Supported by the National Natural Science Foundation of China under Grant Nos.90718003, 60373000, 60973027 (国家自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2007AA01Z401 (国家高技术研究发展计划(863))
将现有入侵容忍、自毁技术与自律计算相结合,提出了一种基于SM-PEPA(semi-Markov performance evaluation process algebra)的关键任务系统自律可信性模型以支持形式化分析和推理.该模型具有一定程度的自管理能力,采用分级处理的方式应对各种程度的可信性威胁,满足了关键任务系统对可信性的特殊需求.在此基础上,从稳态概率角度提出了一种自律可信性度量方法.最后,结合具体实例对模型参数对自律可信性的影响进行了初步分析.实验结果表明,增大关键任务系统可信性威胁检测率和自恢复成功率,可在较大范围内提高系统的自律可信 特性.
In this paper, the existing intrusion tolerance and self-destruction technology are integrated into autonomic computing in order to construct an autonomic dependability model based on SM-PEPA (semi-Markov performance evaluation process algebra) which is capable of formal analysis and verification. It can hierarchically anticipate Threats to dependability (TtD) at different levels in a self-management manner to satisfy the special requirements for dependability of mission-critical systems. Based on this model, a quantification approach is proposed on the view of steady-state probability to evaluate autonomic dependability. Finally, this paper analyzes the impacts of parameters of the model on autonomic dependability in a case study, and the experimental results demonstrate that improving the detection rate of TtD as well as the successful rate of self-healing will greatly increase the autonomic dependability.