From the I-WAY to the National Technology Grid

Woodward, Paul R.; DeFanti, Tom; Catlett, Charlie

doi:10.1145/265684.265692

Cited by 62 publications

(34 citation statements)

References 7 publications

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“…When the popularity of a data file passes a dynamic threshold, the replication operation will be triggered. (4),…”

Section: Decide Which and When To Replicatementioning

confidence: 99%

“…As a specialization and extension of the Grid [1], the Data Grid is a solution for this problem [2]. A data grid connects a collection of hundreds of geographically distributed computers and storage resources located in different parts of the world to facilitate sharing of data and resources [3], [4]. Grids can be classified into computational grids and data grids [5].…”

Section: Introductionmentioning

confidence: 99%

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A four-phase data replication algorithm for data grid

Saleh¹,

Javidan

FatehiKhajeh³

2015

JACST

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Nowadays, scientific applications generate a huge amount of data in terabytes or petabytes. Data grids currently proposed solutions to large scale data management problems including efficient file transfer and replication. Data is typically replicated in a Data Grid to improve the job response time and data availability. A reasonable number and right locations for replicas has become a challenge in the Data Grid. In this paper, a four-phase dynamic data replication algorithm based on Temporal and Geographical locality is proposed. It includes: 1) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 2) analyzing and modeling the relationship between system availability and the number of replicas, and calculating a suitable number of new replicas; 3) evaluating and identifying the popular data in each site, and placing replicas among them; 4) removing files with least cost of average access time when encountering insufficient space for replication. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid Projects. The simulation results show that the proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, effective network usage and percentage of storage filled.

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“…When the popularity of a data file passes a dynamic threshold, the replication operation will be triggered. (4),…”

Section: Decide Which and When To Replicatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A four-phase data replication algorithm for data grid

Saleh¹,

Javidan

FatehiKhajeh³

2015

JACST

View full text Add to dashboard Cite

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“…"Networked virtual supercomputers, or metacomputers, are execution environments in which high-speed networks are used to connect supercomputers, databases, scientific instruments, and advanced display devices, perhaps located at geographically distributed sites" [8] 2,3 * "The National Computational Science Alliance calls its prototype infrastructure the National Technology Grid, a name derived from the notion of the electrical power grid that transformed the U.S., and indeed the world, during the past century" [22] "Computational grids are large-scale high-performance distributed computing environments that provide dependable, consistent, and pervasive access to high-end computational resources" [9] 1,8,9,10 "A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities" [6] 8,9,10 "The real and specific problem that underlies the Grid concept is coordinated resource sharing and problem solving in dynamic, multiinstitutional virtual organizations" [11] 4,6,10 "A distributed network computing (NC) system is a virtual computer formed by a networked set of heterogeneous machines that agree to share their local resources with each other. A Grid is a very large scale, generalized distributed NC system that can scale to Internet-size environments with machines distributed across multiple organizations and administrative domains" [18] 1,2 * ,3,4,5,7 * "Grid technologies and infrastructure support the sharing and coordinated use of diverse resources in dynamic, distributed virtual organizations -that is, the creation, from geographically distributed components operated by distinct organizations with differing policies, of virtual computing systems that are sufficiently integrated to deliver the desired QoS" [12] 2,3,4,5,6,7 * ,8,10…”

Section: Main Grid Usesmentioning

confidence: 99%

“…The I-WAY experiment in turn motivated some very important projects such as the National Technology Grid, which coined in 1997 the term grid, "a name derived from the notion of the electrical power grid", to call the "truly U.S. national-scale advanced computational infrastructure" they envisioned [22].…”

Section: Introductionmentioning

confidence: 99%

Grid Characteristics and Uses: A Grid Definition

2004

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“…Inicialmente, los conceptos y tecnologías relacionados con el Grid fueron desarrollados para permitir la compartición de recursos en las colaboraciones científicas [142,143]. La necesidad de este tipo de colaboraciones no eraúnicamente la compartición de datos experimentales sino también aplicaciones, recursos computacionales e instrumental específico como telescopios y microscopios [141].…”

Section: Objetivos Principalesunclassified

Computación de altas prestaciones sobre entornos grid en aplicaciones biomédicas: simulación de la actividad eléctrica cardiaca y diseño de proteínas

Martínez¹

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The important research advances, in many scientific areas, have been fostered by an improvement of the computational strategies employed. As an example, High Performance Computing enables the collaborative usage of multiple processors to accelerate the resolution of scientific problems, and even to face large problems.However, there are several scientific applications whose computational requirements can exceed the computing capacities of a single organisation. This way, the recent advances in the bandwidth of the communication networks have leveraged the idea of joining geographically distributed resources, creating a global computing infrastructure known as the Grid.This thesis combines High Performance Computing and Grid Computing in order to accelerate the execution of scientific applications, and to allow solving problems that can not be solved, in a reasonable time, with the resources of a single organisation.For that purpose, a system that offers an abstraction layer to simplify the execution of general scientific applications, in Grid infrastructures, has been developed. This system, called GMarte, provides metascheduling functionality for the concurrent execution of parallel applications on resources based on the Globus Toolkit, the standard software in computational Grids. Later, and according to the current trend towards service-oriented architectures, a metascheduler Grid service has been created, featuring interoperability and based on standard technologies. This Grid service offers metascheduling functionality to multiple clients, which use high-level graphical applications to interact with it, using security mechanisms for data protection. This way, it is possible to simplify and foster the usage of Grid technologies for the efficient execution of scientific applications.The proposed computational approach has been applied to two biomedical applications: the cardiac electrical activity simulation and the protein design with targeted properties. First of all, a parallel simulation system of the action potential propagation on cardiac tissues has been developed.Secondly, an efficient system has been implemented for the design of proteins. In both cases, the usage of High Performance Computing has enabled to accelerate the executions as well as to face larger dimension problems.Finally, executions of both applications have been performed over different Grid deployments, in order to evaluate the advantages of a strategy that combines both computationally advanced techniques. 3 Títol Computació d'Altes Prestacions en Entorns Grid en Aplicacions Biomèdiques: Simulació de l'Activitat Elèctrica Cardiaca i Disseny de Proteines ResumEls importants avanços en la investigació, de nombrosesàrees de coneixement, han vingut propiciats per una millora en les estratègies de computació emprades. A mode d'exemple, la Computació d'Altes Prestacions permet la utilització col·laborativa de múltiples processadors per a accelerar la resolució de problemes científics, i fins i tot abordar problemes de major dimens...

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From the I-WAY to the National Technology Grid

Cited by 62 publications

References 7 publications

A four-phase data replication algorithm for data grid

A four-phase data replication algorithm for data grid

Grid Characteristics and Uses: A Grid Definition

Computación de altas prestaciones sobre entornos grid en aplicaciones biomédicas: simulación de la actividad eléctrica cardiaca y diseño de proteínas

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