Markovian approximations for a grid computing network with a ring structure
Optical grid networks allow many computing sites to share their resources by connecting them through high-speed links, providing a more efficient use of the resources and a timely response for incoming jobs. These jobs originate from users connected to each of the sites and, in contrast to tradition...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2010
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/28113
- Acceso en línea:
- https://doi.org/10.1080/15326349.2010.498315
https://repository.urosario.edu.co/handle/10336/28113
- Palabra clave:
- Markov chains
Optical grids
Queueing networks
- Rights
- License
- Restringido (Acceso a grupos específicos)
id |
EDOCUR2_c8b5175d75174f6923a68bd8b5d262ba |
---|---|
oai_identifier_str |
oai:repository.urosario.edu.co:10336/28113 |
network_acronym_str |
EDOCUR2 |
network_name_str |
Repositorio EdocUR - U. Rosario |
repository_id_str |
|
spelling |
800352026009434e46a-0bd9-48dd-af17-71c10f74be0b2020-08-19T14:45:51Z2020-08-19T14:45:51Z2010-08-04Optical grid networks allow many computing sites to share their resources by connecting them through high-speed links, providing a more efficient use of the resources and a timely response for incoming jobs. These jobs originate from users connected to each of the sites and, in contrast to traditional queueing networks, a particular job does not have to be processed in a predefined site. Furthermore, a job is always processed locally if there is an available local server. In this paper we propose two different methods to approximate the performance of an optical grid network with a ring topology. The first method is based on approximating the inter-overflow time process, while the second separately characterizes the periods where jobs are overflowed and the periods where they are served locally. Both approaches rely on a marked Markovian representation of the overflow process at each station and on reducing this representation by moment-matching methods. The results show that the methods accurately approximate the rate of locally processed jobs, one of the main performance measures.application/pdfhttps://doi.org/10.1080/15326349.2010.498315ISSN: 1532-6349EISSN: 1532-4214https://repository.urosario.edu.co/handle/10336/28113engThe Institute for Operations Research and the Management SciencesTaylor & Francis383No. 3357Stochastic ModelsVol. 26Stochastic Models, ISSN: 1532-6349;EISSN: 1532-4214, Vol.26, No.3 (2010); pp. 357–383https://www.tandfonline.com/doi/abs/10.1080/15326349.2010.49831Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecStochastic Modelsinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURMarkov chainsOptical gridsQueueing networksMarkovian approximations for a grid computing network with a ring structureAproximaciones de Markov para una red informática en cuadrícula con estructura de anilloarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Pérez, Juan F.Van Houdt, B.10336/28113oai:repository.urosario.edu.co:10336/281132021-09-23 12:28:08.421https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Markovian approximations for a grid computing network with a ring structure |
dc.title.TranslatedTitle.spa.fl_str_mv |
Aproximaciones de Markov para una red informática en cuadrícula con estructura de anillo |
title |
Markovian approximations for a grid computing network with a ring structure |
spellingShingle |
Markovian approximations for a grid computing network with a ring structure Markov chains Optical grids Queueing networks |
title_short |
Markovian approximations for a grid computing network with a ring structure |
title_full |
Markovian approximations for a grid computing network with a ring structure |
title_fullStr |
Markovian approximations for a grid computing network with a ring structure |
title_full_unstemmed |
Markovian approximations for a grid computing network with a ring structure |
title_sort |
Markovian approximations for a grid computing network with a ring structure |
dc.subject.keyword.spa.fl_str_mv |
Markov chains Optical grids Queueing networks |
topic |
Markov chains Optical grids Queueing networks |
description |
Optical grid networks allow many computing sites to share their resources by connecting them through high-speed links, providing a more efficient use of the resources and a timely response for incoming jobs. These jobs originate from users connected to each of the sites and, in contrast to traditional queueing networks, a particular job does not have to be processed in a predefined site. Furthermore, a job is always processed locally if there is an available local server. In this paper we propose two different methods to approximate the performance of an optical grid network with a ring topology. The first method is based on approximating the inter-overflow time process, while the second separately characterizes the periods where jobs are overflowed and the periods where they are served locally. Both approaches rely on a marked Markovian representation of the overflow process at each station and on reducing this representation by moment-matching methods. The results show that the methods accurately approximate the rate of locally processed jobs, one of the main performance measures. |
publishDate |
2010 |
dc.date.created.spa.fl_str_mv |
2010-08-04 |
dc.date.accessioned.none.fl_str_mv |
2020-08-19T14:45:51Z |
dc.date.available.none.fl_str_mv |
2020-08-19T14:45:51Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1080/15326349.2010.498315 |
dc.identifier.issn.none.fl_str_mv |
ISSN: 1532-6349 EISSN: 1532-4214 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/28113 |
url |
https://doi.org/10.1080/15326349.2010.498315 https://repository.urosario.edu.co/handle/10336/28113 |
identifier_str_mv |
ISSN: 1532-6349 EISSN: 1532-4214 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
383 |
dc.relation.citationIssue.none.fl_str_mv |
No. 3 |
dc.relation.citationStartPage.none.fl_str_mv |
357 |
dc.relation.citationTitle.none.fl_str_mv |
Stochastic Models |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 26 |
dc.relation.ispartof.spa.fl_str_mv |
Stochastic Models, ISSN: 1532-6349;EISSN: 1532-4214, Vol.26, No.3 (2010); pp. 357–383 |
dc.relation.uri.spa.fl_str_mv |
https://www.tandfonline.com/doi/abs/10.1080/15326349.2010.49831 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.acceso.spa.fl_str_mv |
Restringido (Acceso a grupos específicos) |
rights_invalid_str_mv |
Restringido (Acceso a grupos específicos) http://purl.org/coar/access_right/c_16ec |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
The Institute for Operations Research and the Management Sciences Taylor & Francis |
dc.source.spa.fl_str_mv |
Stochastic Models |
institution |
Universidad del Rosario |
dc.source.instname.none.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.none.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1818107032899682304 |