivals, which are estimated on the fly to steer the allocation of computation jobs to the servers.

关键词： Renewable Edge Networks Sustainable Edge computing Energy Harvesting

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Single-Phase Grounding Line Selection Method for Distribution Network with New Energy

Single-Phase Grounding Line Selection Method for Distributio...

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international conference on Cyber Security Intelligence and Analytics, CSIA 2021

作者： Chen, Shijun Jiang, Hua Li, Ming State Grid Xuzhou Power Supply Company Xuzhou Jiangsu China School of Electrical and Power Engineering China University of Mining and Technology Xuzhou Jiangsu China

ISBN: (纸本)9783030700416

By analyzing the transient and steady-state property of zero-sequence component in traditional network when grounding fault happens, the property of grounding fault with new energy access to distribution network are deeply studied. By comparing the similarities and differences of fault characteristics between traditional distribution network and new energy access network when grounding fault happened, a line selection method for the network is proposed, and it has been proved by simulation and experiment. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： distributed power generation

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A hierarchical control scheme with bi-level communication networks for the interconnected DC microgrids cluster

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international JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年第PartB期142卷

作者： Li, Li Dong, Mi Chen, Xiaojiao Yi, Feng Chen, Guo Song, Dongran Yang, Jian Cent South Univ Sch Automation Changsha 410083 Peoples R China Chinese Acad Sci Inst Plasma Phys Hefei 230031 Peoples R China

This paper proposes a hierarchical control scheme based on distributed alternating direction method of multipliers (ADMM) for the interconnected DC microgrids cluster. This scheme is fully distributed and consists of three coordinated control levels through bi-level distributed communication networks. The constraints of the economic dispatch problem are decoupled for tertiary control and decomposed into global and local optimization problems using the ADMM framework. To realize parallel computing of ADMM, we designed a fast second-order distributed average consensus algorithm to estimate the global average exchanged value and the average output power of a single microgrid, thus removing the coupling within the microgrids cluster and individual microgrid. Considering the voltage deviation caused by the traditional droop control, voltage control without droop based on the distributed algorithm is proposed to realize voltage restoration and power distribution among dispatchable generators for individual microgrid, combined with traditional primary and secondary control. Numerical simulations of an off-grid microgrids cluster are designed to validate the effectiveness of the proposed control method. Results show that the proposed hierarchical control scheme can ensure the independence and privacy of information, which is beneficial to solve technical and economic challenges brought by centralized optimization. In addition, the proposed algorithm can be applied to more realistic scenarios, such as conditions for time-varying loads and cost functions.

关键词： Hierarchical control DC microgrids cluster Alternating direction multiplier method Fast second-order distributed average consensus algorithm Voltage control without droop

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IHFBF: A High-Performance Blockchain Framework for Improving Hyperledger Fabric Permissioned Chain

IHFBF: A High-Performance Blockchain Framework for Improving...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Min Xu Xiaoding Wang Hui Lin College of Computer and Cyber Security Fujian Normal University Fuzhou China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Permissioned blockchain frameworks typically employ efficient Byzantine fault-tolerant consensus protocols, making them appealing for the deployment of fast transaction applications among a large number of mutually distrustful participants. However, existing permissioned blockchain frameworks typically use sequential serial workflows to invoke the consensus protocol and execute transactions for the application, resulting in significantly lower performance for these applications when deployed in traditional systems. Therefore, a new permissioned blockchain framework is needed to improve transaction processing efficiency and enhance system performance for practical blockchain technology applications. We propose IHFBF (Improved Hyperledger Fabric Blockchain Framework), an improved permissioned blockchain framework that employs a predictive transaction sorting method by selecting a node within the consensus nodes to act as a sorter. This enables parallel execution of the consensus protocol and transactions, resulting in improved overall system performance. However, if the sorter is a malicious node, it can severely impact system performance. To address this, IHFBF uses a view-change method based on a deny-list approach, which effectively guides all participants and replaces or denies malicious participants. Compared to other three fast permissioned blockchain frameworks, IHFBF’s parallel workflow framework reduces latency and exhibits better throughput in the presence of malicious participants, resulting in efficient system performance.

关键词： Fault tolerance Privacy distributed ledger System performance Fault tolerant systems Throughput Fabrics

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A Docker-Based Short Circuit parallel Calculation Strategy in Cloud Platform

A Docker-Based Short Circuit Parallel Calculation Strategy i...

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IEEE international conference on Artificial Intelligence and Information Systems (ICAIIS)

作者： Li, Bo Zhao, Ruifeng Liu, Yang Guo, Wenxin Lu, Jiangang Guangdong Grid Co Power Dispatching & Control Ctr Guangzhou Peoples R China

ISBN: (纸本)9781728165905

this paper proposed a short-circuit calculation parallelization strategy for power system analysis based on Docker technology to improve the efficiency and speed of calculation in cloud platform. This strategy mainly combines the advantage of the lightweight virtual application characteristics of Docker technology and parallel computing strategy to realize high efficiency short circuit calculation. The node matrix parallel decomposition algorithm is used for short-circuit parallel calculation. The Docker container is used to calculate every step of short-circuit parallel calculation and could dynamically be created and released according to the node size. Cloud platform simulation of short-circuit computing of different node sizes is carried out through Cloudsim. In the simulation, the computing time of serial algorithm, virtual machine parallel algorithm and container parallel algorithm was compared. The simulation results shows that the strategy can increasingly improve the efficiency and speed of short-circuit parallel calculation in cloud platform.

