Title: Models for hyper-converged cloud computing infrastructures planning
Authors: Carlos Melo; Jamilson Dantas; Paulo Maciel; Danilo Mendonça Oliveira; Jean Araujo; Rubens Matos; Iure Fé
Addresses: Informatics Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil ' Informatics Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil ' Informatics Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil ' Informatics Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil ' Academic Unit of Garanhuns, Federal Rural University of Pernambuco, Garanhuns, Pernambuco, Brazil ' Federal Institute of Education Science and Technology of Sergipe, Lagarto, Sergipe, Brazil ' Brazilian Army, Picos, Piauí, Brazil
Abstract: The Data Centre concept has evolved, mainly due to the need to reduce expenses with the required physical space to store, provide and maintain large computational infrastructures. The Software-Defined Data Centre (SDDC) is a result of this evolution. Through SDDC, any service can be hosted by virtualising more reliable and easier-to-keep hardware resources. Nowadays, many services and resources can be provided in a single rack, or even a single machine, with similar availability, considering the deployment costs of silo-based environments. One of the ways to apply the SDDC into a data centre is through hyper-convergence. Among the main contributions of this paper are the behavioural models developed for availability and capacity-oriented availability evaluation of silo-based, converged and hyper-converged cloud computing infrastructures. The obtained results may help stakeholders to select between converged and hyper-converged environments, due to their similar availability but with the particularity of having lower deployment costs.
Keywords: hyper-convergence; dependability models; dynamical reliability block diagrams; SDDC; DRBD; virtualisation; capacity-oriented availability; deployment cost; redundancy; cloud computing; OpenStack.
International Journal of Grid and Utility Computing, 2020 Vol.11 No.2, pp.196 - 208
Received: 28 Apr 2018
Accepted: 22 Dec 2018
Published online: 03 Mar 2020 *