Polos, Rawaa Putros. Gathering multi-dimensional data of scalable container-based cluster for performance analysis. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2021.
Gathering multi-dimensional data of scalable container-based cluster for performance analysis
Abstract:
Data collection is a systematic process of gathering,
monitoring, and analysing specific information to find
out solutions for relevant queries and the evaluation of the
results. Whether the collected data will be used to perform
research on business or academic areas, it allows gaining clear
insights and first-hand knowledge of the research problem. In
this paper, a new framework for gathering multi-dimensional
performance data of a container-based cluster has been proposed
and developed. Our main goal is to provide a systematic approach
for gathering data-set and make it ready-to-use for a business or
research analysis.
The new framework provides the following functions: i) Multidimensional
data collection, centrally performance metrics from
the container-based cluster. iii) Re-structuring the collected data
to facilitate its usage, iv) Pre-processing of the structured data
by applying cleaning operations, v) Systematically storing the
collected data in a public repository to be available for usages.
In this work, Docker Swarm is used to building the cluster and
in each stage, various technologies are utilized to collect, clean,
and publish the data of the running states of the cluster. By using
our framework, collected data can be used to better manage and
monitor the clusters nodes and containers.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2021
Modified:
2024-06-11
Issued:
2024-06-10
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BibliograpyCitation :
In IEEE Computer Society. 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT 2021) (pp.139-145). Los Alamitos, CA : IEEE Computer Society