Modelling Adaptive Autonomic Cloud Application Utility Using Template Functions

Autonomic decisions are necessary for persistent Cloud application adaptation due to dynamic execution context and changing workload. However, it is often difficult to accurately model the utility to represent the application owner's preferences as a mathematical function linking the utility with the monitored information from the application. We propose a systematic approach for utility function modelling for adaptive applications in the Cloud continuum. This method exploits a set of utility function templates, automated quality checks, and the impact of measurements and performance indicators values on the utility value range. The method is evaluated with an illustrative example of a Cloud application that is compared to an existing manually modelled utility function.