关键词： Docker cloud platform short-circuit calculation parallel calculation

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computing ENVIRONMENT for the SUPER-CHARM-TAU FACTORY DETECTOR PROJECT 9

COMPUTING ENVIRONMENT for the SUPER-CHARM-TAU FACTORY DETECT...

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9th international conference "distributed computing and grid Technologies in Science and Education", grid 2021

作者： Belozyorova, Maria Maksimov, Dmitry Razuvaev, Georgiy Sukharev, Andrey Vorobyev, Vitaly Zhadan, Anastasiia Zhadan, Daniil Budker Institute of Nuclear Physics 11 akademika Lavrentieva prospect Novosibirsk630090 Russia Novosibirsk State University 1 Pirogova street Novosibirsk630090 Russia

The project of the Super Charm-Tau (SCT) factory - a high-luminosity electron-positron collider for studying charmed hadrons and tau lepton - is proposed by Budker INP. The project implies single collision point equipped with a universal particle detector. The Aurora software framework has been developed for the SCT detector. It is based on trusted and widely used in high energy physics software packages, such as Gaudi, Geant4, and ROOT. At the same time, new ideas and developments are employed, in particular the Aurora project benefits a lot from the turnkey software for future colliders (Key4HEP) initiative. This paper describes the first release of the Aurora framework, summarizes its core technologies, structure and roadmap for the near future. From the hardware point of view the Budker INP general computing facility (BINP/GCF) providing the required computational and storage resources is described. © 2021 CEUR-WS. All rights reserved.

关键词： Computer programming

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LGDB-Net: Dual-Branch Path for Building Extraction from Remote Sensing Image

LGDB-Net: Dual-Branch Path for Building Extraction from Remo...

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international conference on parallel and distributed Systems (ICPADS)

作者： Ronghuan Zhang Jing Zhao Ming Li Qingzhi Zou Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China School of Intelligence and Information Engineering Shandong University of Traditional Chinese Medicine Jinan China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Extracting buildings from remote sensing images using deep learning techniques is a widely applied and crucial task. Convolutional Neural Networks (CNNs) adopt hierarchical feature representation, showcasing powerful capabilities in extracting local information but facing challenges in capturing global features. Transformers can address this limitation, but they perform poorly in extracting local features and significantly increase memory requirements and computational complexity. To overcome these challenges, we propose a method for building extraction from remote sensing images called LGDB-Net (Local-Global Dual-Branch Network), employing a dual-branch approach. Firstly, inspired by Swin Transformer, we designed GB-Former(Global Branch-Former) as the backbone network to model global information. We use a linear multi-head self-attention mechanism to reduce time and memory complexity while maintaining a large global receptive field. Additionally, we replace the traditional multi-layer perceptron with a convolution-enhanced multi-layer perceptron to improve channel feature representation, reduce model parameters, and enhance segmentation performance. Secondly, we use multiple Depth-wise Conv3×3 + LN (Layer Normalization) + GeLU (Gaussian Error Linear Unit) modules as the auxiliary branch for local detailed feature extraction. Finally, we adopt a multi-scale feature fusion strategy to integrate feature information from both branches. We conduct a series of experiments on three datasets: WHU, Massachusetts, and Inria. The experimental results demonstrate that the proposed method not only effectively improves segmentation accuracy with lower building omission and commission rates but also significantly reduces model parameters and computational complexity.

关键词： Accuracy Computational modeling Memory management Neural networks Feature extraction Transformers Sensors Data mining Computational complexity Remote sensing

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Accelerating cryo-EM Reconstruction of RELION on the New Sunway Supercomputer

Accelerating cryo-EM Reconstruction of RELION on the New Sun...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Jingle Xu Jiayu Fu Lin Gan Yaojian Chen Zhenchun Huang Guangwen Yang Department of Computer Science and Technology Tsinghua University China National Supercomputing Center in Wuxi China Zhejiang Lab China

Over the long journey of understanding the micro-world, cryo- EM has become an effective technique for biomolec-ular structure determinations. However, due to the complex algorithmic features and large amounts of computing data, so-phisticated HPC solutions are in urgent demand. In this paper, we present our efforts of porting RELION to the new generation of Sunway supercomputer. Optimizations that fit well with the new hardware architecture have been proposed, including a multi-level parallel scheme that smartly maps and scales RELION onto the novel Sun way architecture, optimizations that address memory bottlenecks and improve memory efficiency, and a pipeline approach that obtains excellent computation and communication overlapping. Combining all proposed optimizations, the calculation time for one iteration is greatly reduced from 7,577 seconds to 2,017 seconds, with a speedup of 3.757x. The overall design is scaled to over 131,072 cores with a parallel efficiency of 95 %.

关键词： Three-dimensional displays Scalability Memory management Pipelines parallel processing Supercomputers Biology

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