EXTENDED SOFTWARE AGING AND REJUVENATION MODEL FOR ANDROID OPERATING SYSTEM CONSIDERING DIFFERENT AGING LEVELS AND REJUVENATION PROCEDURE TYPES

V. Yakovyna, B. Uhrynovskyi
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引用次数: 2

Abstract

A complex model based on Continuous-Time Markov Chains is proposed, which combines an extended aging and rejuvenation model taking into account different aging levels and a model of mobile device usage activity. A graph of states and transitions is constructed, which describes the proposed model without taking into account mobile device usage activity, and taking it into account. A system of Kolmogorov – Chapman differential equations is written on the basis of the states graph. A set of test simulations for conducting experimental calculations of the model and analysis of results is described. A system of differential equations for each simulation is calculated using the 4th order Runge-Kutta method. The analysis of simulations with recovery after aging-related failure and without recovery allowed to formulate the main objectives of the rejuvenation procedure in the proposed model to improve the user experience. Analysis of different rejuvenation planning strategies indicates that the most effective approach is to perform rejuvenation in the “Aging” state, when the device is already aging, but it is not yet a state with a high probability of aging-related failure. Analysis of simulations with warm and cold rejuvenation shows that this factor affects the results of the model calculation, and the application of one or another approach depends on the aging conditions and the mobile device usage activity. The developed model based on the Markov chain can be used to predict the optimal time of the rejuvenation procedure. In addition, the model considers both cold and warm rejuvenation. Further studies which take into account the real data and aging conditions are needed for proposed aging and rejuvenation model.
考虑不同老化程度和再生程序类型的android操作系统扩展软件老化与再生模型
提出了一种基于连续时间马尔可夫链的复杂模型,该模型结合了考虑不同老化水平的扩展老化和再生模型和移动设备使用活动模型。构造了一个状态和转换图,它描述了在不考虑移动设备使用活动的情况下提出的模型,并将其考虑在内。在状态图的基础上,建立了一个Kolmogorov - Chapman微分方程组。描述了一组用于进行模型实验计算和结果分析的试验模拟。用四阶龙格-库塔法计算了每个模拟的微分方程组。通过对衰老相关故障后恢复和不恢复的模拟分析,可以制定拟议模型中恢复过程的主要目标,以改善用户体验。对不同的返老还老规划策略进行分析表明,最有效的方法是在“老化”状态下进行返老还老,此时设备已经老化,但还不是老化失效概率高的状态。冷热再生和热再生的仿真分析表明,该因素会影响模型的计算结果,采用哪种方法取决于老化条件和移动设备的使用活动。所建立的基于马尔可夫链的模型可用于预测返老还童的最佳时间。此外,该模型考虑了冷回春和暖回春。提出的衰老与返老还童模型需要进一步的研究,考虑到实际数据和老化条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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