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

共 34256 条记录，以下是4301-4310 订阅

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Optimization of emergency load shedding employing social learning-based PSO

Optimization of emergency load shedding employing social lea...

引用

2021 international conference on Computer Engineering and Artificial Intelligence, ICCEAI 2021

作者： Xie, Yongsheng Feng, Changyou Gai, Chenhao Li, Changgang State Grid Xinjiang Electric Power Corporation Xinjiang Urumqi China State Grid Corporation of China Beijing China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education China Shandong Jinan China

ISBN: (纸本)9781665439602

Emergency load shedding (ELS) is an essential measure to prevent power system accidents from expanding. Economy and security need to be optimized comprehensively for ELS. In this paper, an ELS optimization model is established, which takes the minimum load shedding amount as the objective function and the transient angle security, transient voltage deviation acceptability, transient frequency deviation acceptability, maximum controllable load as constraints. The social learning-based particle swarm optimization (SL-PSO) algorithm is proposed to solve the ELS optimization problem, which adopts adaptive parameters. The portable and open-source power system dynamic simulation toolkit (STEPS) is used for numerical simulation to check the feasibility of the solution. Finally, the efficiency of the solution is improved by parallel computing. The proposed model and algorithm are validated with the IEEE 39 bus test system. © 2021 IEEE.

关键词： Particle swarm optimization (PSO)

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SPEAR: Dynamic Spatio-Temporal Query Processing over High Velocity Data Streams 37

SPEAR: Dynamic Spatio-Temporal Query Processing over High Ve...

引用

37th IEEE international conference on Data Engineering (IEEE ICDE)

作者： Baig, Furqan Teng, Dejun Kong, Jun Wang, Fusheng SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA SUNY Stony Brook Dept Biomed Informat Stony Brook NY 11794 USA Georgia State Univ Dept Comp Sci Dept Math & Stat Atlanta GA 30303 USA

ISBN: (纸本)9781728191843

With the advent of IoT and emerging 5G technology, real-time streaming data are being generated at unprecedented speed and volume having both temporal and spatial dimensions. Effective analysis at such scale and speed require support for dynamically adjusting querying capabilities in real-time. In the spatio-temporal domain, this warrants data as well as query optimization strategies especially for objects with changing motion states. Contemporary spatio-temporal data stream management systems in the distributed domain are mostly dominated by specify-once-apply-continuously query model. Any modification in query state requires query restart limiting system responsiveness and producing outdated or in worst case erroneous results. In this paper, we propose adaptations of principles from streaming databases, spatial data management, and distributed computing to support dynamic spatio-temporal query processing over high-velocity big data streams. We first formulate a set of spatio-temporal data types and functions to seamlessly handle changes in distributed query states. We develop a comprehensive set of streaming spatio-temporal querying methods and propose geohash based dynamic spatial partitioning for effective parallel processing. We implement a prototype on top of Apache Flink, where the in-memory stream processing fits nicely with our spatio-temporal models. Comparative evaluation of our prototype demonstrates the effectiveness of our strategy by maintaining high consistent processing rates for both stationary as well as moving queries over high velocity spatio-temporal big data streams.

关键词： spatio-temporal stream-processing spatiotemporal-stream real-time-spatio-temporal spatial-stream distributed-stream

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Performance Evaluation of distributed Machine Learning for Load Forecasting in Smart grids 30

Performance Evaluation of Distributed Machine Learning for L...

引用

30th international conference on Cybernetics and Informatics (K and I)

作者： Syed, Dabeeruddin Refaat, Shady S. Abu-Rub, Haitham Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Texas A&M Univ Qatar Doha Qatar

ISBN: (纸本)9781728143811

Load forecasting in smart grid is the process of predicting the amount of electrical power to meet the short, medium and long term demands. Accurate load forecasting helps electrical utilities to manage their energy production, operations, control and management. Most of the state-of-the-art forecasting methodologies utilize classical machine learning algorithms to predict the electrical load. There is a need that big data platforms and parallel distributed computing are utilized to their potential in the available solutions. In this paper, the Apache Spark and Apache Hadoop are utilized as big data platforms for distributed computing in order to predict the load using available big data. In this paper, MLib, Spark library for machine learning algorithms, is utilized for distributed computing. Using MLib allows testing the classic regression algorithms such as linear regression, generalized linear regression, decision tree, random forest and gradient-boosted trees in addition to survival regression and isotonic regression. The obtained results show that Spark produces high accuracy while parallelizing the process of load forecasting in highly competent training and test times. Actual big data are used in the load forecasting process.

关键词： Apache Spark Load Forecast distributed Machine Learning Smart grids distributed computing

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Performance and Portability Analysis of OPS Structured grid parallel Library 3

Performance and Portability Analysis of OPS Structured Grid ...

