loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Xuesong Peng and Barbara Pernici

Affiliation: Politecnico di Milano, Italy

Keyword(s): Monitoring Data, Data Reduction, Time-series Prediction, Data Center.

Abstract: Nowadays, in order to observe and control data centers in an optimized way, people collect a variety of monitoring data continuously. Along with the rapid growth of data centers, the increasing size of monitoring data will become an inevitable problem in the future. This paper proposes a correlation-based reduction method for streaming data that derives quantitative formulas between correlated indicators, and reduces the sampling rate of some indicators by replacing them with formulas predictions. This approach also revises formulas through iterations of reduction process to find an adaptive solution in dynamic environments of data centers. One highlight of this work is the ability to work on upstream side, i.e., it can reduce volume requirements for data collection of monitoring systems. This work also carried out simulated experiments, showing that our approach is capable of data reduction under typical workload patterns and in complex data centers.

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 18.227.24.209

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:
Peng, X. and Pernici, B. (2016). Correlation-Model-Based Reduction of Monitoring Data in Data Centers. In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS; ISBN 978-989-758-184-7; ISSN 2184-4968, SciTePress, pages 395-405. DOI: 10.5220/0005794803950405

@conference{smartgreens16,
author={Xuesong Peng. and Barbara Pernici.},
title={Correlation-Model-Based Reduction of Monitoring Data in Data Centers},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS},
year={2016},
pages={395-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005794803950405},
isbn={978-989-758-184-7},
issn={2184-4968},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS
TI - Correlation-Model-Based Reduction of Monitoring Data in Data Centers
SN - 978-989-758-184-7
IS - 2184-4968
AU - Peng, X.
AU - Pernici, B.
PY - 2016
SP - 395
EP - 405
DO - 10.5220/0005794803950405
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic