This paper focuses on the generation of stochastic models for dependability and performability analysis, through mechanisms for the automatic replication of template models when identity of replicas cannot be anonymous. The major objective of this work is to support the modeler in selecting the most appropriate replication mechanism, given the characteristics of the system under analysis. To this purpose, three most used solutions to identity-aware replication are considered and a formal framework to allow representing them in a consistent way is first defined. Then, a comparison of their behavior is extensively carried out, with focus on efficiency, both from a theoretical perspective and from a quantitative viewpoint. For the latter, a specific implementation of the considered replication mechanisms in the Möbius modeling environment and a case study representative of realistic interconnected infrastructures are developed.

本文通过当副本的身份不能匿名时自动复制模板模型的机制，着重于用于可靠性和性能分析的随机模型的生成。鉴于正在分析的系统的特性，这项工作的主要目的是支持建模者选择最合适的复制机制。为此，考虑了三种最常用的身份识别复制解决方案，并首先定义了一个允许以一致方式表示它们的正式框架。然后，从理论角度和定量角度广泛地比较了它们的行为，并着重于效率。对于后者，