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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 1401 条记录，以下是111-120 订阅

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Dynamic request allocation and scheduling for context aware applications subject to a percentile response time SLA in a distributed cloud

Dynamic request allocation and scheduling for context aware ...

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2nd IEEE international conference on cloud computing Technology and Science, cloudCom 2010

作者： Boloor, Keerthana Chirkova, Rada Viniotis, Yannis Salo, Tiia Department of Electrical and Computer Engineering North Carolina State University Raleigh NC United States Department of Computer Science North Carolina State University Raleigh NC United States IBM Software Research Triangle Park NC United States

ISBN: (纸本)9780769543024

We consider geographically distributed datacenters forming a collectively managed cloud computing system, hosting multiple Service Oriented Architecture (SOA) based context aware applications, each subject to Service Level Agreements (SLA). The Service Level Agreements for each context aware application require the response time of a certain percentile of the input requests to be less than a specified value for a profit to be charged by the cloud provider. We present a novel approach of data-oriented dynamic service-request allocation with gi-FIFO scheduling, in each of the geographically distributed datacenters, to globally increase the profit charged by the cloud computing system. Our evaluation shows that our dynamic scheme far outperforms the commonly deployed static allocation with either First in First Out (FIFO) or Weighted Round Robin (WRR) scheduling. © 2010 IEEE.

关键词： Profitability

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Research on security defense based on randomization in cloud computing environment 2

Research on security defense based on randomization in cloud...

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2nd international conference on Information Technology and Intelligent Control, CITIC 2022

作者： Yun, Kai Bai, Liang Tuerhong, Mieralimujiang Bai, Xiaojun State Grid Xinjiang Electric Power Co LTD. Information Communication Company Xinjiang830000 China

ISBN: (纸本)9781510657649

cloud computing uses cloud resources to provide users with computing and storage services It has changed the processing mode of information resources for individuals and enterprises But The existing security reinforcement methods of cloud computing environment can not deal with external attacks caused by the singularity of cloud computing environment services and its own vulnerabilities This article starts from the cloud service itself the security threats of cloud computing platform are studied from three aspects: cloud service interface and network interface In order to deal with these security threats, the cloud service itself is analyzed and compared Randomization method of cloud service interface and network interface next. A randomization deployment model with multi-level, inter layer randomization awareness and distributed collaboration is proposed. The problem of randomization parameter awareness in model deployment is discussed the cooperation of the same layer services on different virtual machines The corresponding solutions are given. Finally, the security measures and limitations of the randomization method are discussed. Point out the future research direction. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： distributed database systems

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Proceedings - 2nd IEEE international conference on cloud computing Technology and Science, cloudCom 2010

Proceedings - 2nd IEEE International Conference on Cloud Com...

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2nd IEEE international conference on cloud computing Technology and Science, cloudCom 2010

ISBN: (纸本)9780769543024

The proceedings contain 105 papers. The topics discussed include: LEMO-MR: low overhead and elastic MapReduce implementation optimized for memory and CPU-intensive applications;LEEN: locality/fairness-aware key partitioning for MapReduce in the cloud;correlation based file prefetching approach for Hadoop;elasticLM: a novel approach for software licensing in distributed computing infrastructures;a mechanism of flexible memory exchange in cloud computing environments;fine-grained data access control systems with user accountability in cloud computing;a token-based access control system for RDF data in the clouds;performance analysis of high performance computing applications on the Amazon web services cloud;combining grid and cloud resources by use of middleware for SPMD applications;using global behavior modeling to improve QoS in cloud data storage services;and resource allocation with a budget constraint for computing independent tasks in the cloud.

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parallelization of isogeometric analysis on memory distributed computing platforms

Parallelization of isogeometric analysis on memory distribut...

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2nd international conference on parallel, distributed, grid and cloud computing for engineering, PARENG 2011

作者： Rypl, D. Patzák, B. Department of Mechanics Faculty of Civil Engineering Czech Technical University Prague Czech Republic

ISBN: (纸本)9781905088423

Isogeometric analysis has been recently introduced as a viable alternative to the standard, polynomial-based finite element analysis. Similarly to the finite element method, isogeometric solution of complex engineering problems may lead to computationally very demanding analysis, demands of which can be alleviated by performing it in a parallel computing environment. This paper presents how the isogeometric analysis based on NURBS can be parallelized on memory distributed computing platforms. While the actual parallelization of the isogeometric computational code resembles methodologically very much the parallelization of the finite element code, the construction of the appropriate domain decomposition of the isogeometric mesh is rather complicated compared to the partitioning of the finite element mesh. The paper introduces a new methodology, how to construct a weighted dual graph of a twodimensional NURBS-based isogeometric mesh that can be decomposed by standard graph-based partitioning approaches. The application of the proposed strategy is illustrated on a simple two-dimensional example. © Civil-Comp Press, 2011.

