Optimization of Data Access for Grid Environment

2004 ◽  
pp. 93-102 ◽  
Author(s):  
Lukasz Dutka ◽  
Renata Słota ◽  
Darin Nikolow ◽  
Jacek Kitowski
Keyword(s):  
Data Access ◽  
Grid Environment

Managing Inconsistencies in Data Grid Environments

2012 ◽  
pp. 303-316
Author(s):  
Ejaz Ahmed ◽  
Nik Bessis ◽  
Peter Norrington ◽  
Yong Yue
Keyword(s):  
Data Access ◽  
Heterogeneous Data ◽  
Data Mapping ◽  
Data Systems ◽  
Grid Environment ◽  
Federated Databases ◽  
Matching Process ◽  
Generic Strategy ◽  
Service Oriented ◽  
Matching Strategy

Much work has been done in the area of data access and integration using various data mapping, matching, and loading techniques. One of the main concerns when integrating data from heterogeneous data sources is data redundancy. The concern is mainly due to the different business contexts and purposes from which the data systems were originally built. A common process for accessing data from integrated databases involves the use of each data source’s own catalogue or metadata schema. In this article, the authors take the view that there is a greater chance of data inconsistencies, such as data redundancies when integrating them within a grid environment as compared to traditional distributed paradigms. The importance of improving the data search and matching process is briefly discussed, and a partial service oriented generic strategy is adopted to consolidate distinct catalogue schemas of federated databases to access information seamlessly. To this end, a proposed matching strategy between structure objects and data values across federated databases in a grid environment is presented.

Managing Inconsistencies in Data Grid Environments

2010 ◽  
Vol 2 (4) ◽  
pp. 51-64 ◽  
Author(s):  
Ejaz Ahmed ◽  
Nik Bessis ◽  
Peter Norrington ◽  
Yong Yue
Keyword(s):  
Data Access ◽  
Heterogeneous Data ◽  
Data Mapping ◽  
Data Systems ◽  
Grid Environment ◽  
Federated Databases ◽  
Matching Process ◽  
Generic Strategy ◽  
Service Oriented ◽  
Matching Strategy

Much work has been done in the area of data access and integration using various data mapping, matching, and loading techniques. One of the main concerns when integrating data from heterogeneous data sources is data redundancy. The concern is mainly due to the different business contexts and purposes from which the data systems were originally built. A common process for accessing data from integrated databases involves the use of each data source’s own catalogue or metadata schema. In this article, the authors take the view that there is a greater chance of data inconsistencies, such as data redundancies when integrating them within a grid environment as compared to traditional distributed paradigms. The importance of improving the data search and matching process is briefly discussed, and a partial service oriented generic strategy is adopted to consolidate distinct catalogue schemas of federated databases to access information seamlessly. To this end, a proposed matching strategy between structure objects and data values across federated databases in a grid environment is presented.

Spatial data access control in grid environment

2009 ◽  
Author(s):  
Menglong Yan ◽  
Yong Gao ◽  
Lun Wu ◽  
Pengfei Wu ◽  
Yong Zhao ◽  
...  
Keyword(s):  
Access Control ◽  
Spatial Data ◽  
Data Access ◽  
Grid Environment ◽  
Data Access Control

QoS-Constrained Resource Scheduling Base on Market Economy Models in Grid Computing

2013 ◽  
Vol 443 ◽  
pp. 599-602
Author(s):  
Lei Chen
Keyword(s):  
Market Economy ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Supply And Demand ◽  
Resource Scheduling ◽  
Data Access ◽  
Grid Environment ◽  
Task Scheduling Algorithm ◽  
User Tasks

The Grid task scheduling algorithm is proposed that takes the service quality of resource scheduling, time and cost together into consideration, so that it can better meet user tasks Quality of Service (QoS) requirements and make the complex grid environment open. On the basis of the price model drove by supply and demand in economy, we design the Grid task scheduling algorithm in the market economy model. The experiment results indicate the effectiveness of proposed algorithm in terms of usersQoS guarantee. It reduce data access latency and decrease bandwidth consumption.

Interactive Distributed Data Access in a GRID Environment

2004 ◽  
pp. 190-197
Author(s):  
D. Rodríguez ◽  
J. Marco ◽  
R. Marco ◽  
C. Martínez-Rivero
Keyword(s):  
Data Access ◽  
Distributed Data ◽  
Grid Environment

Simulation of Data Management in Group Purchasing System

2008 ◽  
Vol 33-37 ◽  
pp. 1445-1450
Author(s):  
Zong Feng Zou ◽  
Tao Yu
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Data Access ◽  
Reliable Data ◽  
Grid Environment ◽  
Comparison System ◽  
Price Comparison ◽  
Support Provider ◽  
The Stability ◽  
Modular Framework

By Data Grid to handle data sharing problems of distributed position in Group Purchasing. And so, evaluating and mining massive amounts of data is without fail required replication is important techniques to provide fast data access. Several replication modeling algorithms are studied in the paper. OptorSim provides a modular framework under different Grid environment. OptorSim is used to achieve the Grid simulator to research the stability and transient action. Modern group-companies are often made of many subsidiary companies. Stocking centralization can economize much fund for its large-scale purchasing action. Subordinate companies hope to choose the best provider according to reliable data in most possible area. Advanced data in variety units is massive amounts of data that must be post-processed and organized to support provider evaluation actions. Increasing data volumes from all of the companies challenge to state-of-the-art database system and data-loading techniques. Grid concept is adopted to solve the problem in the project which is named Price Comparison System (PCS). One of the key technologies in the system is to improve the data access.

A New Architecture of Data Access Middleware under Grid Environment

2006 ◽  
Author(s):  
Qingyang Wang ◽  
Jingshu Chen ◽  
Xibin Gao ◽  
Wei Zhou ◽  
Baoping Yan
Keyword(s):  
Data Access ◽  
Grid Environment
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