一种基于PEPA流近似方法的动态自省模型

基金项目:

国家自然科学重大计划基金资助项目(90718003)

国家自然科学基金资助项目(60973027,60373000)

国家“八六三”基金资助项目(2007AA01Z401).

详细信息

A Dynamic Self-reflection Model Based on Fluid Flow Approximation of PEPA

College of Computer and Science Technology, Harbin Engineering University, Harbin 150001, China

摘要: 现有的基于自然语言或框图的自省模型已不能满足系统验证和分析的需求.本文采用流近似方法将PEPA转化为常微分方程组(ODEs),提出了一种基于性能评价进程代数(PEPA)语言的动态自省模型,且具有形式化推理验证和量化分析的功能,避免传统马尔可夫链求解方法状态空间爆炸的问题.分析结果显示,缩减被管理组件检测过程的延迟时间、减小执行指令序列长度对于自省效率的提高具有重要作用.
- 自省 /
- 自律计算 /
- 性能评价进程代数 /
- 常微分方程
Abstract: The existing self-reflection models based on natural language or diagram have not been able to meet the requirements of verification and analysis. The PEPA model is converted into Ordinary Differential Equations (ODEs). A dynamic self-reflection model based on Performance Evaluation Process Algebra (PEPA) which provides an insight into quantitative analysis besides reasoning is proposed to describe the process of selfreflection. Using a fluid flow approximation method to avoid a state-space explosion of Markov chains, a traditional solution method. The analysis results demonstrate that it is important to improve the efficiency of selfreflection by decreasing the latency time of monitor as well as shortening the length of instruction sequences.
- self-reflection /
- autonomic computing /
- PEPA /
- ordinary differential equations