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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1404 条记录，以下是671-680 订阅

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A Component Based Graphical parallel Programming Approach for Numerical Simulation Development

A Component Based Graphical Parallel Programming Approach fo...

引用

IEEE international conference on Big Data Security on cloud (BigDataSecurity), High Performance and Smart computing (HPSC) and Intelligent Data and Security (IDS)

作者： Liao Li Mo Zeyao Zhang Aiqing High Performance Computing Center CAEP Software Center for High Performance Numerical Simulation Beijing China

Building massively parallel numerical simulations is not easy due to lasting changes of parallel programming models and various software technologies needed. We develop a component based graphical parallel programming approach to lower the difficulties of coding applications in scientific and engineering computing and support rapid development of large scale simulations basing on a domain specific framework. parallel applications can be constructed simply by configuring components and assembling them in predefined flowcharts interactively. Large part of codes is auto generated from the graphical configuration for an application. The approach facilitates the rapid design and development of parallel numerical simulations by shielding many knowledge and technologies required from domain experts. Real applications demonstrate that the approach for developing complex numerical is both practical and efficient.

关键词： Kernel Numerical simulation Programming Numerical models parallel processing Graphical user interfaces

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SBDaaS: Smart building diagnostics as a service on the cloud

SBDaaS: Smart building diagnostics as a service on the cloud

引用

international conference on Intelligent Green Building and Smart grid (IGBSG)

作者： Nader Mohamed Sanja Lazarova-Molnar Jameela Al-Jaroodi Middleware Technologies Lab. Bahrain Center for Energy Informatics University of Southern Denmark Denmark Department of Engineering Robert Morris University USA

ISBN: (纸本)9781467382564

Huge amounts of data can be collected from smart buildings for accurate diagnostics. However, analyzing, storing and processing this data require huge resources as well as advanced software that implements innovative algorithms for accurate smart building diagnostics. This can be very costly for smart buildings owners. cloud computing can provide a scalable and cost-effective platform to satisfy these needs. cloud computing is an emerging commercial IT infrastructure model that offers to eliminate the need for clients to maintain in-house high-cost hardware, software, and network infrastructures. It also reduces or even eliminates the high-cost of recruiting technical professionals to support these infrastructures and operate the in-house IT solutions. This paper proposes a new cloud service that provides some mechanisms for smart building diagnostics that clients, smart building owners and managers, can use. This service is called Smart Building Diagnostics as a Service (SBDaaS). The paper presents an architecture developed for this service. In addition, it discusses the opportunities of utilizing such a service.

关键词： cloud computing Smart buildings Fault detection Energy consumption Computational modeling

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GPU-Accelerated Preconditioned GMRES Solver

GPU-Accelerated Preconditioned GMRES Solver

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IEEE international conference on Big Data Security on cloud (BigDataSecurity), High Performance and Smart computing (HPSC) and Intelligent Data and Security (IDS)

作者： Bo Yang Hui Liu Zhangxin Chen Xuhong Tian Dept. of Chemical and Petroleum Engineering University of Calgary Calgary AB Canada College of Mathematics and Informatics South China Agricultural University Guangzhou China

Linear solvers and parallel computing are crucial for developing a new generation reservoir simulator. To acquire satisfied acceleration performance, we study the parallel algorithms of linear solvers with preconditioners on GPUs (Graphics Processing Units). The classical GMRES solver is implemented, and the parallelization of ILU(0) and ILUT preconditioners based on the Restricted Additive Schwarz (RAS) method is studied. We also develop a parallel triangular solver to solve preconditioner systems on GPUs. The numerical experiments demonstrate our ILU preconditioned solver has favorable acceleration performance against a traditional CPU.

关键词： Graphics processing units Linear systems Sparse matrices Mathematical model Algorithm design and analysis conferences Reservoirs

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A new data-intensive task scheduling in optorsim, an open source grid simulator

A new data-intensive task scheduling in optorsim, an open so...

