Architecturing elastic edge storage services for data-driven decision making

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorLujic, Ivanen_US
dc.contributor.authorTruong, Hong Linhen_US
dc.contributor.departmentVienna University of Technologyen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.editorBures, Tomasen_US
dc.contributor.editorDuchien, Laurenceen_US
dc.contributor.editorInverardi, Paolaen_US
dc.date.accessioned2019-11-07T12:04:55Z
dc.date.available2019-11-07T12:04:55Z
dc.date.embargoinfo:eu-repo/date/embargoEnd/2020-09-02en_US
dc.date.issued2019-01-01en_US
dc.description.abstractIn the IoT era, a massive number of smart sensors produce a variety of data at unprecedented scale. Edge storage has limited capacities posing a crucial challenge for maintaining only the most relevant IoT data for edge analytics. Currently, this problem is addressed mostly considering traditional cloud-based database perspectives, including storage optimization and resource elasticity, while separately investigating data analytics approaches and system operations. For better support of future edge analytics, in this work, we propose a novel, holistic approach for architecturing elastic edge storage services, featuring three aspects, namely, (i) data/system characterization (e.g., metrics, key properties), (ii) system operations (e.g., filtering, sampling), and (iii) data processing utilities (e.g., recovery, prediction). In this regard, we present seven engineering principles for the architecture design of edge data services.en
dc.description.versionPeer revieweden
dc.format.extent9
dc.format.extent97-105
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationLujic , I & Truong , H L 2019 , Architecturing elastic edge storage services for data-driven decision making . in T Bures , L Duchien & P Inverardi (eds) , Software Architecture - 13th European Conference, ECSA 2019, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 11681 LNCS , Springer , pp. 97-105 , European Conference on Software Architecture , Paris , France , 09/09/2019 . https://doi.org/10.1007/978-3-030-29983-5_7en
dc.identifier.doi10.1007/978-3-030-29983-5_7en_US
dc.identifier.isbn9783030299828
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.otherPURE UUID: 718f067a-041c-40cc-95a2-1921b8e3beb6en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/718f067a-041c-40cc-95a2-1921b8e3beb6en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85072839558&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/37786429/SCI_Lujic_Architecturing_truong_ecsa2019.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/41096
dc.identifier.urnURN:NBN:fi:aalto-201911076101
dc.language.isoenen
dc.relation.ispartofEuropean Conference on Software Architectureen
dc.relation.ispartofseriesSoftware Architecture - 13th European Conference, ECSA 2019, Proceedingsen
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.relation.ispartofseriesVolume 11681 LNCSen
dc.rightsopenAccessen
dc.subject.keywordAdaptationen_US
dc.subject.keywordArchitectural designen_US
dc.subject.keywordEdge computingen_US
dc.subject.keywordEdge data serviceen_US
dc.subject.keywordEngineeringen_US
dc.subject.keywordIoTen_US
dc.subject.keywordService computingen_US
dc.titleArchitecturing elastic edge storage services for data-driven decision makingen
dc.typeConference article in proceedingsfi
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