Metrics and Benchmarks for Self-Aware Computing Systems
Self-Aware Computing Systems, Springer Verlag, Berlin Heidelberg, Germany, (2017)Abstract
In this chapter, we propose a list of metrics grouped by the MAPE-K paradigm for quantifying properties of self-aware computing systems. This set of metrics can be seen as a starting point toward benchmarking and comparing self-aware computing systems on a level-playing field. We discuss state-of-the art approaches in the related fields of self-adaptation and self-protection to identify commonalities in metrics for self-aware computing. We illustrate the need for benchmarking self-aware computing systems with the help of an approach that uncovers real-time characteristics of operating systems. Gained insights of this approach can be seen as a way of enhancing self-awareness by a measurement methodology on an ongoing basis. At the end of this chapter, we address new challenges in reference workload definition for benchmarking self-aware computing systems, namely load intensity patterns and burstiness modeling.
