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检索条件"任意字段=18th International Conference on Parallel and Distributed Computing Systems, PDCS 2005"

共 303 条记录，以下是91-100 订阅

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Improved asynchronous group mutual exclusion in token-passing networks

Improved asynchronous group mutual exclusion in token-passin...

引用

18th IASTED international conference on parallel and distributed computing and systems

作者： Lin, David Moh, Teng-Sheng Moh, Melody San Jose State Univ Dept Comp Sci San Jose CA 95192 USA

ISBN: (纸本)9780889866386

Group mutual exclusion (GME) was first introduced by Joung [5] as a generalization of the n-process mutual exclusion problem, and subsequently modeled as the Congenial Talking Philosophers problem. GME allows processes requesting for the same resource to concurrently access the shared resource. However, a process requesting a resource that is different from the one currently being used will not be able to access the requested resource at the same time. Two solutions to the GME problem for a ring network exist. One by Wu and Joung had an unbounded message size problem [11, 12], the second one by Cantarell, et. al. provided a bound for message size, but could potentially generate an unbounded number of messages [2, 3]. this work presents a GME algorithm for a token-passing network that solves both problems by providing a bound both to the number of messages and to message size. Analysis results of time and message complexities and of correctness are presented. Performance is evaluated by simulation experiments, which further validate complexity analyses.

关键词： distributed algorithm group mutual exclusion message passing token passing

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How to improve the scalability of an industrial parallel reservoir simulator

How to improve the scalability of an industrial parallel res...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Gratien, Jean-Marc Guignon, thomas Magras, Jean-Francois Quandalle, Philippe Ricois, Olivier IFP Energies Nouvelles 1 & 4 Av Bois Preau F-92852 Rueil Malmaison France

ISBN: (纸本)9780889866386

Reservoir Engineering industry is very interested in using ever growing dataset with more and more complex physics and detailed models. the key issue still remains running simulations in an acceptable CPU time. Regarding the trend in hardware technologies, the challenge is to improve the efficiency of reservoir simulation software on a large number of processors. New numerical difficulties and performance problems appear when the number of cells and the number of processors are growing. In this paper, we present different approaches to overcome these kinds of problems. We discuss technical choices such like advanced scalable linear solver algorithm, load balancing issue with different domain decomposition strategies, dynamic space criteria, mesh partitioner strategy and parallel solver performance management, flexible 10 strategy from simple file system to more complex parallel file system or database. We have developed and benchmarked these different solutions on published reference large scale problems and actual case studies with several tens millions of cells. We analyse the results and discuss the efficiency of each solution to overcome the scalability difficulties and performance limitations due to load unbalance.

关键词： cluster reservoir simulation solver parallel IO scalability

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A distributed Fine-Grained Flow Control Sytem for Scalable Aircraft Spares Management and Optimization in Clouds

A Distributed Fine-Grained Flow Control Sytem for Scalable A...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Aye, theint theint Ta Nguyen Binh Duong Li, Xiaorong Li, Elaine Wong Kay A STAR Inst High Performance Comp 1 Fusionopolis Way Singapore 138632 Singapore EADS Innovat Works Singapore 797562 Singapore

ISBN: (纸本)9781467345651;9780769549033

In this paper, we presented the design, implementation, and evaluation of a distributed system to manage the parallelized analytics for Aircraft Spare parts Management and Optimizations (SMO), which is a well-known problem in logistics industry. Our proposed solution is able to solve the resource-intensive SMO problem using distributed computing infrastructures (e. g., private or public clouds) in a scalable manner. We designed and fine-tuned a parallel meta-heuristics based on a fine-grained flow control workflow model which enables flow controls of running parallel meta-heuristics in multiple processors and achieved significant performance gains. Together with priority based scheduling, the proposed system effectively dispatches submitted SMO jobs over the set of distributed resources to accommodate different classes of users. Extensive experimental studies were conducted to analyze the performance of parallelized SMO job executions in term of execution time, computation and data transmission time, waiting time, memory usage, etc. Insightful lessons have been drawn from the obtained results;and potential areas for further improvements have also been identified.

