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Benchmarking Tool for Modern Distributed Stream Processing Engines

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dc.contributor.authorHanif, Muhammad-
dc.contributor.authorYoon, Hyeongdeok-
dc.contributor.authorLee, Choonhwa-
dc.date.accessioned2022-07-10T14:53:46Z-
dc.date.available2022-07-10T14:53:46Z-
dc.date.created2021-05-13-
dc.date.issued2019-01-
dc.identifier.issn1976-7684-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/148477-
dc.description.abstractThere is an upsurge in the usage and adaptation of streaming applications in the recent years by both industry and academia. At the core of these applications is streaming data processing engines that perform resource management and allocation in order to support continuous track of queries over distributed data streams. Several stream processing engines exists to handle these distributed streaming applications. In this paper, we present different challenges of the stream processing systems, in particular to stateful operators and implement Linear Road benchmark to examine the characteristic and performance metrics of the streaming system, in particular Apache Flink. Furthermore, we examine that Apache Flink can be used as a core for an efficient Linear Road application implementation for distributed environments without breaching the SLA requirements of the application.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE Computer Society-
dc.titleBenchmarking Tool for Modern Distributed Stream Processing Engines-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Choonhwa-
dc.identifier.doi10.1109/ICOIN.2019.8718106-
dc.identifier.scopusid2-s2.0-85066761823-
dc.identifier.wosid000475888000074-
dc.identifier.bibliographicCitationInternational Conference on Information Networking, v.2019-January, pp.393 - 395-
dc.relation.isPartOfInternational Conference on Information Networking-
dc.citation.titleInternational Conference on Information Networking-
dc.citation.volume2019-January-
dc.citation.startPage393-
dc.citation.endPage395-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordPlusAcoustic streaming-
dc.subject.keywordPlusCloud computing-
dc.subject.keywordPlusData handling-
dc.subject.keywordPlusDistributed computer systems-
dc.subject.keywordPlusDistributed parameter control systems-
dc.subject.keywordPlusEngines-
dc.subject.keywordPlusnformation management-
dc.subject.keywordPlusRoads and streets-
dc.subject.keywordPlusDistributed data streams-
dc.subject.keywordPlusDistributed environments-
dc.subject.keywordPlusDistributed stream processing-
dc.subject.keywordPlusDistributed streaming-
dc.subject.keywordPlusStream processing engines-
dc.subject.keywordPlusStream processing systems-
dc.subject.keywordPlusStreaming applications-
dc.subject.keywordPlusStreaming data processing-
dc.subject.keywordPlusBenchmarking-
dc.subject.keywordAuthorBenchmarking-
dc.subject.keywordAuthorCloud Computing-
dc.subject.keywordAuthorDistributed Computing-
dc.subject.keywordAuthorSLA-
dc.subject.keywordAuthorStreaming-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/8718106-
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