Simulation has become a commonly employed first step in evaluating novel approaches towards resource allocation and task scheduling on distributed architectures. However, existing simulators fall short in their modeling of the instability common to shared computational infrastructure, such as public clouds. In this work, we present DynamicCloudSim which extends the popular simulation toolkit CloudSim with several factors of instability, including inhomogeneity and dynamic changes of performance at runtime as well as failures during task execution. As a use case and validation of the introduced functionality, we simulate the impact of instability on scientific workflow scheduling by assessing and comparing the performance of four schedulers in the course of several experiments. Results indicate that our model seems to adequately capture the most important aspects of cloud performance instability, though a validation on real hardware is still pending. The source code of DynamicCloudSim and the examined schedulers is available at https://code.google.com/p/dynamiccloudsim/.