引用

3rd IEEE international conference on Frontiers Technology of Information and Computer, ICFTIC 2021

作者： Chen, Fengting Che, Yonggang Wang, Wenke Ma, Jian National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology Changsha410073 China National University of Defense Technology Changsha410073 China National University of Defense Technology School of Military Basic Education Changsha410073 China

ISBN: (纸本)9781665406055

The complexity and diversity of high-performance computer architectures have brought great challenges to parallel application development. Using DSL (Domain Specific Language) to achieve multi-platform automatic parallelization is a solution to this problem. This paper tests and analyzes the multi-platform parallel performance of OPS (Oxford parallel Library for Structured Mesh Solvers), a typical DSL framework for scientific applications. Two representative structured mesh applications are used in our evaluation. The performance of their MPI, hybrid MPI/OpenMP and CUDA versions generated by OPS are evaluated on the Intel Xeon E5-2600 V3 CPU and the NVIDIA Tesla K80 GPU. The performance of OPS generated codes are compared against the corresponding manually parallelized and optimized codes. The results show that for the two applications, OPS based approach can generate parallel codes with comparable performance to manually parallelized and optimized codes. This paper further analyzes the differences between OPS-based multi-platform parallel code generation and manual parallelization approaches and their impact on performance. It also quantitatively evaluates the cross-platform portability of OPS, and points out some possible directions of improvement. © 2021 IEEE.

关键词： parallel programming

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Joint Service Placement and Request Scheduling for Multi-SP Mobile Edge computing Network 26

Joint Service Placement and Request Scheduling for Multi-SP ...

引用

26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Lei, Zhengwei Xu, Hongli Huang, Liusheng Meng, Zeyu Univ Sci & Technol China Dept Comp Sci & Technol Hefei Peoples R China

ISBN: (纸本)9781728190747

Mobile edge computing(MEC), as an emerging computing paradigm, pushes services away from centralized remote cloud to distributed edge servers deployed by multiple service providers(SPs), improving user experience and reducing the communication burden on core network. However, this distributed computing architecture also brings some new challenges to the network. In multi-SP MEC system, a SP prefers to use edge servers deployed by itself instead of others, which not only improves service quality but also reduces processing cost. The service placement and request scheduling strategies directly affect the revenue of SPs. Since the service popularity changes over time and the resources of edge servers are limited, the network system needs to make decisions about service placement and request scheduling dynamically to provide better service for users. Owing to the lack of long-term prior knowledge and involving binary decision variables, how to place services and schedule requests to boost the profit of SPs is a challenging problem. We formally formalize this joint optimization problem and propose an efficient online algorithm. First, we invoke Lyapunov optimization technology to convert the long-term optimization problem into a series of subproblems, then a dual-decomposition algorithm is utilized to solve the subproblem. Experimental results show that the algorithm proposed in this paper achieves nearly optimal performance, and it raises 25% and 70% profit compared to greedy and Top-K algorithms, respectively.

关键词： Service Placement Request Scheduling Profit Maximization Lyapunov Optimization

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SOLVING the PROBLEMS of BYZANTINE GENERALS USING BLOCKCHAIN TECHNOLOGY 9

SOLVING the PROBLEMS of BYZANTINE GENERALS USING BLOCKCHAIN ...

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

作者： Bogdanov, Alexander Degtyarev, Alexander Shchegoleva, Nadezhda Korkhov, Vladimir Zaynalov, Nodir Kiyamov, Jasur Dik, Aleksandr Faradzhov, Anar Saint Petersburg State University 7-9 Universitetskaya emb. Saint Petersburg199034 Russia Samarkand Branch Tashkent University of Information Technology Uzbekistan Plekhanov Russian University of Economics 36 Stremyanny lane Moscow117997 Russia

The process of digitalization of the Russian economy as the basis for the transition to the digital economy is conditioned by the requirements of objective reality and is based, first of all, on the introduction of digital technologies into the activities of its actors. The most promising is the Blockchain technology, which has the capabilities of the most effective coordination of the economic interests of the actors of the digital economy and is applicable in various spheres of economic activity. The article discusses the basics of cryptocurrencies and blockchain operation, as well as the technologies in which this "Tasks of Byzantine generals" (decision-making tasks) occurs. A comparison is made for solution of the problem with different blockchain technologies with several platforms that prevent behavior dangerous for transactions network and thereby increasing the competitiveness of the cryptocurrency. © 2021 CEUR-WS. All rights reserved.

关键词： distributed ledger

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Improving the Stability of Smart grids by Using Flexible AlternatingCurrent Transmission Systems (FACTS) 12

Improving the Stability of Smart Grids by Using Flexible Alt...

