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检索条件"任意字段=8th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1804 条记录，以下是601-610 订阅

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Multi-loop Control Strategy for parallel distributed Generation Units in Standalone applications 8

Multi-loop Control Strategy for Parallel Distributed Generat...

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8th international conference on Modelling, Identification and Control (ICMIC)

作者： Saim, Abdelhakim Mellah, Rabah Houari, Azeddine Djerioui, Ali Machmoum, Mohamed Univ Mouloud Mammeri Tizi Ouzou Fac Elect & Comp Engn Tizi Ouzou 15000 Algeria Univ Nantes IREENA Lab F-44602 St Nazaire France

ISBN: (纸本)9780956715777

this paper presents a suitable output voltage control approach for parallel distributed generation (DG) units working in standalone operating mode. Indeed, an Adaptive Multi Resonant controller with weighted State Feedbacks is optimally designed for the voltage control loop while a Proportional regulator is proposed for the inner current loop. thankful to its frequency adjusting ability, the proposed multi loop controller is also expanded to a wireless power sharing controlled parallel inverters. A co-simulation is carried out combining Matlab/Simulink and PSIM environments in order to highlight the effectiveness of the global control structure which ensures high tracking performance with reduced rate of harmonic distortion, deals efficiently with any load disturbances and may face large frequency deviation while an accurate power sharing is maintained among the parallel DG units.

关键词： distributed generation standalone microgrid multi-loop control droop control resonant control

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Agent-Based Cloud computing Systems for Traffic Management 8

Agent-Based Cloud Computing Systems for Traffic Management

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8th international conference on Intelligent Networking and Collaborative Systems (INCoS)

作者： Vascak, Jan Hvizdos, Jakub Puheim, Michal Tech Univ Kosice Fac Elect Engn & Informat Dept Cybernet & Artificial Intelligence Kosice Slovakia

ISBN: (纸本)9781509041237

the need for a safe and economically efficient traffic represents a challenge for creating traffic management systems. this paper deals with merging three basic concepts, namely cloud-based technologies, agent-based approaches and fuzzy cognitive maps to solve the localisation and path planing for several vehicles of different types in the form of independent agents, which communicate with a supervisory system located on the cloud. the proposed system was directly tested on a playground and obtained results were analysed using several selected criteria. Finally, some further possibilities of potential utilization and future research are mentioned.

关键词： distributed computer systems

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Track Chair's Report: Convergence of distributed Clouds, Grids and their Management CDCGM 2016 25

Track Chair's Report: Convergence of Distributed Clouds, Gri...

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25th IEEE international conference on Enabling technologies - Infrastructure for Collaborative Enterprises (WETICE)

作者： Messina, Fabrizio Mikkilineni, Rao Morana, Giovanni Univ Catania Dept Math & Informat Vle Andrea Doria 6 I-95125 Catania Italy C3DNA Inc Santa Clara CA USA C3DNA Inc R&D & Engn Catania Italy

ISBN: (纸本)9781509016631

this track has made significant contribution to advance the current state of the art in enterprise distributed application management across datacenters, and clouds public or private. the scale of distributed applications and their management have taken a new dimension demanding tolerance to wild fluctuations both in workloads and available computing resource pools. A new computing model proposing extensions to the current von Neumann implementation of the Turing machine was contributed by the efforts of participating in this conference since 2009. the result is a practical demonstration of these concepts, showing infrastructure agnostic auto-failover, auto-scaling and live-migration of even state-sensitive distributed applications. By eliminating virtual image motion which is the current state of the art, this approach improves efficiency and reduces complexity and tool fatigue prevalent in todays enterprises. In addition, a review of the super recursive algorithms and inductive Turing machines in this track provides the theoretical foundation for new computing. In addition, there are five full papers describing advances in current distributed and cloud computing practices dealing with quality of service, adaptive algorithms and software defined network architectures. One short paper discusses a new approach for resource allocation in distributed systems. On the eve of the 25th anniversary of WETICE, this track attests to its success where the work started here has contributed to both theoretical and practical application going from ideation to application within a span of 6 years.

