Systematic mapping for big data stream processing frameworks

dc.authorscopusid57193499041
dc.authorscopusid8514029100
dc.authorscopusid14054145900
dc.contributor.authorYazıcı, Ali
dc.contributor.authorYazici,A.
dc.contributor.authorKarakaya, Ziya
dc.contributor.otherSoftware Engineering
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-07-05T15:44:36Z
dc.date.available2024-07-05T15:44:36Z
dc.date.issued2016
dc.departmentAtılım Universityen_US
dc.department-tempAlayyoub M., Atilim University, Institute of Natural and Applied Sciences, Ankara, Turkey; Yazici A., Atilim University, Faculty of Engineering, Ankara, Turkey; Karakaya Z., Atilim University, Faculty of Engineering, Ankara, Turkeyen_US
dc.description.abstractThere has been lots of discussions about the choice of a stream processing framework (SPF) for Big Data. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, the cutting edge technologies used in each stream processing framework might better them, it is still hard to say which framework bests the rest under different scenarios and conditions. In this study, we aim to show trends and differences about several SPFs for Big Data by using the Systematic Mapping (SM) approach. To achieve our objectives, we raise 6 research questions (RQs), in which 91 studies that conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can help researchers to obtain an overview of the field. © 2016 IEEE.en_US
dc.identifier.citation2
dc.identifier.doi10.1109/ICDIM.2016.7829760
dc.identifier.endpage36en_US
dc.identifier.isbn978-150902640-1
dc.identifier.scopus2-s2.0-85014331330
dc.identifier.startpage31en_US
dc.identifier.urihttps://doi.org/10.1109/ICDIM.2016.7829760
dc.identifier.urihttps://hdl.handle.net/20.500.14411/3793
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2016 11th International Conference on Digital Information Management, ICDIM 2016 -- 2016 11th International Conference on Digital Information Management, ICDIM 2016 -- 19 September 2016 through 21 September 2016 -- Porto -- 126084en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBig Dataen_US
dc.subjectFlinken_US
dc.subjectInfoSphereen_US
dc.subjectS4en_US
dc.subjectSparken_US
dc.subjectStormen_US
dc.subjectStreamingen_US
dc.titleSystematic mapping for big data stream processing frameworksen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationda7e013c-bd57-4ea1-bfa8-e2b6b92dd61e
relation.isAuthorOfPublicationbfd1f6fe-b2b5-455f-b781-9916b46d604f
relation.isAuthorOfPublication.latestForDiscoveryda7e013c-bd57-4ea1-bfa8-e2b6b92dd61e
relation.isOrgUnitOfPublicationd86bbe4b-0f69-4303-a6de-c7ec0c515da5
relation.isOrgUnitOfPublicatione0809e2c-77a7-4f04-9cb0-4bccec9395fa
relation.isOrgUnitOfPublication.latestForDiscoveryd86bbe4b-0f69-4303-a6de-c7ec0c515da5

Files

Collections