Virtual data Grid middleware services for data-intensive science

2006 ◽  
Vol 18 (6) ◽  
pp. 595-608 ◽  
Author(s):  
Yong Zhao ◽  
Michael Wilde ◽  
Ian Foster ◽  
Jens Voeckler ◽  
James Dobson ◽  
...  
Keyword(s):  
Data Grid ◽  
Data Intensive ◽  
Grid Middleware ◽  
Virtual Data

scholarly journals Grid middleware services for virtual data discovery, composition, and integration

2004 ◽  
Author(s):  
Yong Zhao ◽  
Michael Wilde ◽  
Ian Foster ◽  
Jens Voeckler ◽  
Thomas Jordan ◽  
...  
Keyword(s):  
Data Discovery ◽  
Grid Middleware ◽  
Virtual Data

A Virtual Data Grid for LIGO

2001 ◽  
pp. 3-12 ◽  
Author(s):  
Ewa Deelman ◽  
Carl Kesselman ◽  
Roy Williams ◽  
Albert Lazzarini ◽  
Thomas A. Prince ◽  
...  
Keyword(s):  
Data Grid ◽  
Virtual Data

Grid Computing Based Middleware for Labor and Social Security Data Storage Resources Discovery

2011 ◽  
Vol 148-149 ◽  
pp. 1425-1428
Author(s):  
Jian Yu
Keyword(s):  
Social Security ◽  
Grid Computing ◽  
Data Storage ◽  
Social Insurance ◽  
Large Scale ◽  
Data Grid ◽  
Dynamic Management ◽  
Grid Middleware ◽  
Large Scale Data ◽  
Large Groups

Labor and social security social insurance and employment related to large groups of services. The labor security department of information technology often combined with computational grid computing systems. This paper presents a new kind of data grid middleware for data storage resources discovery and dynamic management in labor and social security resources environment. The architecture of grid storage resources discovery and dynamic management is presented for discovering data storage resources from the different computer organizational structure. The middleware can realize the necessary functions for the ultra large-scale application in data grid environment. It could be applied to the ultra large-scale data storage management in grid computing in next generation labor and social security resources environment.

scholarly journals Tracking provenance in a virtual data grid

2008 ◽  
Vol 20 (5) ◽  
pp. 565-575 ◽  
Author(s):  
Ben Clifford ◽  
Ian Foster ◽  
Jens-S. Voeckler ◽  
Michael Wilde ◽  
Yong Zhao
Keyword(s):  
Data Grid ◽  
Virtual Data

Speculative Scheduling of Parameter Sweep Applications using Job Behaviour Descriptions

2011 ◽  
pp. 72-89
Author(s):  
Attila Ulbert ◽  
László Csaba Lorincz ◽  
Tamás Kozsik ◽  
Zoltán Horváth
Keyword(s):  
Decision Procedure ◽  
Job Scheduling ◽  
Data Migration ◽  
Job Descriptions ◽  
Job Description ◽  
Data Intensive ◽  
Grid Middleware ◽  
Grid Applications ◽  
Access Information ◽  
Completion Times

The execution of data intensive Grid applications raises several questions regarding job scheduling, data migration, and replication. This paper presents new scheduling algorithms using more sophisticated job behaviour descriptions that allow estimating job completion times more precisely thus improving scheduling decisions. Three approaches of providing input to the decision procedure are discussed: a) single job description, b) multiple job descriptions, and c) multiple job descriptions with mutation. The proposed Grid middleware components (1) monitor the execution of jobs and gather resource access information, (2) analyse the compiled information and generate a description of the behaviour of the job, (3) refine the already existing job description, and (4) use the refined behaviour description to schedule the submitted jobs.

ARRA: An Associated Replica Replacement Algorithm Based on Apriori Approach for Data Intensive Jobs in Data Grid

2010 ◽  
Vol 439-440 ◽  
pp. 1409-1414 ◽  
Author(s):  
Jian Hua Jiang ◽  
Hui Fang Ji ◽  
Gao Chao Xu ◽  
Xiao Hui Wei
Keyword(s):  
Data File ◽  
Data Grid ◽  
Relative Advantage ◽  
Data Intensive ◽  
File Access ◽  
Replacement Algorithm ◽  
Data Files ◽  
Network Usage ◽  
Effective Network ◽  
Replica Replacement

Creating many replicas in the processing of data-intensive jobs in data grid is an efficient strategy. Replica replacement is the crucial step to this strategy. Economic model, popularity model and hybrid model etc. have been proposed to solve this issue of replica replacement with analysis and prediction based on each data file, however, these models neglect association relationships among different data files. To find out these association relationships hidden in data-intensive jobs, Apriori algorithm in data mining field is adopted to analyze behaviors of each data-intensive job. An associated replica replacement algorithm based on Apriori approach in data grid is proposed in this paper. This algorithm has two major steps: 1) associated behavior analysis and classification of data files in each node; 2) generation and application of replica replacement rules. Our proposed algorithm is simulated in Optorsim to be compared with LFU algorithm. The experiment shows that there is a relative advantage compared with LFU in mean job times of all jobs, number of remote file access and effective network usage perspectives.

scholarly journals Server‐side workflow execution using data grid technology for reproducible analyses of data‐intensive hydrologic systems

2016 ◽  
Vol 3 (4) ◽  
pp. 163-175 ◽  
Author(s):  
Bakinam T. Essawy ◽  
Jonathan L. Goodall ◽  
Hao Xu ◽  
Arcot Rajasekar ◽  
James D. Myers ◽  
...  
Keyword(s):  
Data Grid ◽  
Grid Technology ◽  
Workflow Execution ◽  
Data Intensive ◽  
Server Side ◽  
Hydrologic Systems ◽  
Using Data
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