AN ADAPTIVE COST-BASED SOFTWARE REJUVENATION SCHEME WITH NONPARAMETRIC PREDICTIVE INFERENCE APPROACH

• Rinsaka Koichiro

  Kobe Gakuin University

• Dohi Tadashi

  Hiroshima University

Abstract

This paper proposes an approach to estimate an optimal software rejuvenation schedule minimizing an expected total software cost per unit time. Based on a non-parametric predictive inference (NPI) approach, we derive the upper and lower bounds of the predictive expected software cost via the predictive survival function from system failure time data, and characterize an adaptive cost-based software rejuvenation policy, from the system failure time data with a right-censored observation. In simulation experiments, it is shown that our NPI-based approach is quite useful to predict the optimal software rejuvenation time.

Journal

• Journal of the Operations Research Society of Japan

  Journal of the Operations Research Society of Japan 60 (4), 461-478, 2017

  The Operations Research Society of Japan

Keywords

• Reliability
• software rejuvenation
• software aging
• statistical estimation
• adaptive policy
• non-parametric predictive inference
• software cost model

Details

• CRID: 1390001204113249792
• NII Article ID: 130006182214
• NII Book ID: AA00703935
• DOI: 10.15807/jorsj.60.461
• ISSN: 21888299
• ISSN: 04534514
• NDL BIB ID: 028595256
• Web Site: http://id.ndl.go.jp/bib/028595256
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I028595256
• Web Site: https://www.jstage.jst.go.jp/article/jorsj/60/4/60_461/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed