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Estimating Periodic Software Rejuvenation Schedules under Discrete-Time Operation Circumstance

机译:离散时间操作环境下的定期软件更新计划估算

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摘要

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider periodic software rejuvenation models based on the expected cost per unit time in the steady state under discrete-time operation circumstance. By applying the discrete renewal reward processes, we describe the stochastic behavior of a telecommunication billing application with a degradation mode, and determine the optimal periodic software rejuvenation schedule minimizing the expected cost. Similar to the earlier work by the same authors, we develop a statistically non-parametric algorithm to estimate the optimal software rejuvenation schedule, by applying the discrete total time on test concept. Numerical examples are presented to estimate the optimal software rejuvenation schedules from the simulation data. We discuss the asymptotic behavior of estimators developed in this paper.
机译:软件复兴是一种预防性的主动解决方案,对于抵消软件老化现象特别有用。在本文中,我们考虑基于离散时间运行情况下稳态下每单位时间的预期成本的周期性软件更新模型。通过应用离散的续订奖励过程,我们以降级模式描述了电信计费应用程序的随机行为,并确定了使预期成本最小化的最佳周期性软件更新计划。与同一作者的早期工作类似,我们通过在测试概念上应用离散的总时间,开发了一种统计上非参数的算法来估计最佳的软件复兴计划。给出了数值示例,以根据仿真数据估算最佳的软件更新计划。我们讨论本文开发的估计量的渐近行为。

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