Testing uncertainty of cyber-physical systems in IoT cloud infrastructures: combining model-driven engineering and elastic execution

Abstract

Today's cyber-physical systems (CPS) span IoT and cloud-based datacenter infrastructures, which are highly heterogeneous with various types of uncertainty. Thus, testing uncertainties in these CPS is a challenging and multidisciplinary activity. We need several tools for modeling, deployment, control, and analytics to test and evaluate uncertainties for different configurations of the same CPS. In this paper, we explain why using state-of-the art model-driven engineering (MDE) and model-based testing (MBT) tools is not adequate for testing uncertainties of CPS in IoT Cloud infrastructures. We discus how to combine them with techniques for elastic execution to dynamically provision both CPS under test and testing utilities to perform tests in various IoT Cloud infrastructures.