Dynamic Modelling of Tactics Impact on the Stability of Self-Aware Cloud Architectures

Given the elasticity, on-demand nature, and runtime dynamics of the cloud, a stable self-adaptive architecture should keep the fulfilment of Quality of Service objectives stable, while performing stable adaptations that converge towards these objectives. The dynamic management and selection of architectural tactics, as adaptation mechanisms, shall be in the heart of the adaptation process, as being essential for effective and stable adaptations. This calls for measuring the impact of tactics on the stability of inter-related quality attributes during run-time. In this paper, we introduce a Markovian-based analytical model for dynamically assessing the impact of tactics on the stability behaviour of self-adaptive cloud architectures. The model also employs self-awareness capabilities for betterinforming the selection of optimal tactics configurations leading to stability. Experimental evaluations have shown the accuracy and efficiency of the model in measuring and predicting the impact of tactics on stabilising the Quality of Service provision and the adaptation process.