关键词： Cloud computing parallel meta-heuristics distributed systems workflow control job scheduling

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Enabling On-Demand Mashups of Open Data with Semantic Services

Enabling On-Demand Mashups of Open Data with Semantic Servic...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Feng, Yuzhang Veeramani, Anitha Kanagasabai, Rajaraman ASTAR Inst Infocomm Res Singapore Singapore

ISBN: (纸本)9781467345651;9780769549033

Analogous to software-as-a-service (SaaS), platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS), data-as-a-service (DaaS) is used to provide data on demand to users over the Internet and is gaining popularity in the current cloud computing era. In particular, several Open Data initiatives have led to a number of data services in various formats becoming available online, and it remains a challenge to make full use of the data by transferring between and answering queries from different sources in a automatic, dynamic and meaningful manner. In this paper we propose a service-oriented, composition-based approach towards tackling the integration of open data services. We provide a formal, semantic-based modeling of data services and convert the integration problem into the service composition problem. then the composition graph can be used to create the executable queries to the various data services. We illustrate our idea by using a case study in the real estate domain.

关键词： Data integration composition semantic service data services data integration Enabling Software as a service PLUG-IN Cloud computing open data

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A VM-based Resource Management Method Using Statistics

A VM-based Resource Management Method Using Statistics

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Zhang, Zhenzhong Xiao, Limin Li, Yongnan Ruan, Li Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China

ISBN: (纸本)9781467345651;9780769549033

Virtualization technology is one of the key technologies in cloud computing. Proper allocation of the virtual machines onto available hosts plays an important role on the performance optimization of cloud computing. At present, many resource management methods are based on the load model to predict the resource requirements of the application. However, a variety of heterogeneous hardware environments and virtualization technologies make it hard to efficiently allocate the resources based on existing methods. To address the problem, we proposed a virtual machine allocation strategy based on statistics. And the contribution of this paper include:(1) A load-resource model for estimating the resource demand of each virtual machine;(2) An algorithm for assigning virtual machines onto the hosts among resource pool according to the resources requirement of virtual machine. Experiments show that our load-resource model can accurately estimate the resource requirements of virtual machines for physical host, and our virtual machine assigning algorithm can achieve better load balancing compared with the first-fit and best-fit algorithm.

关键词： Cloud computing Virtual machine performance modeling Load balancing Virtual Machine Allocation Strategy

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Towards A Common Benchmark Framework for Cloud Brokers

Towards A Common Benchmark Framework for Cloud Brokers

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Le Duy Ngan Flora, Tsai S. Keong, Chan Chee Kanagasabai, Rajaraman ASTAR Data Anal Dept I2R Singapore Singapore Nanyang Technol Univ Sch Elect & Elect Engn EEE Singapore Singapore

ISBN: (纸本)9781467345651;9780769549033

Cloud computing has attracted a lot of interest from both academia and industry because of the promise of cost-effectiveness. As a result, increasingly large numbers of cloud services have become available. this implies challenges in brokering between the cloud consumers and providers. To meet this demand, several cloud brokers have been introduced. Unfortunately, most of the cloud brokers cannot solve real life scenarios and cannot be evaluated in an unbiased manner because their evaluations are often academic and independent. this paper proposes a new benchmark to evaluate and compare cloud brokers. Our benchmark called Cloud Broker Challenge (CBC) describes the cloud providers, cloud consumers, and goals with five variety levels of complexities. CBC Benchmark is useful to the Cloud community for an unbiased evaluation and comparison of brokers and can potentially enable development of real-life cloud brokers.

关键词： Cloud computing Cloud broker Cloud discovery Cloud service selection Performance evaluation

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Byzantine fault tolerant execution of long-running distributed applications

Byzantine fault tolerant execution of long-running distribut...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Pallemulle, Sajeeva L. Wehrman, Ian Goldman, Kenneth J. Washington Univ Dept Comp Sci & Engn St Louis MO 63130 USA

ISBN: (纸本)9780889866386

Long-running distributed applications that automate critical decision processes require Byzantine fault tolerance to ensure progress in spite of arbitrary failures. Existing replication protocols for data servers guarantee that externally requested operations execute correctly even if a bounded number of replicas fail arbitrarily. However, since these protocols only support passive state machine replication, they are insufficient to support continued correct execution of autonomous long-running distributed applications. Building on the Castro and Liskov Byzantine Fault Tolerance protocol for replicated state machines (CLBFT), we present a practical algorithm for Byzantine fault-tolerant execution of autonomous distributed applications. the algorithm supports replicated clients that actively execute application logic by issuing operation requests on replicated data servers as well as other replicated clients. Our work facilitates dynamic upgrades to replica groups, supports both synchronous and asynchronous operation requests, and provides fault isolation between replica groups with respect to both correctness and performance. the algorithm scales well to large replica groups with only twice the latency and message complexity as compared to CLBFT, which supports only unreplicated clients.

