Storage Space Optimisation for Green Data Center
The characteristic that determines a green data center is low amount of carbon footprint produced by its physical data storages. Increasing demand of data volumes in many data intensive applications call for additional physical data storages that are not only impractically large to maintain, but als...
Saved in:
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2013
|
Subjects: | |
Online Access: | http://eprints.utem.edu.my/id/eprint/10981/1/procedia.pdf http://eprints.utem.edu.my/id/eprint/10981/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utem.eprints.10981 |
---|---|
record_format |
eprints |
spelling |
my.utem.eprints.109812021-09-02T12:50:55Z http://eprints.utem.edu.my/id/eprint/10981/ Storage Space Optimisation for Green Data Center Nurul A., Emran Abdullah, Noraswaliza ZA4450 Databases The characteristic that determines a green data center is low amount of carbon footprint produced by its physical data storages. Increasing demand of data volumes in many data intensive applications call for additional physical data storages that are not only impractically large to maintain, but also contribute to the amount of carbon footprint produced. It is argued in this paper that, if storage space can be optimised to gain free spaces, the storage space requirement can be reduced. In this paper, a model to optimize database storage space by mining functional dependencies that are present among data sets is proposed. Sample data sets from the microbial domain have been used where data of large data volume raises storage space concern. The initial results of the implementation of the model that is necessary in designing a complete space optimization algorithm are presented. Elsevier 2013 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/10981/1/procedia.pdf Nurul A., Emran and Abdullah, Noraswaliza (2013) Storage Space Optimisation for Green Data Center. Procedia Engineering , 53 . pp. 483-490. ISSN 1877-7058 |
institution |
Universiti Teknikal Malaysia Melaka |
building |
UTEM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknikal Malaysia Melaka |
content_source |
UTEM Institutional Repository |
url_provider |
http://eprints.utem.edu.my/ |
language |
English |
topic |
ZA4450 Databases |
spellingShingle |
ZA4450 Databases Nurul A., Emran Abdullah, Noraswaliza Storage Space Optimisation for Green Data Center |
description |
The characteristic that determines a green data center is low amount of carbon footprint produced by its physical data storages. Increasing demand of data volumes in many data intensive applications call for additional physical data storages that are not only impractically large to maintain, but also contribute to the amount of carbon footprint produced. It is argued in this paper that, if storage space can be optimised to gain free spaces, the storage space requirement can be reduced. In this paper, a model to optimize database storage space by mining functional dependencies that are present among data sets is proposed. Sample data sets from the microbial domain have been used where data of large data volume raises storage space concern. The initial results of the implementation of the model that is necessary in designing a complete space optimization algorithm are presented. |
format |
Article |
author |
Nurul A., Emran Abdullah, Noraswaliza |
author_facet |
Nurul A., Emran Abdullah, Noraswaliza |
author_sort |
Nurul A., Emran |
title |
Storage Space Optimisation for Green Data Center |
title_short |
Storage Space Optimisation for Green Data Center |
title_full |
Storage Space Optimisation for Green Data Center |
title_fullStr |
Storage Space Optimisation for Green Data Center |
title_full_unstemmed |
Storage Space Optimisation for Green Data Center |
title_sort |
storage space optimisation for green data center |
publisher |
Elsevier |
publishDate |
2013 |
url |
http://eprints.utem.edu.my/id/eprint/10981/1/procedia.pdf http://eprints.utem.edu.my/id/eprint/10981/ |
_version_ |
1710679396558307328 |
score |
13.18916 |