Publication:
A noble approach to develop dynamically scalable namenode in hadoop distributed file system using secondary storage

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cris.author.scopus-author-id 57205622345
cris.author.scopus-author-id 55633508000
cris.author.scopus-author-id 57820914600
cris.author.scopus-author-id 58196719900
cris.author.scopus-author-id 57195514183
cris.author.scopus-author-id 57194844651
dc.contributor.author Shaha T.R.
dc.contributor.author Akhtar M.N.
dc.contributor.author Johora F.T.
dc.contributor.author Hossain M.Z.
dc.contributor.author Rahman M.
dc.contributor.author Ahmad R.B.
dc.date.accessioned 2024-12-14T04:31:38Z
dc.date.available 2024-12-14T04:31:38Z
dc.date.issued 2019-02-01
dc.description.abstract For scalable data storage, Hadoop is widely used nowadays. It provides a distributed file system that stores data on the compute nodes. Basically, it represents a master/slave architecture that consists of a NameNode and copious Data Nodes. Data Nodes contain application data and metadata of application data resides in the Main Memory of NameNode. In cached approach, they fragment the metadata depending on the last access time and move the least frequently used data to secondary memory. If the requested data is not found in main memory then the secondary data will be loaded again on the RAM. So when the secondary data reloads to the primary memory then the NameNode main memory limitation arises again. The focus of this research is to reduce the namespace problem of main memory and to make the system dynamically scalable. A new Metadata Fragmentation Algorithm is proposed that separates the metadata list of NameNode dynamically. The NameNode creates Secondary Memory File in perspective of the threshold value and allocates secondary memory location based on the requirement. According to the proposed algorithm the maximum third, out of fourth of main memory is used at the secondary file caching time. The free space aids in faster operation by Dynamically Scalable NameNode approach. This proposed algorithm shows that the space utilization is increased to 17% and time utilization is increased to 0.0005% with the comparison of the existing fragmentation algorithm.
dc.identifier.doi 10.11591/ijeecs.v13.i2.pp729-736
dc.identifier.scopus 2-s2.0-85060852974
dc.identifier.uri https://hdl.handle.net/20.500.14170/10834
dc.relation.grantno undefined
dc.relation.ispartof Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.ispartofseries Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.issn 25024752
dc.rights open access
dc.subject Datanode | Hadoop | Metadata | Namenode | Secondary storage
dc.title A noble approach to develop dynamically scalable namenode in hadoop distributed file system using secondary storage
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 736
oaire.citation.issue 2
oaire.citation.startPage 729
oaire.citation.volume 13
oairecerif.affiliation.orgunit Dhaka University of Engineering and Technology, Gazipur
oairecerif.affiliation.orgunit Dhaka University of Engineering and Technology, Gazipur
oairecerif.affiliation.orgunit Jahangirnagar University
oairecerif.affiliation.orgunit Dhaka University of Engineering and Technology, Gazipur
oairecerif.affiliation.orgunit Daffodil International University
oairecerif.affiliation.orgunit Universiti Sultan Zainal Abidin
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person.identifier.scopus-author-id 57205622345
person.identifier.scopus-author-id 55633508000
person.identifier.scopus-author-id 57820914600
person.identifier.scopus-author-id 58196719900
person.identifier.scopus-author-id 57195514183
person.identifier.scopus-author-id 57194844651
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