Understanding and Comparing Approaches for Performance Engineering of Self-adaptive Systems Based on Queuing Networks

Enabling self-adaptation within hardware/software systems is a complex task, mainly due to environment uncertainty that has to be faced while the system is providing its functionalities. Besides, non-functional goals that have to be met by the system may be introduced, defining Quality-of-Service (QoS) requirements which drive the adaptation. This paper enhances a previous study which surveyed the literature with respect to performance-driven self-adaptation, supported by the Queuing Network paradigm. The seven approaches identified in previous work are detailed in this paper based on a well-defined taxonomy deriving from the former’s classification scheme and spanning over different dimensions, with particular emphasis on the way adaptation mechanisms are introduced, e.g. available knobs, nonfunctional goals, sources of uncertainty. Based on such taxonomy, internal characteristics of those approaches are described, as well as commonalities and differences, aimed at providing a detailed view of the current state-of-art in the context of performance-driven self-adaptation supported by the Queuing Network paradigm.