loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Francisco Cruz ; Fábio Coelho and Rui Oliveira

Affiliation: INESC TEC & Universidade do Minho, Portugal

Keyword(s): Performance, Cloud Computing, NoSQL Databases.

Abstract: Buffer caching mechanisms are paramount to improve the performance of today’s massive scale NoSQL databases. In this work, we show that in fact there is a direct and univocal relationship between the resource usage and the cache hit ratio in NoSQL databases. In addition, this relationship can be leveraged to build a mechanism that is able to estimate resource usage of the nodes composing the NoSQL cluster.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.141.24.134

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Cruz, F.; Coelho, F. and Oliveira, R. (2016). Towards Performance Prediction in Massive Scale Datastores. In Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016) - Volume 1: DataDiversityConvergence; ISBN 978-989-758-182-3; ISSN 2184-5042, SciTePress, pages 371-373. DOI: 10.5220/0005929203710373

@conference{datadiversityconvergence16,
author={Francisco Cruz. and Fábio Coelho. and Rui Oliveira.},
title={Towards Performance Prediction in Massive Scale Datastores},
booktitle={Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016) - Volume 1: DataDiversityConvergence},
year={2016},
pages={371-373},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005929203710373},
isbn={978-989-758-182-3},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016) - Volume 1: DataDiversityConvergence
TI - Towards Performance Prediction in Massive Scale Datastores
SN - 978-989-758-182-3
IS - 2184-5042
AU - Cruz, F.
AU - Coelho, F.
AU - Oliveira, R.
PY - 2016
SP - 371
EP - 373
DO - 10.5220/0005929203710373
PB - SciTePress