引用

international conference on Open Source Software computing (OSSCOM)

作者： Mahshid Helali Moghadam Seyyed Morteza Babamir Department of Computer Engineering University of Kashan Kashan Iran

ISBN: (纸本)9781509045815

Scheduling is one of the most important issues in executing tasks in grid systems. A data grid mainly deals with sharing and managing large amounts of distributed data in executing data-intensive applications. It is primarily a solution to satisfy the requirements of data-intensive tasks processing. OptorSim is a useful open source simulation tool for data grids. In this paper a new two-step data-intensive task scheduling called DSAS was proposed, implemented and, incorporated as a new scheduling package into OptorSim. As stated by the simulation results, the proposed scheduling strategy which was added to OptorSim, improves the mean response time and the mean waiting time of tasks compared to other common tasks scheduling strategies. The modified OptorSim benefits from a new scheduling package which improves the performance of task scheduling.

关键词： Scheduling Processor scheduling Computational modeling distributed databases Data models Performance evaluation Simulation

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A Security-Aware Data Placement Mechanism for Big Data cloud Storage Systems

A Security-Aware Data Placement Mechanism for Big Data Cloud...

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IEEE international conference on Big Data Security on cloud (BigDataSecurity), High Performance and Smart computing (HPSC) and Intelligent Data and Security (IDS)

作者： Seungmin Kang Bharadwaj Veeravalli Khin Mi Mi Aung Department of Electrical and Computer Engineering National University of Singapore Singapore Data Storage Institute A*STAR Singapore

Public clouds have become an attractive candidate to meet the ever-growing storage demands. However, storing data in public clouds increases data retrieval time and threat level for data security. These challenges drive the need for intelligent methods that solve the data placement problem to achieve high performance while satisfying the security requirement. In this paper, we propose a novel approach for data placement in cloud storage systems addressing the above challenges. With the security constraint, we first formulate the data placement problem as a linear programming model that minimizes the total retrieval time of a data, which is divided and distributed over storage nodes. We then develop a heuristic algorithm namely Security-awarE Data placement mechanism for cloud storage Systems (SEDuLOUS) to solve the problem. We demonstrate the effectiveness of the proposed algorithm through comprehensive simulations. The simulation results show that the proposed algorithm significantly reduces the retrieval time by up to 20% for the random-network-topology systems and 19% for the Internet2-topology system compared to baseline methods, which consider only the security requirement.

关键词： cloud computing Silicon distributed databases Encryption Data models Memory

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A Potential Field Based Framework for Publish/Subscribe Service in P2P cloud

A Potential Field Based Framework for Publish/Subscribe Serv...

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international conference on parallel and distributed Systems (ICPADS)

作者： Jiangfeng Li Zhenyu Liao Zehong Zhou Jian Xu Qinpei Zhao Chenxi Zhang School of Software Engineering Tongji Univeristy Shanghai P.R.China

ISBN: (纸本)9781509053827

As Internet is developing rapidly, new information is generated with an incredibly high speed. In this situation, publish/subscribe services provided by cloud providers are used to recommend useful information to the users in the Internet. However, the middleware models and routing algorithms in existing publish/subscribe approaches cannot perform efficiently in the P2P cloud, which is one of the novel cloud types that belongs to the distributed cloud. The P2P cloud brings challenge to publish/subscribe services because it has larger scale and more complicated network architecture than the traditional cloud. In this paper, a Potential Field based service framework is proposed to provide high-quality publish/subscribe services in P2P cloud. A middleware is designed in the framework to match subscribe requests and published information. Furthermore, a Potential Field Model is constructed. Under the model, event brokers are organized as P2P overlay for routing on request message. The simulation results show our proposed method has advantages in recall rate, response time, and bandwidth cost against other methods.

关键词： cloud computing Potential energy Routing Clustering algorithms Biological system modeling Monitoring

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A Modified Ant Colony based optimization for managing cloud resources in manufacturing sector

A Modified Ant Colony based optimization for managing Cloud ...

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IEEE international conference on Green High Performance computing (ICGHPC)

作者： N.C. Brintha J.T. Winowlin Jappes Shajulin Benedict Department of Computer Science and Engineering Kalasalingam Institute of Technology Krishnankoil India Department of Mechanical Engineering Kalasalingam University Krishnankoil India HPCCLoud Research Laboratory St. Xaviers Catholic College of Engineering Chunkankadai India

Resource scheduling and management is an important problem in cloud Manufacturing. The concept of optimization for scheduling jobs is an important issue to be considered in scheduling of different resources among heterogeneous users. The resources are placed across diversified locations in cloud and the major task is to distribute the resources effectively such that the makespan and completion time is reduced. In this paper, a Modified Ant Colony based optimization technique is proposed to optimize the resources through distributed computation. ACO is used to choose one among the different alternative rules to determine the processing order of each resource. Rather than having a larger search space, this approach reduces the search space and gives better solution. This reduces the delay in allocating resources to the user by providing an adaptive and global search technique. This approach reduces the total completion time of jobs and also takes in to account the migration time of the process. A series of experiments were conducted and the results of the experiment are compared with other heuristic algorithms like PSO. The results have shown that this approach can produce optimal solutions quickly by reducing delays.

