Enabling BOINC in infrastructure as a service cloud system
Volunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different se...
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doaj-a50ab993f4e04f2e9a399331d29f6d352020-11-24T23:45:13ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032017-02-0110281182610.5194/gmd-10-811-2017Enabling BOINC in infrastructure as a service cloud systemD. Montes0J. A. Añel1T. F. Pena2P. Uhe3D. C. H. Wallom4EPhysLab, Universidade de Vigo, Ourense, SpainEPhysLab, Universidade de Vigo, Ourense, SpainCentro de Investigación en Tecnoloxías da Información (CITIUS), University of Santiago de Compostela, Santiago de Compostela, SpainSchool of Geography and the Environment, University of Oxford, Oxford, UKOxford e-Research Centre, University of Oxford, Oxford, UKVolunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low-cost access to massive computing resources but also where there is a significant public interest in the research being done.<br><br>We discuss the way in which cloud services can help BOINC-based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing platform within the cloud, and outline new approaches that could open up new possibilities in this field, using Climateprediction.net (<a href="http://www.climateprediction.net/" target="_blank">http://www.climateprediction.net/</a>) as a case study.</p>http://www.geosci-model-dev.net/10/811/2017/gmd-10-811-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
D. Montes J. A. Añel T. F. Pena P. Uhe D. C. H. Wallom |
spellingShingle |
D. Montes J. A. Añel T. F. Pena P. Uhe D. C. H. Wallom Enabling BOINC in infrastructure as a service cloud system Geoscientific Model Development |
author_facet |
D. Montes J. A. Añel T. F. Pena P. Uhe D. C. H. Wallom |
author_sort |
D. Montes |
title |
Enabling BOINC in infrastructure as a service cloud system |
title_short |
Enabling BOINC in infrastructure as a service cloud system |
title_full |
Enabling BOINC in infrastructure as a service cloud system |
title_fullStr |
Enabling BOINC in infrastructure as a service cloud system |
title_full_unstemmed |
Enabling BOINC in infrastructure as a service cloud system |
title_sort |
enabling boinc in infrastructure as a service cloud system |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2017-02-01 |
description |
Volunteer or crowd computing is becoming increasingly popular for solving
complex research problems from an increasingly diverse range of areas. The
majority of these have been built using the Berkeley Open Infrastructure for
Network Computing (BOINC) platform, which provides a range of different
services to manage all computation aspects of a project. The BOINC system is
ideal in those cases where not only does the research community involved need
low-cost access to massive computing resources but also where there is a
significant public interest in the research being done.<br><br>We discuss the way in which cloud services can help BOINC-based projects to
deliver results in a fast, on demand manner. This is difficult to achieve
using volunteers, and at the same time, using scalable cloud resources for
short on demand projects can optimize the use of the available resources. We
show how this design can be used as an efficient distributed computing
platform within the cloud, and outline new approaches that could open up new
possibilities in this field, using Climateprediction.net (<a href="http://www.climateprediction.net/" target="_blank">http://www.climateprediction.net/</a>) as a
case study.</p> |
url |
http://www.geosci-model-dev.net/10/811/2017/gmd-10-811-2017.pdf |
work_keys_str_mv |
AT dmontes enablingboincininfrastructureasaservicecloudsystem AT jaanel enablingboincininfrastructureasaservicecloudsystem AT tfpena enablingboincininfrastructureasaservicecloudsystem AT puhe enablingboincininfrastructureasaservicecloudsystem AT dchwallom enablingboincininfrastructureasaservicecloudsystem |
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