关键词： Cloud computing grid computing distributed Intelligent Managed Element Networks distributed Services Management Services Virtualization parallel computing

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Online credit card fraud detection: A hybrid framework with big data technologies 15

Online credit card fraud detection: A hybrid framework with ...

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Joint 15th IEEE international conference on Trust, Security and Privacy in computing and Communications, 10th IEEE international conference on Big Data Science and Engineering and 14th IEEE international Symposium on parallel and distributed Processing with applications, IEEE TrustCom/BigDataSE/ISPA 2016

作者： Dai, You Yan, Jin Tang, Xiaoxin Zhao, Han Guo, Minyi Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (纸本)9781509032051

In this paper, we focus on designing an online credit card fraud detection framework with big data technologies, by which we want to achieve three major goals: 1) the ability to fuse multiple detection models to improve accuracy, 2) the ability to process large amount of data and 3) the ability to do the detection in real time. To accomplish that, we propose a general workflow, which satisfies most design ideas of current credit card fraud detection systems. We further implement the workflow with a new framework which consists of four layers: distributed storage layer, batch training layer, key-value sharing layer and streaming detection layer. With the four layers, we are able to support massive trading data storage, fast detection model training, quick model data sharing and real-time online fraud detection, respectively. We implement it with latest big data technologies like Hadoop, Spark, Storm, HBase, etc. A prototype is implemented and tested with a synthetic dataset, which shows great potentials of achieving the above goals. © 2016 IEEE.

关键词： Big data

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Massively parallel technologies Based on Microelectromechanical Systems for Improving Effective Functioning of the Aircraft 4

Massively Parallel Technologies Based on Microelectromechani...

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4th IEEE international conference Methods and Systems of Navigation and Motion Control (MSNMC)

作者： Serhii, Tovkach Natl Aviat Univ Kiev Ukraine

ISBN: (纸本)9781509010530

the problem of development adaptive control systems based on microelectromechanical systems for reduce turbulent flow of the aircraft has been considered. Complex solution based on microelectromechanical systems and graphic processing platform NVIDIA Tegra, which includes massively parallel technology, has been proposed. It develops parallel processing software based on algorithms that delivers scaling and speed up on distributed memory systems for high performance applications. the distributed microelectromechanical systems technique involves spreading integrated sense-compute-act modules over areas to sense the physical world and act upon it. Tiny elements can reduce drag by sensing vortices and interacting with them. It will help to reach better maneuverability, increase the range of aircraft payload and capability.

关键词： turbulent flow control microelectromechanical sysytems (MEMS) parallel computing scaling graphic processing unit

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A New Control Method of parallel-Connected Inverters Using Receding-horizon Prediction with Continuous Control Set 8

A New Control Method of parallel-Connected Inverters Using R...

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8th IEEE international Power Electronics and Motion Control conference (IPEMC-ECCE Asia)

作者： Chen, Manxin Hu, Jiefeng Li, Kerui Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781509012107

Existing control techniques of parallel-connected inverters are often complicated with multiple voltage and current loops. A large amount of tuning effort is required to ensure system stability, and the power quality is usually deteriorated due to voltage deviations. this paper proposes a new control method for parallel-connected three-phase voltage source inverters using model predictive control (MPC). High-quality voltages for local loads can be obtained. In addition, each inverter can adjust the output current to achieve proper load sharing according to the power ratings of distributed generation (DG) sources. Hot-swap capability is also achieved to facilitate the connection or disconnection operations to the common AC bus. Started with State-Space function which includes time-consuming matrix calculation can be done in PC. thus, control gains are found and MPC can be achieved based on a digital signal processor (DSP). the proposed method is simple without complex coordinate transformation or proportional-integral (PI) regulators. the effectiveness of the proposed control strategy are verified by the test results under various scenarios, presenting promising applications in microgrids.