关键词： cloud computing Manufacturing Resource management Job shop scheduling Processor scheduling Ant colony optimization

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Trusted third party for data security in cloud environment

Trusted third party for data security in cloud environment

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international conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB)

作者： Noopur Katre Deepti Theng G.H. Raisoni College of Engineering Nagpur (M.S.) India

ISBN: (纸本)9781467397469

cloud computing which is an up growing technology required more security especially when it include third party as service provider. To overcome this issue ECC which is data encryption technique for cloud environment with trusted third party will be used which will provide key management by which the key manager will provide multiple keys, which will avoid the chances of whole data from getting hacked at a time and also provide access control and file secured deletion. Using the anonymization technique with ECC will help access only authorised data to the authorized user. When the file gets deleted logically and further more the key can be retrieve if the client needs to access its uploaded data from the cloud by using the same ECC, this protocol is highly efficient. By using this protocol it will prevent from any kind of intrusion from any anonymous intruder, thus the overall outcome expected from this work will be to provide security for the access of data in cloud environment.

关键词： cloud computing Elliptic curve cryptography Encryption distributed databases Protocols

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A post-prognostics decision framework for cell site using cloud computing and Internet of Things

A post-prognostics decision framework for cell site using Cl...

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international conference on cloud Technologies and Applications (cloudTech)

作者： Safa Meraghni Labib Sadek Terrissa Noureddine Zerhouni Christophe Varnier Soheyb Ayad LINFI Laboratory University of Biskra Biskra Algeria UMR CNRS 6174- UFC / ENSMM / UTBM Institut FEMTO-ST Besancon France

ISBN: (纸本)9781467388955

Maintenance is one of the main factors of production process. The aim of maintenance strategy is not just to repair and maintain equipment in a good condition, but to implement efficient maintenance solutions to ensure the good function while minimizing the cost of maintenance. Predictive maintenance strategy start by collecting data from sensors, analyze this data and predict the malfunction or failure in the system. As a result, with this information, we try to find the optimal solution for maintenance. Prognostics Health Manager (PHM) offers significant benefits for maintenance. It predicts the future behavior of a system as well as its remaining useful life. However when factories have a large number of asset with mobile and stationary equipment in different geographically sites. Making decision and collecting data become difficult to be done. In this study we interested in stationary equipment geographically distributed; and we propose a decision post-prognostics framework to help engineers to take the optimal decision for maintenance operation in order to minimize maintenance cost. In order to enhance the post-prognostics decision, we propose a framework based on Iot technology for real-time sensing to collect data from equipment and cloud computing paradigm for resources management and information processing.

关键词： Computer architecture cloud computing Reliability Lead Microprocessors Maintenance engineering

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A Proposed Architecture for Soft computing in Smart grid as a cloud-based Service 2

A Proposed Architecture for Soft Computing in Smart Grid as ...

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2nd international conference on Knowledge Based engineering and Innovation (KBEI)

作者： Dezhabad, Naghmeh Motamedi, Seyed Ahmad Sharifian, Saeed Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781467365062

Smart grid empowers the electrical utilities improve the efficiency and the availability of the power system while constantly monitoring, controlling and managing the demands of customers. Computational requirements for Smart grid applications can be met by utilizing the cloud computing model. Collecting, storing and analyzing large amount of data, which can be very varied and produced at high rates will be done in a distributed manner. The scalable and elastic resources of a cloud infrastructure not only satisfy these needs but also offer interesting properties to utility companies (i.e., elasticity, scalability, pay-as-you-go model, etc.) and make a reliable, robust, and efficient Smart grid environment. In this paper, we present the opportunities and challenges of using cloud computing in power grid Applications and propose a cloud-based solution for information requirements of Smart grid.

关键词： component Smart grid cloud computing Soft grid Big Data

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