INVESTIGATION OF THE PERFORMANCE OF DIFFERENT OPERATING SYSTEMS FOR REAL-TIME EMBEDDED SYSTEMS

This article presents the findings of an investigation into the effectiveness of various real-time operating systems for embedded computing devices. The existing research weir examined and analyzed for their discussion of how operating system performance is monitored in real-time embedded systems and the obstacles that researchers confront in doing so. As the analysis demonstrates, recent developments in machine learning, real-world testing platforms, virtualization technologies, and hybrid evaluation methodology have increased our power to analyze and optimize operating system performance. This improvement was made possible by hybrid evaluation methodologies. Simulation, testing in the real world, and performance modeling are some of the other strategies that are used. In the final section of the paper, the potential applications of this research in industry and academia are discussed, along with future research directions for the establishment of more standardized and thorough evaluation methodologies and more efficient optimization approaches for real-time embedded systems. These topics are discussed in conjunction with the potential applications of this research in industry.