关键词： distributed Generation parallel-Connected Inverters Model predictive Control (MPC)

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parallel Gathering Discovery over Big Trajectory Data 4

Parallel Gathering Discovery over Big Trajectory Data

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4th IEEE international conference on Big Data (Big Data)

作者： Xian, Yongyi Liu, Yan Xu, Chuanfei Concordia Univ Fac Engn & Comp Sci Montreal PQ Canada

ISBN: (纸本)9781467390057

the advances in location-acquisition technologies have generated massive spatio-temporal trajectory data, which represent the mobility of a diversity of moving objects over time, such as people, vehicles, and animals. Discovery of traveling companions on trajectory data has many real-world applications. Most of existing discovery approaches are limited to centralized computing, while these techniques for handling large-scale trajectory data require considerable performance improvement. parallel computing essentially provides an alternative method for handling this problem. In this work, we first present the design and implementation of both batch and streaming gathering patterns discovery algorithm in a distributed parallel computing fashion. Afterwards, we further propose several optimization techniques for efficient computation. Finally we conduct extensive experiments based on a public dataset to evaluate the efficiency of our approaches and effectiveness of optimizations using Amazon EC2 clusters.

关键词： parallel computing gathering discovery trajectory data

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Review of Energy Routers Applied for the Energy Internet Integrating Renewable Energy 8

Review of Energy Routers Applied for the Energy Internet Int...

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8th IEEE international Power Electronics and Motion Control conference (IPEMC-ECCE Asia)

作者： Guo, Hui Wang, Fei Luo, Jian Zhang, Lijun Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China

ISBN: (纸本)9781509012107

A technical review of energy routers applied in the future energy internet is carried out in this paper. the energy router (E-router) as a critical equipment of the energy internet can better solve changes of the power dispatching and management caused by a variety of distributed renewable energy sources accessing to low-voltage distribution networks. Basic design considerations and components of the E-router in terms of power conversions, energy management and communication are summarized in details. this paper classifies the E-router according to different applications and further analyzes the function structures and the implementation of different types of the E-router, which shows key components/technologies are solid state transformers, multiport-converters and time-division multiplex transmission respectively.

关键词： distributed renewable energy energy internet energy router solid state transformer multiport converter hierarchical control

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An Agglomeration Strategy for the parallel Processes Mapping onto a distributed computing Architecture 6th

An Agglomeration Strategy for the Parallel Processes Mapping...

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6th international conference on Supercomputing in Mexico (ISUM)

作者： Catana-Salazar, Juan C. Ortega-Arjona, Jorge L. Univ Nacl Autonoma Mexico Posgrad Ciencia & Ingn Computac Mexico City 04510 DF Mexico Univ Nacl Autonoma Mexico Fac Ciencias Dept Matemat Mexico City 04510 DF Mexico

ISBN: (纸本)9783319322438;9783319322421

parallel processes, by nature, tend to interchange a high amount of data between them to maintain a highly cohesive system. Nevertheless, when a parallel system is executed on a distributed computing architecture, communications over the network and the time spent by them become very important. this paper introduces a strategy, based on the Max-flow min-cut theorem, to agglomerate and allocate parallel processes onto a distributed computing architecture. the main goal of the strategy is to decrease the amount of remote communications and increase the amount of local communications. the strategy allocates the processes "carefully" over the distributed nodes, and that causes the communication time of the parallel system to be minimized.

关键词： parallel process Mapping problem Networks flows

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Large-scale geographically weighted regression on Spark 8

Large-scale geographically weighted regression on Spark

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8th international conference on Knowledge and Systems Engineering, KSE 2016

作者： Tran, Hung Tien Nguyen, Hiep Tuan Tran, Viet-Trung Hanoi University of Science and Technology Viet Nam

ISBN: (纸本)9781467389297

Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is a critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale. © 2016 IEEE.

关键词： parallel programming

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