Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.

As the amounts of data and use of distributed systems for data storage and processing have increased, reducing the number of replications has turned into a crucial requirement in these systems, which has been addressed by plenty of research. In this paper, an algorithm has been proposed to reduce th...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Khatereh Sabaghian, Keyhan Khamforoosh, Abdolbaghi Ghaderzadeh
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/322aa71e314042998c27589bc8e76701
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:322aa71e314042998c27589bc8e76701
record_format	dspace
spelling	oai:doaj.org-article:322aa71e314042998c27589bc8e767012021-12-02T20:09:21ZPresentation of a new method based on modern multivariate approaches for big data replication in distributed environments.1932-620310.1371/journal.pone.0254210https://doaj.org/article/322aa71e314042998c27589bc8e767012021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254210https://doaj.org/toc/1932-6203As the amounts of data and use of distributed systems for data storage and processing have increased, reducing the number of replications has turned into a crucial requirement in these systems, which has been addressed by plenty of research. In this paper, an algorithm has been proposed to reduce the number of replications in big data transfer and, eventually to lower the traffic load over the grid by classifying data efficiently and optimally based on the sent data types and using VIKOR as a method of multivariate decision-making for ranking replication sites. Considering different variables, the VIKOR method makes it possible to take all the parameters effective in the assessment of site ranks into account. According to the results and evaluations, the proposed method has exhibited an improvement by about thirty percent in average over the LRU, LFU, BHR, and Without Rep. algorithms. Furthermore, it has improved the existing multivariate methods through different approaches to replication by thirty percent, as it considers effective parameters such as time, the number of replications, and replication site, causing replication to occur when it can make an improvement in terms of access.Khatereh SabaghianKeyhan KhamforooshAbdolbaghi GhaderzadehPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254210 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Khatereh Sabaghian Keyhan Khamforoosh Abdolbaghi Ghaderzadeh Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
description	As the amounts of data and use of distributed systems for data storage and processing have increased, reducing the number of replications has turned into a crucial requirement in these systems, which has been addressed by plenty of research. In this paper, an algorithm has been proposed to reduce the number of replications in big data transfer and, eventually to lower the traffic load over the grid by classifying data efficiently and optimally based on the sent data types and using VIKOR as a method of multivariate decision-making for ranking replication sites. Considering different variables, the VIKOR method makes it possible to take all the parameters effective in the assessment of site ranks into account. According to the results and evaluations, the proposed method has exhibited an improvement by about thirty percent in average over the LRU, LFU, BHR, and Without Rep. algorithms. Furthermore, it has improved the existing multivariate methods through different approaches to replication by thirty percent, as it considers effective parameters such as time, the number of replications, and replication site, causing replication to occur when it can make an improvement in terms of access.
format	article
author	Khatereh Sabaghian Keyhan Khamforoosh Abdolbaghi Ghaderzadeh
author_facet	Khatereh Sabaghian Keyhan Khamforoosh Abdolbaghi Ghaderzadeh
author_sort	Khatereh Sabaghian
title	Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
title_short	Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
title_full	Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
title_fullStr	Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
title_full_unstemmed	Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
title_sort	presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/322aa71e314042998c27589bc8e76701
work_keys_str_mv	AT khaterehsabaghian presentationofanewmethodbasedonmodernmultivariateapproachesforbigdatareplicationindistributedenvironments AT keyhankhamforoosh presentationofanewmethodbasedonmodernmultivariateapproachesforbigdatareplicationindistributedenvironments AT abdolbaghighaderzadeh presentationofanewmethodbasedonmodernmultivariateapproachesforbigdatareplicationindistributedenvironments
_version_	1718375054375387136

Presentation of a new method based on modern multivariate approaches for big data replication in distributed environments.

Ejemplares similares