Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13584
DC FieldValueLanguage
dc.contributor.authorKakoulli, Elena-
dc.contributor.authorKarmiris, Nikolaos D.-
dc.contributor.authorHerodotou, Herodotos-
dc.date.accessioned2019-05-01T10:12:23Z-
dc.date.available2019-05-01T10:12:23Z-
dc.date.issued2018-08-
dc.identifier.citation44th International Conference on Very Large Data Bases, VLDB 2018; Rio de Janeiro; Brazil; 27 -31 August 2017, Journal Proceedings of the VLDB Endowment, vol. 11, no. 12, pp. 1914-1917en_US
dc.identifier.issn2150-8097-
dc.description.abstractThe continuous improvements in memory, storage devices, and network technologies of commodity hardware introduce new challenges and opportunities in tiered storage management. Whereas past work is exploiting storage tiers in pairs or for specific applications, OctopusFS-a novel distributed file system that is aware of the underlying storage mediaoffers a comprehensive solution to managing multiple storage tiers in a distributed setting. OctopusFS contains automated data-driven policies for managing the placement and retrieval of data across the nodes and storage tiers of the cluster. It also exposes the network locations and storage tiers of the data in order to allow higher-level systems to make locality-aware and tier-aware decisions. This demonstration will showcase the web interface of OctopusFS, which enables users to (i) view detailed utilization information for the various storage tiers and nodes, (ii) browse the directory namespace and perform file-related actions, and (iii) execute caching-related operations while observing their performance impact on MapReduce and Spark workloads.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© Association for Computing Machineryen_US
dc.subjectMapReduceen_US
dc.subjectSpark workloadsen_US
dc.titleOctopusFS in action: Tiered storage management for data intensive computingen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.relation.conferenceInternational Conference on Very Large Data Basesen_US
dc.identifier.doi10.14778/3229863.3236223en_US
cut.common.academicyear2017-2018en_US
item.openairetypeconferenceObject-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.languageiso639-1en-
item.fulltextWith Fulltext-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-1489-807X-
crisitem.author.orcid0000-0002-8717-1691-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
Files in This Item:
File Description SizeFormat
p1914-kakoulli.pdfFulltext687.13 kBAdobe PDFView/Open
CORE Recommender
Show simple item record

SCOPUSTM   
Citations 50

1
checked on Nov 6, 2023

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s) 50

398
Last Week
0
Last month
2
checked on Dec 4, 2024

Download(s) 50

108
checked on Dec 4, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.