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Cloud broker proposal based on multicriteria decision‐making and virtual infrastructure migration.

Authors :
Rodrigues, Leonardo R.
Cardoso, Euclides
Alves, Omir C.
Redígolo, Fernando F.
Pillon, Maurício A.
Miers, Charles C.
Koslovski, Guilherme P.
Source :
Software: Practice & Experience; Sep2019, Vol. 49 Issue 9, p1331-1351, 21p
Publication Year :
2019

Abstract

Summary: The adoption of infrastructure as a Service (IaaS) is a reality for academic, industrial, and governmental institutions. Cloud tenants request dynamically provisioned virtual infrastructures (VIs) tailored to their application requirements, detailing not only the virtual compute/storage resources but also the network components, topology, and services. The creation of a large number of cloud providers came along with the widespread use of VIs. The selection of an appropriate provider is a challenging task due to the diversity of the IaaS market and formally is a multicriteria analysis (NP‐hard). Notwithstanding the provider selection complexity, the mobility of VI‐hosted applications is limited due to the optimization anchors introduced by providers. Although the existing IaaS cloud brokers can indicate a hosting provider, they lack on conceptual and technical skills to migrate a VI and all its internal components between providers. This work enhances the state‐of‐the‐art on IaaS cloud brokerage by proposing virtual infrastructure multicriteria allocation and migration–based broker (VIMAM), which performs a multicriteria analysis of providers and VI migration. VIMAM is driven by an analytic hierarchy process (AHP) to select an IaaS provider, offering a set of predefined weighting schemas to represent distinct tenant perspectives. Moreover, to migrate a VI, VIMAM takes into account the virtual machines, containers, switches, and other topology elements. In addition to discussing the AHP ranking weights and frequency of providers selection, the experimental analysis details the implementation of an OpenStack and Docker–based prototype for VI migration. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00380644
Volume :
49
Issue :
9
Database :
Complementary Index
Journal :
Software: Practice & Experience
Publication Type :
Academic Journal
Accession number :
137988093
Full Text :
https://doi.org/10.1002/spe.2723