Modeling and Analyzing Self-Adaptive Systems with Context Petri Nets

Abstract

The development of self-adaptive systems requires the definition of the parts of the system that will be adapted, when such adaptations will take place, and how these adaptations will interact with each other. However, foreseeing all possible adaptations and their interactions is a difficult task, opening the possibility to inconsistencies or erroneous system behavior. To avoid inconsistencies, self adaptive systems require a sound programming model that allows to reason about the correctness of the system in spite of its dynamic reconfigurations. This paper presents context Petri nets, a Petri net-based programming model for selfadaptive systems. This model provides a formal definition of adaptations and their interaction, as well as a consistent process for their inclusion in the system. Besides serving as an underlying run-time model to ensure that adaptations and their constraints remain consistent, context Petri nets allow to analyze properties such as reachability, and liveness in the configuration of self-adaptive systems. Context Petri nets thus are a convenient tool to model and analyze the dynamics of self-adaptive systems, both formally and computationally.