Performance Modeling in Predictable Cloud Computing

Riccardo Mancini, Tommaso Cucinotta, Luca Abeni

2020

Abstract

This paper deals with the problem of performance stability of software running in shared virtualized infrastructures. The focus is on the ability to build an abstract performance model of containerized application components, where real-time scheduling at the CPU level, along with traffic shaping at the networking level, are used to limit the temporal interferences among co-located workloads, so as to obtain a predictable distributed computing platform. A model for a simple client-server application running in containers is used as a case-study, where an extensive experimental validation of the model is conducted over a testbed running a modified OpenStack on top of a custom real-time CPU scheduler in the Linux kernel.

Paper Citation

in Harvard Style

Mancini R., Cucinotta T. and Abeni L. (2020). Performance Modeling in Predictable Cloud Computing.In Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-424-4, pages 69-78. DOI: 10.5220/0009349400690078

in Bibtex Style

@conference{closer20,
author={Riccardo Mancini and Tommaso Cucinotta and Luca Abeni},
title={Performance Modeling in Predictable Cloud Computing},
booktitle={Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2020},
pages={69-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009349400690078},
isbn={978-989-758-424-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Performance Modeling in Predictable Cloud Computing
SN - 978-989-758-424-4
AU - Mancini R.
AU - Cucinotta T.
AU - Abeni L.
PY - 2020
SP - 69
EP - 78
DO - 10.5220/0009349400690078