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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

共 34218 条记录，以下是4861-4870 订阅

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Renewable integration using IEC 61850 enabled smart distribution IEDs with customizable functions 15

Renewable integration using IEC 61850 enabled smart distribu...

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15th international conference on Developments in Power System Protection, DPSP 2020

作者： Venkataraman, Krishnakumar Kanabar, Mital Bhatia, Himanshu GE Grid Solutions Stafford United Kingdom GE Grid Solutions Markham Canada Grid Solutions Stafford United Kingdom

High penetration of renewable resources into traditional Medium Voltage (MV) or secondary distribution grid may impose severe challenges due to bidirectional power flow, low-inertia generation interconnections to weak grid, maintaining power quality, etc. In addition, secondary distribution grid would also require special attention due to aging of the existing infrastructure;lack of automation of existing grid assets;need for remotely managed devices;and regulated reliability indices to maintain grid supply. The grid operators are fonnulating guidelines for interconnection and operation of distributed generation in parallel to the Medium Voltage (MV) network. This requires specific capabilities in the Smart Distribution IEDs. To alleviate above challenges, without complete revamp of an existing distribution grid infrastructure, this paper proposes how the smart distribution Intelligent Electronic Devices (IEDs) can be applied to optimize the Capital Expenditure (CAPEX) for a distribution utility. © 2020 IET conference Publications.

关键词： Power quality

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Impact of CUDA and OpenCL on parallel and distributed computing

Impact of CUDA and OpenCL on Parallel and Distributed Comput...

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international Conf on Electrical and Electronic Engineering (ICEEE)

作者： Abu Asaduzzaman Alec Trent S. Osborne C. Aldershof Fadi N. Sibai Wichita State University Wichita Kansas USA Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia

ISBN: (纸本)9781665440714;9781665411615

Along with high performance computer systems, the Application Programming Interface (API) used is crucial to develop efficient solutions for modern parallel and distributed computing. Compute Unified Device Architecture (CUDA) and Open computing Language (OpenCL) are two popular APIs that allow General Purpose Graphics Processing Unit (GPGPU, GPU for short) to accelerate processing in applications where they are supported. This paper presents a comparative study of OpenCL and CUDA and their impact on parallel and distributed computing. Mandelbrot set (represents complex numbers) generation, Marching Squares algorithm (represents embarrassingly parallelism), and Bitonic Sorting algorithm (represents distributed computing) are implemented using OpenCL (version 2.x) and CUDA (version 9.x) and run on a Linux-based High Performance computing (HPC) system. The HPC system uses an Intel i7-9700k processor and an Nvidia GTX 1070 GPU card. Experimental results from 25 different tests using the Mandelbrot Set generation, the Marching Squares algorithm, and the Bitonic Sorting algorithm are analyzed. According to the experimental results, CUDA performs better than OpenCL (up to 7.34x speedup). However, in most cases, OpenCL performs at an acceptable rate (CUDA speedup is less than 2x).

关键词： Performance evaluation High performance computing Graphics processing units Computer architecture parallel processing Hardware Generators

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Proceedings - 2020 IEEE international conference on Cluster computing, CLUSTER 2020

Proceedings - 2020 IEEE International Conference on Cluster ...

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22nd IEEE international conference on Cluster computing, CLUSTER 2020

ISBN: (纸本)9781728166773

The proceedings contain 71 papers. The topics discussed include: implementing a comprehensive networks-on-chip generator with optimal configurations;ECS2: A fast erasure coding library for GPU-accelerated storage systems with parallel & direct IO;autoscaling high-throughput workloads on container orchestrators;Grade10: a framework for performance characterization of distributed graph processing;data life aware model updating strategy for stream-based online deep learning;energy optimization and analysis with EAR;parallel particle advection bake-off for scientific visualization workloads;HAN: a hierarchical AutotuNed collective communication framework;and evaluating worksharing tasks on distributed environments.

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17th international conference on Intelligent computing, ICIC 2021

17th International Conference on Intelligent Computing, ICIC...

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17th international conference on Intelligent computing, ICIC 2021

ISBN: (纸本)9783030845216

The proceedings contain 130 papers. The special focus in this conference is on Intelligent computing. The topics include: A Comparable Study on Dimensionality Reduction Methods for Endmember Extraction;Hyperspectral Image Classification with Locally Linear Embedding, 2D Spatial Filtering, and SVM;a Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting;Automatic Extraction of Document Information Based on OCR and Image Registration Technology;using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem;super-Large Medical Image Storage and Display Technology Based on Concentrated Points of Interest;person Re-identification Based on Hash;a Robust and Automatic Recognition Method of Pointer Instruments in Power System;partial Distillation of Deep Feature for Unsupervised Image Anomaly Detection and Segmentation;an Evolutionary Neuron Model with Dendritic Computation for Classification and Prediction;Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model;serialized Local Feature Representation Learning for Infrared-Visible Person Re-identification;a Novel Decision Mechanism for Image Edge Detection;Rapid Earthquake Assessment from Satellite Imagery Using RPN and Yolo v3;attention-Based Deep Multi-scale Network for Plant Leaf Recognition;short Video Users’ Personal Privacy Leakage and Protection Measures;An Efficient Video Steganography Method Based on HEVC;analysis on the Application of Blockchain Technology in Ideological and Political Education in Universities;parallel Security Video Streaming in Cloud Server Environment;An Efficient Video Steganography Scheme for Data Protection in H.265/HEVC;an Improved Genetic Algorithm for distributed Job Shop Scheduling Problem;A Robust Lossless Steganography Method Based on H.264/AVC;detection of Pointing Position by Omnidirectional Camera.

