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Optimizing software rejuvenation policy based on CDM for cloud system

机译:基于CDM的云系统软件复兴策略优化

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摘要

The ever-increasing cloud-based systems are suffering progressive performance degradation due to internal accumulated errors and external security attacks. Software rejuvenation is a preventive maintenance policy to solve this problem. However, an ineffective rejuvenation policy usually causes high resource consumption and system cost loss. To guarantee the high availability and minimize the maintenance cost in the cloud-based system, a cost-effective rejuvenation policy is proposed based on cumulative damage model (CDM) in this paper. With our proposal, prior to system failure diagnosis, the system is managed to be rejuvenated either at a predetermined time or at a damage threshold level, whichever occurs first. Further, the system cost rate function is deduced, and an optimal rejuvenation period is derived aiming to minimize the maintenance cost. Experimental results show that the proposed rejuvenation policy is highly effective in term of great reduction on system cost rate.
机译:由于内部累积的错误和外部安全攻击,不断增长的基于云的系统正遭受性能逐步下降的困扰。软件复兴是解决此问题的预防性维护策略。但是,无效的复兴策略通常会导致高资源消耗和系统成本损失。为了保证基于云的系统的高可用性并最小化维护成本,本文提出了一种基于累积损伤模型(CDM)的高性价比的复兴策略。根据我们的建议,在系统故障诊断之前,可以在预定的时间或以损坏阈值水平(以先到者为准)使系统恢复活力。此外,推导系统成本率函数,并得出旨在使维护成本最小化的最佳复兴时期。实验结果表明,所提出的修复策略在大大降低系统成本率方面非常有效。

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