This study investigates levels of Operating System (OS) noise on Apple iPad mobile devices. OS noise causes variations in application performance that interfere with microbenchmark results. OS noise manifests in collected data through extreme outliers and variations in skewness. Using our collected data, we develop an iterative, semi-automated outlier removal process for Apple iPad OS noise profiles. The profiles generated by outlier removal represent the first step toward an adaptive noise mitigation technique, which presents opportunities for use in microbenchmarking across other mobile platforms.
Rehn, Adam; Hamilton, John R.; and Holdsworth, Jason, "Towards an Adaptive OS Noise Mitigation Technique for Microbenchmarking on Apple Ipad Devices" (2014). ICEB 2014 Proceedings. 12.