6,467 research outputs found
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
The Dark Energy Survey Data Management System
The Dark Energy Survey collaboration will study cosmic acceleration with a
5000 deg2 griZY survey in the southern sky over 525 nights from 2011-2016. The
DES data management (DESDM) system will be used to process and archive these
data and the resulting science ready data products. The DESDM system consists
of an integrated archive, a processing framework, an ensemble of astronomy
codes and a data access framework. We are developing the DESDM system for
operation in the high performance computing (HPC) environments at NCSA and
Fermilab. Operating the DESDM system in an HPC environment offers both speed
and flexibility. We will employ it for our regular nightly processing needs,
and for more compute-intensive tasks such as large scale image coaddition
campaigns, extraction of weak lensing shear from the full survey dataset, and
massive seasonal reprocessing of the DES data. Data products will be available
to the Collaboration and later to the public through a virtual-observatory
compatible web portal. Our approach leverages investments in publicly available
HPC systems, greatly reducing hardware and maintenance costs to the project,
which must deploy and maintain only the storage, database platforms and
orchestration and web portal nodes that are specific to DESDM. In Fall 2007, we
tested the current DESDM system on both simulated and real survey data. We used
Teragrid to process 10 simulated DES nights (3TB of raw data), ingesting and
calibrating approximately 250 million objects into the DES Archive database. We
also used DESDM to process and calibrate over 50 nights of survey data acquired
with the Mosaic2 camera. Comparison to truth tables in the case of the
simulated data and internal crosschecks in the case of the real data indicate
that astrometric and photometric data quality is excellent.Comment: To be published in the proceedings of the SPIE conference on
Astronomical Instrumentation (held in Marseille in June 2008). This preprint
is made available with the permission of SPIE. Further information together
with preprint containing full quality images is available at
http://desweb.cosmology.uiuc.edu/wik
Next-Generation EU DataGrid Data Management Services
We describe the architecture and initial implementation of the
next-generation of Grid Data Management Middleware in the EU DataGrid (EDG)
project.
The new architecture stems out of our experience and the users requirements
gathered during the two years of running our initial set of Grid Data
Management Services. All of our new services are based on the Web Service
technology paradigm, very much in line with the emerging Open Grid Services
Architecture (OGSA). We have modularized our components and invested a great
amount of effort towards a secure, extensible and robust service, starting from
the design but also using a streamlined build and testing framework.
Our service components are: Replica Location Service, Replica Metadata
Service, Replica Optimization Service, Replica Subscription and high-level
replica management. The service security infrastructure is fully GSI-enabled,
hence compatible with the existing Globus Toolkit 2-based services; moreover,
it allows for fine-grained authorization mechanisms that can be adjusted
depending on the service semantics.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla,Ca, USA, March 2003 8 pages, LaTeX, the file contains all
LaTeX sources - figures are in the directory "figures
Data as a Service (DaaS) for sharing and processing of large data collections in the cloud
Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft
Grids and the Virtual Observatory
We consider several projects from astronomy that benefit from the Grid paradigm and
associated technology, many of which involve either massive datasets or the federation
of multiple datasets. We cover image computation (mosaicking, multi-wavelength
images, and synoptic surveys); database computation (representation through XML,
data mining, and visualization); and semantic interoperability (publishing, ontologies,
directories, and service descriptions)
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Connecting the time domain community with the Virtual Astronomical Observatory
The time domain has been identified as one of the most important areas of
astronomical research for the next decade. The Virtual Observatory is in the
vanguard with dedicated tools and services that enable and facilitate the
discovery, dissemination and analysis of time domain data. These range in scope
from rapid notifications of time-critical astronomical transients to annotating
long-term variables with the latest modeling results. In this paper, we will
review the prior art in these areas and focus on the capabilities that the VAO
is bringing to bear in support of time domain science. In particular, we will
focus on the issues involved with the heterogeneous collections of (ancillary)
data associated with astronomical transients, and the time series
characterization and classification tools required by the next generation of
sky surveys, such as LSST and SKA.Comment: Submitted to Proceedings of SPIE Observatory Operations: Strategies,
Processes and Systems IV, Amsterdam, 2012 July 2-
Core Services in the Architecture of the National Digital Library for Science Education (NSDL)
We describe the core components of the architecture for the (NSDL) National
Science, Mathematics, Engineering, and Technology Education Digital Library.
Over time the NSDL will include heterogeneous users, content, and services. To
accommodate this, a design for a technical and organization infrastructure has
been formulated based on the notion of a spectrum of interoperability. This
paper describes the first phase of the interoperability infrastructure
including the metadata repository, search and discovery services, rights
management services, and user interface portal facilities
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