摘要
在需要长期运行的系统中,软件老化是一种常见的现象,现有基于时序分析的软件老化评估方法,大多基于简单的自回归或ARMA模型,没有充分考虑软件老化关键指标的非平稳性、季节性等特征。该文提出一种基于乘积季节ARIMA模型的软件老化评估方法。并通过实验表明,该方法能够较好地拟合季节性负载系统的软件老化趋势,并能做出准确的预测以支撑软件再生。
Software aging is a common phenomenon in a system that needs long-term operation. The existing analysis methods based on time series analysis mainly focus on autoregressive moving average （ARMA） models, not fully considered the seasonality or non-stationarity of the key indicators about software aging. This paper proposes a new software aging evaluation method based on seasonal autoregressive integrated moving average （ARIMA） model. The experimental results show that the method can well fit the software aging trend of seasonal load systems, and can achieve accurate prediction for supporting software rejuvenation.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2017年第3期583-587,611,共6页
Journal of University of Electronic Science and Technology of China
基金
国家973重点基础研究发展规划项目(2011CB302605)
国家科技支撑计划(2012BAH47B04)
关键词
乘积季节模型
软件老化
软件再生
时序分析
multiplicative seasonal model
software aging
software rejuvenation
time series analysis
