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Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach

Publication ,  Journal Article
Bai, J; Chang, X; Ning, G; Zhang, Z; Trivedi, KS
Published in: IEEE Transactions on Cloud Computing
January 1, 2022

With the rapid and wide development and deployment of system virtualization, service availability analysis has become increasingly important in a virtualized system (VS) which suffers from software aging. Software rejuvenation techniques can be applied to improve service availability but its effectiveness depends on the rejuvenation policy, which defines when and where to rejuvenate, and which rejuvenation technique to be triggered. This article aims to analyze the optimal inspection time interval for maximizing application service (AS) availability under a three-level rejuvenation policy, in which rejuvenation techniques are deployed at each level, namely, AS, virtual machine (VM), and virtual machine monitor (VMM) levels. We first apply Markov regenerative process to construct an analytical model for the VS. Experiments of injecting memory leaks are conducted to measure aging-related parameters. Furthermore, numerical analysis is carried out to study the quantitative relationship between AS availability and inspection time interval, and determine the approximate optimal inspection time interval.

Duke Scholars

Published In

IEEE Transactions on Cloud Computing

DOI

EISSN

2168-7161

Publication Date

January 1, 2022

Volume

10

Issue

3

Start / End Page

2118 / 2130

Related Subject Headings

  • 4606 Distributed computing and systems software
  • 0806 Information Systems
  • 0805 Distributed Computing
 

Citation

APA
Chicago
ICMJE
MLA
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Bai, J., Chang, X., Ning, G., Zhang, Z., & Trivedi, K. S. (2022). Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach. IEEE Transactions on Cloud Computing, 10(3), 2118–2130. https://doi.org/10.1109/TCC.2020.3028648
Bai, J., X. Chang, G. Ning, Z. Zhang, and K. S. Trivedi. “Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach.” IEEE Transactions on Cloud Computing 10, no. 3 (January 1, 2022): 2118–30. https://doi.org/10.1109/TCC.2020.3028648.
Bai J, Chang X, Ning G, Zhang Z, Trivedi KS. Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach. IEEE Transactions on Cloud Computing. 2022 Jan 1;10(3):2118–30.
Bai, J., et al. “Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach.” IEEE Transactions on Cloud Computing, vol. 10, no. 3, Jan. 2022, pp. 2118–30. Scopus, doi:10.1109/TCC.2020.3028648.
Bai J, Chang X, Ning G, Zhang Z, Trivedi KS. Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach. IEEE Transactions on Cloud Computing. 2022 Jan 1;10(3):2118–2130.

Published In

IEEE Transactions on Cloud Computing

DOI

EISSN

2168-7161

Publication Date

January 1, 2022

Volume

10

Issue

3

Start / End Page

2118 / 2130

Related Subject Headings

  • 4606 Distributed computing and systems software
  • 0806 Information Systems
  • 0805 Distributed Computing