'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
—Increased complexity in IT, big data, and advanced
analytical techniques are some of the trends driving demand
for more sophisticated and scalable search technology. Despite
Quality of Service (QoS) being a critical success factor in
most enterprise software service offerings, it is often not a
generic component of the enterprise search software stack. In
this paper, we explore enterprise search engine dependability
and performance using a real-world company architecture and
associated data sourced from an ElasticSearch implementation
on Linknovate.com. We propose a Fault Tree model to assess the
availability and reliability of the Linknovate.com architecture.
The results of the Fault Tree model are fed into a Stochastic Petri
Net (SPN) model to analyze how failures and redundancy impact
application performance of the use case system. Availability and
MTTF were used to evaluate the reliability and throughput was
used to evaluate the performance of the target system. The best
results for all three metrics were returned in scenarios with high
levels of redundancy