Modeling and analysis of high availability techniques in a virtualized system

Chang, Xiaolin ; Wang, Tianju ; Rodríguez, Ricardo J. (Universidad de Zaragoza) ; Zhang, Zhenjiang

Resumen: Availability evaluation of a virtualized system is critical to the wide deployment of cloud computing services. Time-based, prediction-based rejuvenation of virtual machines (VM) and virtual machine monitors, VM failover and live VM migration are common high-availability (HA) techniques in a virtualized system. This paper investigates the effect of combination of these availability techniques on VM availability in a virtualized system where various software and hardware failures may occur. For each combination, we construct analytic models rejuvenation mechanisms to improve VM availability; (2) prediction-based rejuvenation enhances VM availability much more than time-based VM rejuvenation when prediction successful probability is above 70%, regardless failover and/or live VM migration is also deployed; (3) failover mechanism outperforms live VM migration, although they can work together for higher availability of VM. In addition, they can combine with software rejuvenation mechanisms for even higher availability; (4) and time interval setting is critical to a time-based rejuvenation mechanism. These analytic results provide guidelines for deploying and parameter setting of HA techniques in a virtualized system.

Idioma: Inglés

DOI: 10.1093/comjnl/bxx049

Año: 2017

Publicado en: COMPUTER JOURNAL 61, 2 (2017), 180-198
ISSN: 0010-4620

Factor impacto JCR: 0.792 (2017)

Categ. JCR: COMPUTER SCIENCE, THEORY & METHODS rank: 75 / 103 = 0.728 (2017) - Q3 - T3
Categ. JCR: COMPUTER SCIENCE, SOFTWARE ENGINEERING rank: 85 / 104 = 0.817 (2017) - Q4 - T3
Categ. JCR: COMPUTER SCIENCE, HARDWARE & ARCHITECTURE rank: 47 / 52 = 0.904 (2017) - Q4 - T3
Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 131 / 148 = 0.885 (2017) - Q4 - T3

Factor impacto SCIMAGO: 0.319 - Computer Science (miscellaneous) (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/644869/EU/Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements/DICE
Financiación: info:eu-repo/grantAgreement/ES/MICINN/TIN2014-58457-R
Financiación: info:eu-repo/grantAgreement/ES/UZ/CUD2016-TEC-06

Tipo y forma: Article (PostPrint)

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