A real-time execution performance agent interface for confidence-based scheduling

Abstract

The use of microprocessors and software to build real-time applications is expanding from traditional domains such as digital control, data acquisition, robotics, and digital switching, to include emerging domains like multimedia, virtual reality, optical navigation, and audio processing. These emerging real-time application domains require much more bandwidth and processing capability than the traditional real-time systems applications. Furthermore, at the same time, the potential performance and complexity of microprocessor and I/O architectures is also rapidly evolving to meet these new application demands (e.g. a super-scalar, pipelined architecture with multilevel cache with burst transmission I/O bus). Finally, the complexity of typical realtime system algorithms is increasing extant to include functions such as image processing, rulebased fault protection, and intelligent sensor processing. The foundation of real-time systems theory is the recognition that bandwidth and processing resources will always be constrained (a more demanding application always exists that can make use of increased resources as they become available). Given this reality, the question is how does an engineer formally ensure, given resource constraints, that the system will not only function correctly, but also meet timing deadlines. Since the introduction of Liu and Layland's rate-monotonic analysis and the development of the formal theory of hard real-time systems, significant progress has been made on extending this theory and developing an engineering process for it. The problem is that the current hard real-time theory and process assumes full reliability and constrains systems more than necessary by requiring either deterministic use of resources or worst-case models of such usage. R...