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

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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...

引用

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

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

引用

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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Secure deduplication method based on tag clustering

Secure deduplication method based on tag clustering

引用

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...

引用

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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Managing Failures in Task-Based parallel Workflows in distributed computing Environments 26th

Managing Failures in Task-Based Parallel Workflows in Distri...

引用

26th international conference on parallel and distributed computing (Euro-Par)

作者： Ejarque, Jorge Bertran, Marta Cid-Fuentes, Javier Alvarez Conejero, Javier Badia, Rosa M. Barcelona Supercomp Ctr Barcelona Spain

ISBN: (纸本)9783030576752;9783030576745

Current scientific workflows are large and complex. They normally perform thousands of simulations whose results combined with searching and data analytics algorithms, in order to infer new knowledge, generate a very large amount of data. To this end, workflows comprise many tasks and some of them may fail. Most of the work done about failure management in workflow managers and runtimes focuses on recovering from failures caused by resources (retrying or resubmitting the failed computation in other resources, etc.) However, some of these failures can be caused by the application itself (corrupted data, algorithms which are not converging for certain conditions, etc.), and these fault tolerance mechanisms are not sufficient to perform a successful workflow execution. In these cases, developers have to add some code in their applications to prevent and manage the possible failures. In this paper, we propose a simple interface and a set of transparent runtime mechanisms to simplify how scientists deal with application-based failures in task-based parallel workflows. We have validated our proposal with use-cases from e-science and machine learning to show the benefits of the proposed interface and mechanisms in terms of programming productivity and performance.

关键词： Failure management Scientific workflows parallel programming distributed computing

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Online Reasoning about the Root Causes of Software Rollout Failures in the Smart grid

Online Reasoning about the Root Causes of Software Rollout F...

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2020 international conference on Communications Control and computing Technologies for Smart grids

作者： Piatkowska, Ewa Gavriluta, Catalin Smith, Paul Andren, Filip Prostl AIT Austrian Inst Technol Vienna Austria

ISBN: (纸本)9781728161273

An essential ingredient of the smart grid is software-based services. Increasingly, software is used to support control strategies and services that are critical to the grid's operation. Therefore, its correct operation is essential. For various reasons, software and its configuration needs to be updated. This update process represents a significant overhead for smart grid operators and failures can result in financial losses and grid instabilities. In this paper, we present a framework for determining the root causes of software rollout failures in the smart grid. It uses distributed sensors that indicate potential issues, such as anomalous grid states and cyber-attacks, and a causal inference engine based on a formalism called evidential networks. The aim of the framework is to support an adaptive approach to software rollouts, ensuring that a campaign completes in a timely and secure manner. The framework is evaluated for a software rollout use-case in a low voltage distribution grid. Experimental results indicate it can successfully discriminate between different root causes of failure, supporting an adaptive rollout strategy.

关键词： Security and Privacy Protection Fault tolerance Software and System Safety Software release management and delivery

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Single Node Acceleration of Generative Adversarial Networks using HPC for Image Analytics 22

Single Node Acceleration of Generative Adversarial Networks ...

引用

Proceedings of the 2022 5th international conference on Computational Intelligence and Intelligent Systems

作者： Aswathy Ravikumar Harini Sriraman School of Computer Science and Engineering Vellore Institute of Technology India

ISBN: (纸本)9781450397612

Generative Adversarial Networks (GAN) are approaches that are utilized for data augmentation, which facilitates the development of more accurate detection models for unusual or unbalanced datasets. Computer-assisted diagnostic methods may be made more reliable by using synthetic pictures generated by GAN. Generative adversarial networks are challenging to train because too unpredictable training dynamics may occur throughout the learning process, such as model collapse and vanishing gradients. For accurate and faster results the GAN network need to trained in parallel and distributed manner. We enhance the speed and precision of the Deep Convolutional Generative Adversarial Networks (DCGAN) architecture by using its parallelism and executing it on High-Performance computing platforms. The effective analysis of a DCGAN in Graphic Processing Unit and Tensor Processing Unit platforms in which each layer execution pattern is analyzed. The bottleneck is identified for the GAN structure for each execution platforms. The Central Processing Unit is capable of processing neural network models, but it requires a great deal of time to do it. Graphic Processing Unit in contrast, side, are a hundred times quicker than CPUs for Neural Networks, however, they are prohibitively expensive compared to CPUs. Using the systolic array structure, TPU performs well on neural networks with high batch sizes but in GAN the shift between CPU and TPU is huge so it does not perform well.

