Proactive replication of dynamic linked data for scalable RDF stream processing

Sejin Chun, Jooik Jung, Xiongnan Jin, Seungjun Yoon, Kyong Ho Lee

Research output: Contribution to journalConference article

Abstract

In this paper, we propose a scalable method of proactively replicating a subset of remote datasets for RDF Stream Processing. Our solution achieves a fast query processing by maintaining the replicated data up-to-date before query evaluation. To construct the replication process effectively, we present an update estimation model to handle the changes in updates over time. With the update estimation model, we re-construct the replication process in response to the outdated data. Finally, we conduct exhaustive tests with a real-world dataset to verify our solution.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1690
Publication statusPublished - 2016
Event2016 Posters and Demonstrations Track, ISWC P and D 2016 - Kobe, Japan
Duration: 2016 Oct 19 → …

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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