An Architectural Overview of the GRelC Data Access Service

2012 ◽  
pp. 517-527
Author(s):  
Sandro Fiore ◽  
Alessandro Negro ◽  
Salvatore Vadacca ◽  
Massimo Cafaro ◽  
Giovanni Aloisio ◽  
...  
Keyword(s):  
Data Access ◽  
Data Grid ◽  
Distributed Data ◽  
Distributed Environment ◽  
Database Access ◽  
Grid Environments ◽  
Grid Database ◽  
Access Service ◽  
Real Challenge ◽  
Grid Storage

Grid computing is an emerging and enabling technology allowing organizations to easily share, integrate and manage resources in a distributed environment. Computational Grid allows running millions of jobs in parallel, but the huge amount of generated data has caused another interesting problem: the management (classification, storage, discovery etc.) of distributed data, i.e., a Data Grid specific issue. In the last decade, many efforts concerning the management of data (grid-storage services, metadata services, grid-database access and integration services, etc.) identify data management as a real challenge for the next generation petascale grid environments. This work provides an architectural overview of the GRelC DAS, a grid database access service developed in the context of the GRelC Project and currently used for production/tutorial activities both in gLite and Globus based grid environments.

An Architectural Overview of the GRelC Data Access Service

2009 ◽  
pp. 98-108 ◽  
Author(s):  
Sandro Fiore ◽  
Alessandro Negro ◽  
Salvatore Vadacca ◽  
Massimo Cafaro ◽  
Giovanni Aloisio ◽  
...  
Keyword(s):  
Data Access ◽  
Data Grid ◽  
Distributed Data ◽  
Distributed Environment ◽  
Database Access ◽  
Grid Environments ◽  
Grid Database ◽  
Access Service ◽  
Real Challenge ◽  
Grid Storage

Grid computing is an emerging and enabling technology allowing organizations to easily share, integrate and manage resources in a distributed environment. Computational Grid allows running millions of jobs in parallel, but the huge amount of generated data has caused another interesting problem: the management (classification, storage, discovery etc.) of distributed data, i.e., a Data Grid specific issue. In the last decade, many efforts concerning the management of data (grid-storage services, metadata services, grid-database access and integration services etc.) identify data management as a real challenge for the next generation petascale grid environments. This work provides an architectural overview of the GRelC DAS, a grid database access service developed in the context of the GRelC Project and currently used for production/tutorial activities both in gLite and Globus based grid environments.

Advanced Grid DataBase Management with the GRelC Data Access Service

2007 ◽  
pp. 683-694 ◽  
Author(s):  
Sandro Fiore ◽  
Alessandro Negro ◽  
Salvatore Vadacca ◽  
Massimo Cafaro ◽  
Maria Mirto ◽  
...  
Keyword(s):  
Database Management ◽  
Data Access ◽  
Grid Database ◽  
Access Service

Towards Ubiquitous Data Access Service of 3D Part Library in Cloud Scheme with Host Independence

2021 ◽  
Author(s):  
Wei Liu ◽  
Chuipin Kong ◽  
Qiang Niu ◽  
Xionghui Zhou
Keyword(s):  
3D Modeling ◽  
Data Access ◽  
Mobile Terminals ◽  
Cad Systems ◽  
Manufacturing Enterprises ◽  
3D Data ◽  
Uniform Interface ◽  
Access Service ◽  
Ongoing Project ◽  
Remote Part

Abstract Most current part libraries are created and deployed in specific usage environments or CAD platforms, which inevitably brings obstacles in the share and exchange for part information. To reduce repeated development and provide a uniform interface for designers in different sites, a 3D part library in cloud scheme is presented in this paper. Host programs with predetermined specification can access the part data through an adapter according to their customized requests with uniform interfaces, which constructs a ubiquitous service. To realize host independence, the part models are created in a native ACIS modeler, and then they are converted into 3D files in various formats for practical needs, finally these files are imported into CAD systems or other platforms in real designs. The whole framework can be divided into three components, namely, PLS(Part Library Service) provider, PLS adapters and hosts. PLS provider is the kernel of 3D data access service in cloud scheme, while PLS adapters serve as the bridges that connect PLS provider and hosts, and the PLS can be grafted on various applications including current mainstream CAD systems as a plug-in module or run on the websites or even mobile terminals. The PLS provider is deployed and maintained on cloud and users can acquire remote part information within a local ongoing project. In the detailed construction of this part library, diversiform knowledge for part parameters and structures is implanted to define the geometry and rule constraints in the 3D modeling, with which the backstage has the ability of conveniently editing the information in the part library for better upgrade and contrapuntally services. The concept has been implemented within a PaaS framework to provide the ubiquitous 3D part data access, which has been successfully applied in a large number of manufacturing enterprises, and accumulates considerable practical cases.

An Ontology-based approach to enable data-driven research in the field of NDT in Civil Engineering

2021 ◽  
Author(s):  
Benjamin Moreno-Torres ◽  
Christoph Völker ◽  
Sabine Kruschwitz
Keyword(s):  
Knowledge Representation ◽  
Civil Engineering ◽  
Common Knowledge ◽  
Measurement Data ◽  
Data Access ◽  
Semantic Knowledge ◽  
Data Sources ◽  
Data Sets ◽  
Extensive Literature ◽  
Distributed Data

<div> <p>Non-destructive testing (NDT) data in civil engineering is regularly used for scientific analysis. However, there is no uniform representation of the data yet. An analysis of distributed data sets across different test objects is therefore too difficult in most cases.</p> <p>To overcome this, we present an approach for an integrated data management of distributed data sets based on Semantic Web technologies. The cornerstone of this approach is an ontology, a semantic knowledge representation of our domain. This NDT-CE ontology is later populated with the data sources. Using the properties and the relationships between concepts that the ontology contains, we make these data sets meaningful also for machines. Furthermore, the ontology can be used as a central interface for database access. Non-domain data sources can be integrated by linking them with the NDT ontology, making them directly available for generic use in terms of digitization. Based on an extensive literature research, we outline the possibilities that result for NDT in civil engineering, such as computer-aided sorting and analysis of measurement data, and the recognition and explanation of correlations.</p> <p>A common knowledge representation and data access allows the scientific exploitation of existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis or material characterization) and simplifies bidirectional knowledge and data transfer between engineers and NDT specialists.</p> </div>

Grid Data Handling

2013 ◽  
pp. 294-321
Author(s):  
Alexandru Costan
Keyword(s):  
Fault Tolerance ◽  
Data Storage ◽  
Large Scale ◽  
File Systems ◽  
Future Research ◽  
Distributed Data ◽  
Data Handling ◽  
Grid Data ◽  
Distributed Data Storage ◽  
Grid Environments

To accommodate the needs of large-scale distributed systems, scalable data storage and management strategies are required, allowing applications to efficiently cope with continuously growing, highly distributed data. This chapter addresses the key issues of data handling in grid environments focusing on storing, accessing, managing and processing data. We start by providing the background for the data storage issue in grid environments. We outline the main challenges addressed by distributed storage systems: high availability which translates into high resilience and consistency, corruption handling regarding arbitrary faults, fault tolerance, asynchrony, fairness, access control and transparency. The core part of the chapter presents how existing solutions cope with these high requirements. The most important research results are organized along several themes: grid data storage, distributed file systems, data transfer and retrieval and data management. Important characteristics such as performance, efficient use of resources, fault tolerance, security, and others are strongly determined by the adopted system architectures and the technologies behind them. For each topic, we shortly present previous work, describe the most recent achievements, highlight their advantages and limitations, and indicate future research trends in distributed data storage and management.

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