MonARCh: an actor based architecture for dynamic linked data monitoring

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dc.authoridYönyül, Burak/0000-0001-7096-8031
dc.authoridAlatlı, Oylum/0000-0001-5361-1305
dc.contributor.authorYonyul, Burak
dc.contributor.authorAlatl, Oylum
dc.contributor.authorErdur, Riza Cenk
dc.date.accessioned2024-08-31T07:50:13Z
dc.date.available2024-08-31T07:50:13Z
dc.date.issued2024
dc.departmentEge Üniversitesien_US
dc.description.abstractMonitoring the data sources for possible changes is an important consumption requirement for applications running in interaction with the Web of Data. In this article, MonARCh which is an architecture for monitoring the result changes of registered SPARQL queries in the Linked Data environment, is proposed. MonARCh can be comprehended as a publish/subscribe system in the general sense. However, it differs in how communication with the data sources is realized. Data sources in the Linked Data environment do not publish the changes in the data. MonARCh provides the necessary communication infrastructure between the data sources and the consumers for the notification of changes. Users subscribe SPARQL queries to the system which are then converted to federated queries. MonARCh periodically checks for updates by re-executing SERVICE clauses and notifying users in case of any result change. In addition, to provide scalability, MonARCh takes the advantage of concurrent computation of the actor model. The parallel join algorithm utilized speeds up query execution and result generation processes. The design science methodology is used during the design, implementation and evaluation of the architecture. When compared to the literature MonARCh meets all the sufficient requirements from the linked data monitoring and state of the art perspectives while having many outstanding features from both points of view. The evaluation results show that even while working under the limited two-node cluster setting MonARCh could reach from 300 to 25,000 query monitoring capacity according to the diverse query selectivities executed within our test bench.en_US
dc.identifier.doi10.7717/peerj-cs.2133
dc.identifier.issn2376-5992
dc.identifier.pmid39145249en_US
dc.identifier.scopus2-s2.0-85199035837en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.7717/peerj-cs.2133
dc.identifier.urihttps://hdl.handle.net/11454/105151
dc.identifier.volume10en_US
dc.identifier.wosWOS:001268140800003en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherPeerj Incen_US
dc.relation.ispartofPeerj Computer Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240831_Uen_US
dc.subjectQuery Monitoringen_US
dc.subjectSparqlen_US
dc.subjectLinked Dataen_US
dc.subjectScalabilityen_US
dc.subjectDistributed And Parallel Processingen_US
dc.subjectConcurrent Computationen_US
dc.subjectPublish/Subscribe Architectureen_US
dc.subjectPush-Pull Modelen_US
dc.subjectActor Modelen_US
dc.titleMonARCh: an actor based architecture for dynamic linked data monitoringen_US
dc.typeArticleen_US

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