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Analysis of an optimal stopping problem for software rejuvenation in a deteriorating job processing system

机译:不断恶化的作业处理系统中软件更新的最佳停止问题分析

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摘要

Software rejuvenation is the proactive maintenance operation for software systems that experience software aging causing degradations in system performance and reliability. The normal system performance can be recovered by software rejuvenation, which restarts the software system to clear all the internal error states due to software aging. Since software rejuvenation drops all the jobs in the system, a trigger for software rejuvenation needs to be carefully determined in consideration of such costs. In this paper, we theoretically derive the optimal policy that minimizes the cost of decision for software rejuvenation in a deteriorating job processing system, which is modeled as an M/M/1 queue with infinite buffer size. In our model, the number of queued jobs is used to represent the system state and the decision of rejuvenation is made upon the completion of a foreground job. We formulate the problem as an optimal stopping problem to analytically derive the optimal policy for the rejuvenation decision. The analytical results show that the optimal stopping policy is determined by the service degradation rate, the costs of dropped jobs and delayed jobs, and it does not depend on the number of queued jobs. This indicates that whether to trigger rejuvenation can be decided immediately when the system confirms the level of service degradation, regardless of the number of queued jobs at that time instant. (C) 2017 Elsevier Ltd. All rights reserved.
机译:对于那些经历了软件老化,导致系统性能和可靠性下降的软件系统,软件复兴是一种主动的维护操作。可以通过软件恢复活力来恢复正常的系统性能,重新启动软件系统可以清除由于软件老化而导致的所有内部错误状态。由于软件更新会丢弃系统中的所有工作,因此需要在考虑此类成本的情况下仔细确定软件更新的触发条件。在本文中,我们从理论上推导了一种最佳策略,该策略可以将不断恶化的作业处理系统中软件更新的决策成本降至最低,该策略被建模为具有无限缓冲区大小的M / M / 1队列。在我们的模型中,排队作业的数量用于表示系统状态,并且在完成前台作业后做出恢复活力的决定。我们将该问题公式化为最佳停止问题,以分析得出复兴决策的最佳策略。分析结果表明,最佳停止策略由服务降级率,丢包和延迟作业的成本决定,并且不取决于排队的作业数。这表明,当系统确认服务质量下降的级别时,可以立即决定是否触发恢复活力,而与当时排队的作业数量无关。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Reliability Engineering & System Safety》 |2017年第12期|128-135|共8页
  • 作者

    Machida Fumio; Miyoshi Naoto;

  • 作者单位

    Tokyo Inst Technol, Dept Math & Comp Sci, Tokyo, Japan;

    Tokyo Inst Technol, Dept Math & Comp Sci, Tokyo, Japan;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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