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Setup of a local P2P electric energy market based on a smart contract blockchain technology 21

Setup of a local P2P electric energy market based on a smart...

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21st international Scientific conference on Electric Power Engineering (EPE)

作者： Perekalskiy, Igor Kokin, Sergey Kupcov, Dmitriy Ural Fed Univ Ekaterinburg Russia

ISBN: (数字)9781728194790

ISBN: (纸本)9781728194790

in an era of the widespread introduction of information technology, the broadest possibilities are opening up for the implementation of additional services for prosumers in the electricity market. The traditional electric power system of Russia allows customers to receive electricity only from large power plants, which leads to centralization and monopoly. Currently, the concept of distributed generation is gaining popularity. The idea is that small electric power generators are distributed throughout the local power network. The introduction of such an electrical network will improve the reliability of the system. However, such a network needs effective management and an electricity metering system. This paper proposes the use of distributed network blockchain technology as a solution to these problems. The proposed double-chain blockchain model will provide for the electric energy trading within the local electricity market, without third-party intermediaries, with a sufficient level of security and automation for all participants.

关键词： blockchain smart grid distributed computing energy internet distributed ledger

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MPS: A Multiple Poisoned Samples Selection Strategy in Backdoor Attack

MPS: A Multiple Poisoned Samples Selection Strategy in Backd...

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

作者： Weihong Zou Shigeng Zhang Weiping Wang Jian Zhang Xuan Liu Schoosl of Computer Science and Engineering Central South University Science and Technology on Parallel and Distributed Processing Laboratory (PDL) College of Computer Science and Electronic Engineering Hunan University

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Recently there has been many studies on backdoor attacks, which involve injecting poisoned samples into the training set in order to embed backdoors into the model. Existing multiple poisoned samples attacks usually randomly select a subset from clean samples to generate the poisoned samples. Filtering-and-Updating Strategy (FUS) has shown that the poisoning efficiency of each poisoned sample is inconsistent and random selection is not optimal. However, FUS does not fully considered the selection of multiple poisoned samples, there are still some issues with the selection of multiple poisoned samples. In this paper, we formulate the selection of multiple types of poisoned samples as a multi-objective optimization problem and proposed a Multiple Poisoned Samples Selection Strategy (MPS) to solve the issue. Unlike FUS, we consider the potential of clean samples that are not selected as to become efficient poisoned samples. Specifically, we use a weight-based contribution approach to calculate the contribution of each sample (clean sample and poisoned sample) during the training process from multiple dimensions. Finally, based on the greedy approach, we retain a subset of samples with the largest contribution in each dimension through iterations. We evaluate the effectiveness of MPS on various attack methods, including BadNet, Blended, ISSBA, and WaNet, as well as benchmark datasets. The experimental results on CIFAR-10 and GTSRB show that MPS can increase the attack strength by 1.45% to 18.34% compared to RSS and 0.43% to 10.84% compared to FUS in multiple poisoned samples attacks, thereby enhancing the stealthiness of the attack. Meanwhile, MPS is suitable for black-box settings, meaning that poisoned samples selected in one setting can be applied to other settings.

关键词： Training Data privacy Closed box Benchmark testing Security Protection Optimization

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LVQ: A Lightweight Verifiable Query Approach for Transaction History in Bitcoin 40

LVQ: A Lightweight Verifiable Query Approach for Transaction...

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40th IEEE international conference on distributed computing Systems (ICDCS)

作者： Dai, Xiaohai Xiao, Jiang Yang, Wenhui Wang, Chaofan Chang, Jian Han, Rui Jin, Hai Huazhong Univ Sci & Technol Sch Comp Sci & Technol Cluster & Grid Comp Lab Serv Comp Technol & Syst LabNatl Engn Res Ctr Bi Wuhan 430074 Peoples R China

ISBN: (纸本)9781728170022

In the Bitcoin system, transaction history of an address can be useful in many scenarios, such as the balance calculation and behavior analysis. However, it is non-trivial for a common user who runs a light node to fetch historical transactions, since it only stores headers without any transaction details. It usually has to request a full node who stores the complete data. Validation of these query results is critical and mainly involves two aspects: correctness and completeness. The former can be implemented via Merkle branch easily, while the latter is quite difficult in the Bitcoin protocol. To enable the completeness validation, a strawman design is proposed, which simply includes the BF (Bloom filter) in the headers. However, since the size of BF is about KB, light nodes in the strawman will suffer from the incremental storage burden. What's worse, an integrated block must be transmitted when BF cannot work, resulting in large network overhead. In this paper, we propose LVQ, the first lightweight verifiable query approach that reduces the storage requirement and network overhead at the same time. To be specific, by only storing the hash of BF in headers, LVQ keeps data stored by light nodes being little. Besides, LVQ introduces a novel BMT (BF integrated Merkle Tree) structure for lightweight query, which can eliminate the communication costs of query results by merging the multiple successive BFs. Furthermore, when BF cannot work, a lightweight proof by SMT (Sorted Merkle Tree) is exploited to further reduce the network overhead. The security analysis confirms LVQ's ability to enable both correctness and completeness validation. In addition, the experimental results demonstrate its lightweight.

