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A Multi-agent Based Framework for RDF Stream Processing

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Advanced Information Networking and Applications (AINA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 449))

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Abstract

When a large amount of data is generated from multiple, heterogeneous and continuous data streams, the need for continuous processing and on-the-fly consumption of the overwhelming flow of data is crucial. In this context, the W3C RDF Stream Processing (RSP) Community Group has defined a common model for continuous querying RDF Streams, giving rise to a plethora of RSP engines. However, their main limitation is that, depending on the application queries, one RSP engine may be more appropriate than another, or multiple engines are required to address complex queries. In this paper, we propose a multi-agent based framework for distributed continuous processing that gives the opportunity to use several RSP engines in the same framework in order to benefit from their advantages and to offer the possibility to use them at the same time or in a sequence to answer complex queries. A preliminary experimental evaluation with a real-world benchmark shows promising results when compared to an existing work.

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Notes

  1. 1.

    C-SPARQL: A Continuous Query Language For RDF Data Streams.

  2. 2.

    CQELS: Continuous Query Evaluation over Linked Streams.

  3. 3.

    http://www.insight-centre.org/dataset/SampleEventService#Query2.

  4. 4.

    Due to space constraint, the full query is available on Github link.

  5. 5.

    https://github.com/anonymSma/sma_processing.

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Authors and Affiliations

  1. Samovar, Télécom SudParis, Institut Polytechnique de Paris, 19 place Marguerite Perey, 91120, Palaiseau, France

    Wafaa Mebrek & Amel Bouzeghoub

  2. EEDIS, Djillali Liabes University of Sidi Bel Abbes, Sidi Bel Abbes, Algeria

    Wafaa Mebrek

Authors
  1. Wafaa Mebrek
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  2. Amel Bouzeghoub
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Correspondence to Amel Bouzeghoub .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Farookh Hussain

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Mebrek, W., Bouzeghoub, A. (2022). A Multi-agent Based Framework for RDF Stream Processing. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-030-99584-3_45

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