关键词： Finite element method

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Coupling GPU and MPTCP to Improve Hadoop/MapReduce Performance 2

Coupling GPU and MPTCP to Improve Hadoop/MapReduce Performan...

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2nd international conference on Intelligent Green Building and Smart grid (IGBSG)

作者： Wang, Chia-Hui Yang, Chen-Kuei Liao, Wei-Chih Chang, Ray-I Wei, Tsao-Ta Ming Chuan Univ Dept Comp Sci & Informat Engn 5 Ming Rd Taoyuan 333 Taiwan Natl Taiwan Univ Dept Engn Sci 1Sec 4Roosevelt Rd Taipei 10617 Taiwan

ISBN: (纸本)9781467384735

Apache Hadoop is the famous open source cloud computing software in recent years, the performance is much better than before due to lots of researchers' efforts, but its performance still has chance to be improved further because of unsatisfied distributed computing speed and slow response time from heterogeneous Internet's uncertain and dynamic environment. In this paper, coupling emerging GPU computing with multi-path TCP (MPTCP) protocol is proposed for current Hadoop/MapReduce architecture to further improve the distributed computing performance. We use GPU computing to speed up the Map's process, and use MPTCP to reduce Reduce's data transfer time. The Hadoop benchmark applications such as Terasort, WordCount and PiEstimate are applied to demonstrate the improved performance of our proposed scheme. According to the preliminary experimental results, the proposed scheme can improve the Hadoop/MapReduce performance by coupling GPU computing and MPTCP multipath protocol with robustness and bandwidth aggregation, to reduce further the distributed computing latency.

关键词： cloud computing distributed computing Hadoop/MapReduce GPU computing MPTCP

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Load Balanced Static grid Scheduling Using Max-Min Heuristic

Load Balanced Static Grid Scheduling Using Max-Min Heuristic

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2nd IEEE international conference on parallel, distributed and grid computing (PDGC)

作者： Ghosh, Tarun Kumar Goswami, Rajmohan Bera, Sumit Barman, Subhabrata Haldia Inst Technol Haldia W Bengal India Pailan Coll Management & Technol Comp Applicat W Bengal India

ISBN: (纸本)9781467329255;9781467329224

grid computing, inspired by electrical power grid, is an emerging trend for making easy access to computing resources. Its main objective is to solve computationally hard problems which otherwise cannot be solved by single CPU. This extremely high computing power is achieved by optimal utilization of geographically distributed heterogeneous resources which are lying idle. Load balanced task scheduling is very important problem in complex grid environment. So task scheduling which is one of the NP-Complete problems becomes a focus of research scholars in grid computing area. The traditional Min-Min and Max-Min algorithms are simple algorithms that produces a schedule that minimizes the makespan than the other traditional algorithms in the literature. In real scenario of Min-Min and Max-Min failed to produce a load balanced schedule. The proposed method has two-phases. In the first phase the traditional Max-Min algorithm is executed and in the second phase the tasks are rescheduled to use the unutilized resources effectively.

关键词： grid computing grid Scheduling Makespan Max-Min Heuristic gridSim

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Improved Efficiency Of Fog And cloud computing Paradigms 2

Improved Efficiency Of Fog And Cloud Computing Paradigms

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2nd IEEE international conference on Advancements and Key Challenges in Green Energy and computing, AKGEC 2024

作者： Wakankar, Ronit Simhachalam, Sumanyu Ganesan, Raghavendran Velmurugan, T. Vellore Institute of Technology School of Electronics Engineering Sense Vellore India

ISBN: (纸本)9798350390179

For effective energy management in smart grids, this research suggests a FOG computing architecture that bridges the gap between the edge and cloud. Facing data congestion in both traditional edge and cloud computing, the system utilizes a two-tiered approach. By preprocessing and filtering sensor data from buildings, edge nodes reduce latency and network traffic. The FOG layer in turn effectively filters data for potential cloud processing while doing real time analysis and decision-making depending on immediate needs. With latency reduction of up to 98.7%, the simulation demonstrates significant benefits over cloud only approaches and enables real time energy adjustments that optimize resource utilization. Overall, scalability and efficient data handling overcome cloud limitations, while enhanced security minimizes reliance on a central cloud. This distributed brain for the grid paves the way for a smarter, more responsive energy landscape, powered by intelligence at the edge. © 2024 IEEE.

关键词： Fog computing

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Research on Query Task Fragmentation in the Scenario of Storage and Compute Separation 2

Research on Query Task Fragmentation in the Scenario of Stor...

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2nd international conference on Intelligent computing and Next Generation Networks, ICNGN 2023

作者： Wang, Beilei Wang, Yulin Li, Yuanzhe Northeastern University Software College Shenyang China Northeastern University Medical and Bioinformatics Engineering College Shenyang China

ISBN: (纸本)9798350329070

The cloud-native database is one of the hottest topics in database research. Storage-compute separation architecture with cloud characteristics is designed to process complex and changeable workloads to reduce resource coupling for cloud-native databases. During processing query loads, the computing layer pushes the operator tasks in execution plans generated from loads down to the storage layer through the network. Query optimization techniques such as operator pushdown and parallel computing have been developed and perfected to improve query speed in storage and compute separation architecture. But at the same time, these technologies also increase the complexity of execution plans, leading to an increase in tasks. Moreover, the experiment shows that under the same query load, the cloud-native database executes a significantly greater number of tasks compared to the distributed database. Given the above phenomenon, the concept of query task fragmentation is proposed. From the view of operator pushdown and parallel computing query optimization, the presence of query task fragmentation is verified through experiments. Experimental results based on the TPC-H benchmark demonstrate that, compared to MySQL distributed cluster, the average number of operator tasks in the execution plan, generated through operator pushdown and parallel computing for the cloud-native databases, increases by 20.17% and 39.49%, respectively. Finally, the impact of task fragmentation is analyzed from the perspectives of technical research and the application of cloud-native databases. © 2023 IEEE.

关键词： Query processing

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A METHOD OF cloud STORAGE ALGORTHOM FOR CROP IMAGES INFORMATION

A METHOD OF CLOUD STORAGE ALGORTHOM FOR CROP IMAGES INFORMAT...

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2nd IEEE international conference on cloud computing and Intelligent Systems (CCIS)

作者： Zhao, Chunjiang Gao, Ronghua Wu, Huarui Natl Engn Res Ctr Informat Technol Agr Beijing 100097 Peoples R China Minist Agr Key Lab Informat Technol Agr Beijing 100097 Peoples R China

ISBN: (纸本)9781467318556;9781467318570

With the development of high resolution images technique, large scale data intensive computing and computing-intensity is highly demanded. However, isolated storage and dispersive management cannot meet exponentially increasing demand for storage and management of crop images. On the basis of the crop images grasped by our independent developed agricultural intelligent search engine, a kind of extraction technique will be studied to extract the special feature behind scattered image data and to build up a cloud platform for the crop images information. Fast and accurate searching for crop images and its highly efficient management under cloud computation environment are achieved through map-reduce parallel mechanism.

关键词： cloud storage Massive image Pyramid distributed computing

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Resource Allocation based on Double Auction for cloud computing System

Resource Allocation based on Double Auction for Cloud Comput...

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18th IEEE international conference on High Performance computing and Communications (HPCC) / 14th IEEE international conference on Smart City (Smart City) / 2nd IEEE international conference on Data Science and Systems (DSS)

作者： Xu, Lei Wang, Jun Nallanathan, A. Li, Yaping Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China Kings Coll London Dept Informat London WC2R 2LS England Nanjing Forestry Univ Coll Econ & Management Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509042975

cloud computing is a new commercial model with distributed computing, utility computing, and grid computing. In many situations, both the cloud service providers (CSPs) and cloud service users maximize their earnings. Consequently, how to resolve the resource allocation and determine the transaction pricing between CSPs and users is a big challenge. In this paper, we propose a double auction-based cloud resource allocation and pricing model, which improves the auction efficiency. In this model, the profit of the middle auctioneer is taken into consideration, and a reliability mechanism is added to the model. The price for the CSPs is designed based on the resource price and the reliability index. Finally, a resource allocation algorithm is proposed. Simulation results demonstrate that the proposed algorithm reduces the number of auction rounds, and improves the auction efficiency very well.

关键词： cloud computing Reliability Resource Allocation Double Auction

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