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 real-time system algorithms is increasing extant to include functions such as image processing, rule-based fault protection, and intelligent sensor processing.; In this thesis we present an alternative framework for the implementation of real-time systems which accommodates mixed hard and soft real-time processing with measurable reliability by providing a confidence based scheduling and execution fault handling framework. This framework, called the RT EPA (real-time execution performance agent), provides a more natural and less constraining approach to translating both timing and functional requirements into a working system. The RT EPA framework is based on an extension to deadline monotonic theory. The RT EPA has been evaluated with simulated loading, an optical navigation test-bed, and the RT EPA monitoring module will be flown on an upcoming NASA space telescope in late 2001. The significance of this work is that it directly addresses the shortcomings in the current process for handling reliability and provides measurable reliability and performance feedback during the implementation, systems integration, and maintenance phases of the real-time systems engineering process. (Abstract shortened by UMI.)
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