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Modelling and simulation of ElasticSearch using CloudSim

Bendechache, Malika orcid logoORCID: 0000-0003-0069-1860, Svorobej, Sergej orcid logoORCID: 0000-0001-8900-8700, Takako Endo, Patricia orcid logoORCID: 0000-0002-9163-5583, Noya Mario, Manuel, Ares, M. Eduardo orcid logoORCID: 0000-0003-3807-5692, Byrne, James orcid logoORCID: 0000-0002-9260-6020 and Lynn, Theo orcid logoORCID: 0000-0001-9284-7580 (2019) Modelling and simulation of ElasticSearch using CloudSim. In: IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), 7-9 Oct 2019, Cosenza, Italy. ISBN 978-1-7281-2923-5

Abstract
Simulation can be a powerful technique for evaluating the performance of large-scale cloud computing services in a relatively low cost, low risk and time-sensitive manner. Largescale data indexing, distribution and management is complex to analyse in a timely manner. In this paper, we extend the CloudSim cloud simulation framework to model and simulate a distributed search engine architecture and its workload characteristics. To test the simulation framework, we develop a model based on a real-world ElasticSearch deployment on Linknovate.com. An experimental evaluation of the framework, comparing simulated and actual query response time, precision and resource utilisation, suggests that the proposed framework is capable of predicting performance at different scales in a precise, accurate and efficient manner. The results can assist ElasticSearch users to manage their scalability and infrastructure requirements
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:ElasticSearch; CloudSim; Cloud; Workload; Query; Modelling; search engine
Subjects:Computer Science > Computer simulation
Computer Science > Information storage and retrieval systems
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: DS-RT '19: Proceedings of the 23rd IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications. 1. IEEE. ISBN 978-1-7281-2923-5
Publisher:IEEE
Official URL:http://dx.doi.org/10.1109/DS-RT47707.2019.8958653
Copyright Information:© 2019 The Authors
Funders:European Union’s Horizon 2020 research and innovation programme under grant agreement No. 732667 (RECAP).
ID Code:24593
Deposited On:11 Jun 2020 10:10 by Malika Bendechache . Last Modified 26 Nov 2020 17:20
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