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
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