关键词： Generative Adversarial Network High-Performance computing Graphic Processing Unit Tensor Processing Unit

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Proceedings - 2020 28th Euromicro international conference on parallel, distributed and Network-Based Processing, PDP 2020

Proceedings - 2020 28th Euromicro International Conference o...

引用

28th Euromicro international conference on parallel, distributed and Network-Based Processing, PDP 2020

ISBN: (纸本)9781728165820

The proceedings contain 67 papers. The topics discussed include: windsurfing with APPA: automating computational fluid dynamics simulations of wind flow using cloud computing;parallel comparison of huge DNA sequences in multiple GPUs with block pruning;accelerating deep learning using multiple GPUs and FPGA-based 10GbE switch;adaptive load balancing based on machine learning for iterative parallel applications;switching at flit level: a congestion efficient flow control strategy for network-on-chip;robustness and energy-elasticity of crown schedules for sets of parallelizable tasks on many-core systems with DVFS;and scalable parallel genetic algorithm for solving large integer linear programming models derived from behavioral synthesis.

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Comparison of Passive Damping based LCL Filter Design Methods for grid-connected Voltage Source Converters 3

Comparison of Passive Damping based LCL Filter Design Method...

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3rd IEEE international conference on Power, Instrumentation, Control and computing, PICC 2020

作者： Naresh, P. Anirudh, C.V.S. Kumar, V. Seshadri Sravan Indian Institute of Technology Department of Electrical Engineering Hyderabad India

ISBN: (纸本)9781728175904

distributed generators are typically interfaced to the grid via power electronic converters that are usually operated in pulse width modulation mode. This results in undesirable higher-order harmonics in currents and voltages that deteriorate the power quality. In order to mitigate these harmonics, a filter is usually connected at the output of the converter before it is interfaced to the grid. The most commonly adopted filter is the LCL filter. This paper analyses the performance of different methods proposed in the literature to design passive LCL filters for a 3- f grid-connected voltage source converter. Various filter design techniques are tested for their compliance with the standards IEEE 519-2014 and IEEE 1547-2018. Further, comparison is carried out in terms of essential system metrics such as reactive power requirement, power factor, and the voltage drop across the filter. The performance of various filter design approaches is analyzed using simulation studies on different distributed generator configurations. © 2020 IEEE.

关键词： Natural frequencies

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A Context Model for Holistic Monitoring and Management of Complex IT Environments 18

A Context Model for Holistic Monitoring and Management of Co...

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IEEE international conference on Pervasive computing and Communications (PerCom)

作者： Mormul, Mathias Stach, Christoph Univ Stuttgart Inst Parallel & Distributed Syst Univ Str 38 D-70569 Stuttgart Germany

ISBN: (纸本)9781728147161

The increased usage of IoT, containerization, and multiple clouds not only changed the way IT works but also the way IT Operations, i.e., the monitoring and management of IT assets, works. Monitoring a complex IT environment leads to massive amounts of heterogeneous context data, usually spread across multiple data silos, which needs to be analyzed and acted upon autonomously. However, for a holistic overview of the IT environment, context data needs to be consolidated which leads to several problems. For scalable and automated processes, it is essential to know what context is required for a given monitored resource, where the context data are originating from, and how to access them across the data silos. Therefore, we introduce the Monitoring Resource Model for the holistic management of context data. We show what context is essential for the management of monitored resources and how it can be used for context reasoning. Furthermore, we propose a multi-layered framework for IT Operations with which we present the benefits of the Monitoring Resource Model.

关键词： context model IT Operations AIOps Monitoring

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