关键词： fault tolerant systems Byzantine agreement autonomous distributed applications

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Communication-conscious mapping of regular nested loop programs onto massively parallel processor arrays

Communication-conscious mapping of regular nested loop progr...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Siegel, Sebastian Merker, Renate Hannig, Frank Teich, Juergen Tech Univ Dresden Inst Circuits & Syst D-01062 Dresden Germany Univ Erlangen Nurnberg Dept Comp Sci 12 D-91058 Erlangen Germany

ISBN: (纸本)9780889866386

Methods for an efficient mapping of algorithms to parallel architectures are of utmost importance because many state-of-the-art embedded digital systems deploy parallelism to increase their computational power. this paper deals with the mapping of loop programs onto processor arrays implemented in an FPGA or available as (reconfigurable) coarsegrained processor architectures. Most existing work is closely related to approaches from the DSP domain and is not able to exploit the full parallelism of a given algorithm and the computational potential of a typical 2-dimensional array. In contrast, we present a mapping methodology which incorporates many important parameters of the target architecture in one approach. these are: number of processing elements, resources of the data path and memory within a processing element, and interconnection within the processor array. Based on these parameters, we formulate an optimization problem whose solution specifies an efficient mapping of an algorithm to the target architecture. We can optimize for speed of the algorithm and/or hardware cost caused by the communication and computation resources of the architecture.

关键词： processor array interconnection data path hardware mapping integer linear programming

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Towards Cooperation between Multiple Video Retrieval systems Based on Impression 18

Towards Cooperation between Multiple Video Retrieval Systems...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Maeda, Tomoki Hochin, Teruhisa Nomiya, Hiroki Kyoto Inst Technol Grad Sch Informat Sci Kyoto Japan Kyoto Inst Technol Informat & Human Sci Kyoto Japan

ISBN: (纸本)9781509055043

this paper proposes a method to convert a factor score matrix for the cooperation between multiple video retrieval systems based on impression. A matrix transforming the factor loading matrix is used. As a result, we showed that the results of two applications of the factor analysis can satisfactorily be transformed by using the transformation matrix.

关键词： Keywords Multiple Video Retrieval System Adaptation Factor Analysis Multiple Regression Analysis

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An Optimal Fully distributed Algorithm to Minimize the Resource Consumption of Cloud Applications

An Optimal Fully Distributed Algorithm to Minimize the Resou...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Tziritas, Nikos Khan, Samee Ullah Xu, Cheng-Zhong Hong, Jue Chinese Acad Sci Beijing 100864 Peoples R China Univ N Dakota Grand Forks ND 58201 USA Wayne State Univ Detroit MI 48202 USA

ISBN: (纸本)9781467345651;9780769549033

According to the pay-per-use model adopted in clouds, the more the resources consumed by an application running in a cloud computing environment, the greater the amount of money the owner of the corresponding application will be charged. therefore, applying intelligent solutions to minimize the resource consumption is of great importance. Because centralized solutions are deemed unsuitable for large-distributed systems or large-scale applications, we propose a fully distributed algorithm (called DRA) to overcome the scalability issues. the aforementioned problem can be solved by identifying an assignment scheme between the interacting components of an application, such as processes and virtual machines, and the computing nodes of a cloud system, such that the total amount of resources consumed by the respective application is minimized. the decisions for the transition from one assignment scheme to another one are made in a dynamic way and based only on local information. It should be stressed that DRA achieves convergence and always results in the optimal solution. We also show, through an experimental evaluation, that DRA achieves up to 55% network cost reduction when compared to the most recent algorithm in the literature.

关键词： placement cloud computing network flow

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