Modeling and characterizing service interference in dynamic infrastructures

Medel, Víctor ; Arronategui, Unai (Universidad de Zaragoza) ; Rana, Omer ; Bañares, José Ángel (Universidad de Zaragoza) ; Tolosana-Calasanz, Rafael (Universidad de Zaragoza)

Resumen: Performance interference can occur when various services are executed over the same physical infrastructure in a cloud system. This can lead to performance degradation compared to the execution of services in isolation. This work proposes a Confirmatory Factor Analysis (CFA)-based model to estimate performance interference across containers, caused by the use of CPU, memory and IO across a number of co-hosted applications. The approach provides resource characterization through human comprehensible indices expressed as time series, so the interference in the entire execution lifetime of a service can be analyzed. Our experiments, based on the combination of real services with different profiles executed in Docker containers, suggest that our model can accurately predict the overall execution time, for different service combinations. The approach can be used by a service designer to identify phases, during the execution life-cycle of a service, that are likely to lead to a greater degree of interference, and to ensure that only complementary services are hosted on the same physical machine. Interference-awareness of this kind will enable more intelligent resource management and scheduling for cloud systems, and may be used to dynamically modify scheduling decisions.

Idioma: Inglés

DOI: 10.1109/ACCESS.2023.3250606

Año: 2023

Publicado en: IEEE Access 11 (2023), 21387-21403
ISSN: 2169-3536

Factor impacto JCR: 3.4 (2023)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 87 / 250 = 0.348 (2023) - Q2 - T2
Categ. JCR: TELECOMMUNICATIONS rank: 47 / 119 = 0.395 (2023) - Q2 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 122 / 353 = 0.346 (2023) - Q2 - T2

Factor impacto CITESCORE: 9.8 - Engineering (all) (Q1) - Materials Science (all) (Q1) - Computer Science (all) (Q1)

Factor impacto SCIMAGO: 0.96 - Engineering (miscellaneous) (Q1) - Materials Science (miscellaneous) (Q1) - Computer Science (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/T35-17D
Financiación: info:eu-repo/grantAgreement/ES/MINECO/PGC2018-099815-B-100

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Arquit.Tecnología Comput. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)