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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.

References

  1. Dell’Aglio, D., Le Phuoc, D., Le-Tuan, A., Intizar Ali, M., Calbimonte, J.-P.: On a web of data streams (2017)

    Google Scholar 

  2. Anicic, D., Fodor, P., Rudolph, S., Stojanovic, N.: EP-SPARQL: a unified language for event processing and stream reasoning. In: Proceedings of the 20th International Conference on World Wide Web, WWW 2011, Hyderabad, India, 28 March–1 April 2011, pp. 635–6441 (2011)

    Google Scholar 

  3. Dell’Aglio, D., Calbimonte, J.-P., Balduini, M., Corcho, O., Della Valle, E.: On correctness in RDF stream processor benchmarking. In: Alani, H., et al. (eds.) ISWC 2013. LNCS, vol. 8219, pp. 326–342. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41338-4_21

    Chapter  Google Scholar 

  4. de Almeida, V.P., Bhowmik, S., Lima, G.F., Endler, M., Rothermel, K.: DSCEP: an infrastructure for decentralized semantic complex event processing. In: IEEE International Conference on Big Data, Big Data 2020, Atlanta, GA, USA, 10–13 December 2020, pp. 391–398 (2020)

    Google Scholar 

  5. Puiu, D., et al.: CityPulse: large scale data analytics framework for smart cities. IEEE Access 4, 1086–1108 (2016)

    Google Scholar 

  6. Ali, M.I., Gao, F., Mileo, A.: CityBench: a configurable benchmark to evaluate RSP engines using smart city datasets. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9367, pp. 374–389. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25010-6_25

    Chapter  Google Scholar 

  7. Calbimonte, J.-P., Corcho, O., Gray, A.J.G.: Enabling ontology-based access to streaming data sources. In: Patel-Schneider, P.F., et al. (eds.) ISWC 2010. LNCS, vol. 6496, pp. 96–111. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17746-0_7

    Chapter  Google Scholar 

  8. Gillani, S., Zimmermann, A., Picard, G., Laforest, F.: A query language for semantic complex event processing: syntax, semantics and implementation. Semant. Web 10(1), 53–93 (2019)

    Google Scholar 

  9. Zhang, Y., Duc, P.M., Corcho, O., Calbimonte, J.-P.: SRBench: a streaming RDF/SPARQL benchmark. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012. LNCS, vol. 7649, pp. 641–657. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35176-1_40

    Chapter  Google Scholar 

  10. Rinne, M., Nuutila, E., Torma, S., Glimm, B., Huynh, D.: INSTANS: high-performance event processing with standard RDF and SPARQL. In: Proceedings of the ISWC 2012 Posters and Demonstrations Track, Boston, USA, 11–15 November 2012, vol. 914 (2012)

    Google Scholar 

  11. Calvaresi, D., Calbimonte, J.-P.: Real-time compliant stream processing agents for physical rehabilitation. Sensors 20(3), 746 (2020)

    Google Scholar 

  12. Barbieri, D.F., Braga, D., Ceri, S., Valle, E.D., Grossniklaus, M.: C-SPARQL: a continuous query language for RDF data streams. Int. J. Semant. Comput. 4(1), 3–25 (2010)

    Article  Google Scholar 

  13. Le-Phuoc, D., Nguyen Mau Quoc, H., Le Van, C., Hauswirth, M.: Elastic and Scalable Processing of Linked Stream Data in the Cloud. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., Janowicz, K. (eds.) ISWC 2013. LNCS, vol. 8218, pp. 280–297. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41335-3_18

    Chapter  Google Scholar 

  14. Le-Phuoc, D., Dao-Tran, M., Pham, M.-D., Boncz, P., Eiter, T., Fink, M.: Linked stream data processing engines: facts and figures. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012. LNCS, vol. 7650, pp. 300–312. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35173-0_20

    Chapter  Google Scholar 

  15. Greenwood, D.A.P., Lyell, M., Mallya, A.U., Suguri, H.: The IEEE FIPA approach to integrating software agents and web services. In: 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), Honolulu, Hawaii, USA, 14–18 May 2007, p. 276 (2007)

    Google Scholar 

  16. Ren, X., et al.: Strider: an adaptive, inference-enabled distributed RDF stream processing engine. Proc. VLDB Endow. 10(12), 1905–1908 (2017)

    Google Scholar 

  17. Le-Phuoc, D., Dao-Tran, M., Xavier Parreira, J., Hauswirth, M.: A native and adaptive approach for unified processing of linked streams and linked data. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 370–388. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25073-6_24

    Chapter  Google Scholar 

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Author information

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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Corresponding author

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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