引用

12th international Renewable Engineering conference (IREC)

作者： Alnasseir, Jamal Alcharea, Raed Almaghout, Fadi Damascus Univ Fac Mech & Elect Engn Dept Elect Power Syst Damascus Syria Minist Elect Syria Damascus Syria

ISBN: (纸本)9781665425483

With the increase of using distributed generation sources in electrical networks, it is necessary to convert the traditional electrical networks into smart networks, which is capable supplying the electric energy reliably and safely. Flexible Alternative Current Transmission Systems (FACTS) is a feasible solution, which will be used, to improve the stability and performance of these networks. This article discusses the effect of interconnecting parallel (STATCOM (Static Synchronous Compensator) and series TCSC (Thyristor-Controlled Series Capacitor) FACTs systems in enhancing the stability of new electrical network. Whereas, one of the traditional generators has been replaced by a wind farm based on the double feed induction generator (DFIG). The simulation results show that connecting FACTS controllers improves the stability of the new electrical networks with the presence of a wind farm, and helps to dampen the undesired vibrations of the network parameters electrical (cornering of the rotor-angle and node-voltages). The results showed that the TCSC was more effective than the STATCOM parallel compensator in improving the critical clearing time of the studied network and the node voltages when a balanced three-phase failure occurs. The study was carried out on modified IEEE-14 nodes using the MATLAB software (Power System Analysis Toolbox), which is specialized program in studying electrical networks.

关键词： Smart grid Flexible Alternative Current Transmission Systems (FACTS) system stability

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A Multi-cloud parallel Selection Approach for Unlinked Microservice Mapped to Budget's Quota: The PUM²Q 1

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10th international conference on Cloud computing and Services Science (CLOSER)

作者： Carvalho, Juliana Trinta, Fernando Vieira, Dario Univ Fed Piaui UFPI Picos Brazil Univ Fed Ceara UFC Fortaleza Ceara Brazil EFREI Paris Paris France

ISBN: (数字)9783030723699

ISBN: (纸本)9783030723682;9783030723699

The world is facing a complicated moment in which social isolation is necessary. Therefore, to minimize the problems of companies, remote work is being widely adopted, which is only possible because of existing technologies, including cloud computing. Choosing the providers to host the business applications is a complex task, as there are many providers and most of them offer various services with the same functionality and different capabilities. Thus, in this paper, we propose an approach, called PUM(2)Q, for selecting providers to host a distributed application based on microservices that have little communication between them. PUM(2)Q is a provider selection approach based on multi-criteria, and it copes with the needs of microservices individually and in parallel. The proposed approach extends our previous one, UM(2)Q, and should be incorporated by PacificClouds. Besides, we carry out a performance evaluation by varying the number of requirements, microservices, and providers. We also compare PUM(2)Q and UM(2)Q. The results presented by PUM(2)Q are better than those given by UM(2)Q, showing not only its viability but also expanding the number of approaches adopted by PacificClouds. As a result, PUM(2)Q making the tasks of the software architect, who is the user of PacificClouds, more flexible.

关键词： Multi-criteria decision-making method Microservices Multi-cloud parallel selection

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Optimal Smart grid Operation and Control Enhancement by Edge computing

Optimal Smart Grid Operation and Control Enhancement by Edge...

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

作者： Liao, Yuan He, Jiangbiao Univ Kentucky Dept Elect & Comp Engn Lexington KY 40506 USA

ISBN: (纸本)9781728161273

The national electric power grid is being transformed into a smart grid through deploying a huge number of distributed sensors across the network, a two-way communication system, intelligent control and optimization algorithms, and advanced hardware components. An increasing volume of data are collected by the sensing system, and transfer of these data to a central location for centralized processing poses burden to the communication system and the central computing system. Edge computing, a distributed computing paradigm, processes data and makes proper decisions locally, stores data locally and provides selected, processed data to a higher level, and thus may significantly relieve communication burden and reduce response time of certain control applications. This paper explores possible applications of edge computing to enhance distributed optimization and control of smart grid, including power system asset management, distributed charging scheme and microgrid protection.

关键词： Smart power grids

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Secure and Verifiable Data Access Control Scheme With Policy Update and Computation Outsourcing for Edge computing 26

Secure and Verifiable Data Access Control Scheme With Policy...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Guan, Yue Guo, Songtao Li, Pan Yang, Yuanyuan Southwest Univ Sch Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China SUNY Stony Brook Sch Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (纸本)9781728190747

Edge computing means that computing tasks are executed on edge devices closer to the data source. It can effectively improve system response speed and reduce the risk of user data leakage. However, current data access control schemes usually focus on cloud computing and rarely on edge computing. Although attribute-based encryption (ABE) scheme can realize flexible and reliable access control, computing cost is too high with the increase of access policy complexity. Therefore, combining computation outsourcing technology with dynamic policy updating technology, we propose a data, access control scheme based on ciphertext-policy ABE (CP-ABE) for edge computing. We outsource part of storage service and part of decryption computing to edge nodes, effectively reducing the computing pressure of users. When data owner requires a new access policy, policy update key is generated timely and transmitted to cloud service provider, which is used to update the access policy, reducing the risk of bandwidth consumption and leakage of the ciphertext back and forth transmission. Finally, security analysis and experiment results verify the safety and effectiveness of our scheme.

关键词： Edge computing CP-ABE dynamic policy update outsourced decryption

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