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Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator

Author

Listed:
  • Malika Bendechache

    (School of Computing, Dublin City University, Dublin 9, Ireland)

  • Sergej Svorobej

    (School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland)

  • Patricia Takako Endo

    (Caruaru Campus, Universidade de Pernambuco, Recife 50050-240, Pernambuco, Brazil)

  • Adrian Mihai

    (Opening.io Company, Dublin 2, Ireland)

  • Theo Lynn

    (Irish Institute of Digital Business, Dublin City University, Dublin 9, Ireland)

Abstract

Simulation has become an indispensable technique for modelling and evaluating the performance of large-scale systems efficiently and at a relatively low cost. ElasticSearch (ES) is one of the most popular open source large-scale distributed data indexing systems worldwide. In this paper, we use the RECAP Discrete Event Simulator (DES) simulator, an extension of CloudSimPlus, to model and evaluate the performance of a real-world cloud-based ES deployment by an Irish small and medium-sized enterprise (SME), Opening.io. Following simulation experiments that explored how much query traffic the existing Opening.io architecture could cater for before performance degradation, a revised architecture was proposed, adding a new virtual machine in order to dissolve the bottleneck. The simulation results suggest that the proposed improved architecture can handle significantly larger query traffic (about 71% more) than the current architecture used by Opening.io. The results also suggest that the RECAP DES simulator is suitable for simulating ES systems and can help companies to understand their infrastructure bottlenecks under various traffic scenarios and inform optimisation and scalability decisions.

Suggested Citation

  • Malika Bendechache & Sergej Svorobej & Patricia Takako Endo & Adrian Mihai & Theo Lynn, 2021. "Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator," Future Internet, MDPI, vol. 13(4), pages 1-12, March.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:4:p:83-:d:523364
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    References listed on IDEAS

    as
    1. Sirdeshmukh, Deepak & Ahmad, Norita B. & Khan, M. Sajid & Ashill, Nicholas J., 2018. "Drivers of user loyalty intention and commitment to a search engine: An exploratory study," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 71-81.
    2. Sergej Svorobej & Patricia Takako Endo & Malika Bendechache & Christos Filelis-Papadopoulos & Konstantinos M. Giannoutakis & George A. Gravvanis & Dimitrios Tzovaras & James Byrne & Theo Lynn, 2019. "Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges," Future Internet, MDPI, vol. 11(3), pages 1-15, February.
    3. Vuylsteke, Alexander & Wen, Zhong & Baesens, Bart & Poelmans, Jonas, 2010. "Consumers' Search for Information on the Internet: How and Why China Differs from Western Europe," Journal of Interactive Marketing, Elsevier, vol. 24(4), pages 309-331.
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