关键词： Bitcoin verifiable query transaction history Merkle tree Bloom filter

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Control Strategy of MMC-Based Flexible DC Transmission System in Cloud computing Environment

Control Strategy of MMC-Based Flexible DC Transmission Syste...

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Lexin Yang Rongbin Yao Lianyungang Normal College Lianyungang Jiangsu China China university of mining and technology Xuzhou Jiangsu China Lianyungang Normal College LianyungangJiangsuChina222006

ISBN: (纸本)9781665435253

Compared with the traditional two-level or h-level voltage source converter, modular multilevel converter has many incomparable advantages, such as long-distance high-capacity transmission, asynchronous grid interconnection, distributed generation connected to the grid, wind power generation connected to the grid, passive Island, drilling platform and so on There are broad application prospects in many fields, such as power supply in partial suitable areas, capacity expansion and reconstruction of urban power grid, etc. This paper studies the control strategy of flexible HVDC system based on MMC in cloud computing environment.

关键词： Drilling Cloud computing Multilevel converters Power supplies HVDC transmission Wind power generation Power grids

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Secure deduplication method based on tag clustering

Secure deduplication method based on tag clustering

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

作者： Fengkun Gao Chunbo Wang Xiaoqiang Di Jinhui Cao Xu Liu Hui Qi Jilin Key Laboratory of Network and Information Security Changchun University of Science and Technology Changchun China School of Computer Science and Technology Changchun University of Science and Technology Changchun China School of Information Technology Changchun Automobile Industry Institute Changchun China

Although cloud storage technology can provide users with convenient storage services, a large amount of duplicate data in the cloud brings a huge storage burden and the risk of privacy leakage. To improve the utilization of cloud storage resources and protect data confidentiality, random message lock encryption technology (R-MLE) can be used to delete redundant data in the cloud. But the theoretical basis of the deduplication scheme based on R-MLE is bilinear mapping, so the computational cost of finding duplicate fingerprint-tags is relatively large. To improve the deduplication efficiency, we proposed a secure deduplication scheme based on the autoencoder model in our previous research, using the model to generate the abstract-tags of the data, and using the similarity of the abstract-tags to quickly filter out the fingerprint-tags with high repeatability, which greatly reduces the number of fingerprint-tag comparisons. On this basis, this paper further proposes a secure deduplication method based on k-means clustering. First, the abstract-tags in cloud storage are clustered, and then the distance between the abstract-tags uploaded by users and the centroid is calculated. Then, the abstract-tags of the category with the closest distance are selected. Finally, duplicate data detection is performed only on the fingerprint-tags corresponding to these abstract-tags. In this way, the filtering speed of fingerprint-tags can be further accelerated. Experiments show that our method has higher performance than the secure deduplication method based on the autoencoder model.

关键词： Cloud computing Data privacy Filtering Computational modeling Fingerprint recognition Data models Computational efficiency

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E2Clab: Exploring the computing Continuum through Repeatable, Replicable and Reproducible Edge-to-Cloud Experiments 22

E2Clab: Exploring the Computing Continuum through Repeatable...

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IEEE international conference on Cluster computing

作者： Rosendo, Daniel Silva, Pedro Simonin, Matthieu Costan, Alexandru Antoniu, Gabriel Univ Rennes IRISA CNRS INRIA Rennes France Univ Potsdam Hasso Plattner Inst Berlin Germany

ISBN: (数字)9781728166773

ISBN: (纸本)9781728166773

distributed digital infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex applications to be executed from IoT Edge devices to the HPC Cloud (aka the computing Continuum, the Digital Continuum, or the Transcontinuum). Understanding end-to-end performance in such a complex continuum is challenging. This breaks down to reconciling many, typically contradicting application requirements and constraints with low-level infrastructure design choices. One important challenge is to accurately reproduce relevant behaviors of a given application workflow and representative settings of the physical infrastructure underlying this complex continuum. In this paper we introduce a rigorous methodology for such a process and validate it through E2Clab. It is the first platform to support the complete analysis cycle of an application on the computing Continuum: (i) the configuration of the experimental environment, libraries and frameworks;(ii) the mapping between the application parts and machines on the Edge, Fog and Cloud;(iii) the deployment of the application on the infrastructure;(iv) the automated execution;and (v) the gathering of experiment metrics. We illustrate its usage with a real-life application deployed on the grid'5000 testbed, showing that our framework allows one to understand and improve performance, by correlating it to the parameter settings, the resource usage and the specifics of the underlying infrastructure.

关键词： Reproducibility Methodology computing Continuum Edge Intelligence

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