Paper Info
Title
Availability analysis of design configurations to compose virtual performance-optimized data center systems in next-generation cloud data centers.
Abstract
Next-generation cloud data centers are based on software-defined data center infrastructures that promote flexibility, automation, optimization, and scalability. The Redfish standard and the Intel Rack Scale Design technology enable software-defined infrastructure and disaggregate bare-metal compute, storage, and networking resources into virtual pools to dynamically compose resources and create virtual performance-optimized data centers (vPODs) tailored to workload-specific demands. This article proposes four chassis design configurations based on Distributed Management Task Force's Redfish industry standard applied to compose vPOD systems, namely, a fully shared design, partially shared homogeneous design, partially shared heterogeneous design, and not shared design; their main difference is based on the used hardware disaggregation level. Furthermore, we propose models that combine reliability block diagram and stochastic Petri net modeling approaches to represent the complexity of the relationship between the pool of disaggregated hardware resources and their power and cooling sources in a vPOD. These four proposed design configurations were analyzed and compared in terms of availability and component's sensitivity indexes by scaling their configurations considering different data center infrastructure. From the obtained results, we can state that, in general, when one increases the hardware disaggregation, availability is improved. However, after a given point, the availability level of the fully shared, partially shared homogeneous, and partially shared heterogeneous configurations remain almost equal, while the not shared configuration is still able to improve its availability.
Year
DOI
Venue
2020
10.1002/spe.2833
SOFTWARE-PRACTICE & EXPERIENCE
Keywords
DocType
Volume
availability,composable systems,next-generation cloud data center,Redfish standard,stochastic models
Journal
50.0
Issue
ISSN
Citations 
6.0
0038-0644
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Daniel Rosendo102.70
Demis Gomes203.04
Guto Leoni Santos3128.85
Leylane Silva400.68
Moreira, A.5165.88
Judith Kelner66216.65
Djamel Sadok737157.81
Glauco Estácio Gonçalves8249.62
Amardeep Mehta911.02
Mattias Wildeman1012.72
Patricia Endo1112125.32