Models for hyper-converged cloud computing infrastructures planning. (3rd February 2020)

• Record Type: Journal Article
• Authors: Melo, Carlos; Dantas, Jamilson; Maciel, Paulo; Oliveira, Danilo Mendonça; Araujo, Jean; Matos, Rubens; Fé, Iure
• Is Part Of: International journal of grid and utility computing. Volume 11:Number 2(2020)
• Page Start: 196
• Page End: 208
• Publication Date: 2020-02-03
• Subjects: hyper-convergence -- dependability models -- dynamical reliability block diagrams -- SDDC -- DRBD -- virtualisation -- capacity-oriented availability -- deployment cost -- redundancy -- cloud computing -- OpenStack; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

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.