The rigorous application of static timing analysis\ud requires a large and costly amount of detail knowledge on the\ud hardware and software components of the system. Probabilistic\ud Timing Analysis has potential for reducing the weight of that\ud demand. In this paper, we present a sound measurement-based\ud probabilistic timing analysis technique based on Extreme Value\ud Theory. In all the experiments made as part of this work, the\ud timing bounds determined by our technique were less than\ud 15% pessimistic in comparison with the tightest possible bounds\ud obtainable with any probabilistic timing analysis technique.\ud As a point of interest to industrial users, our technique also\ud requires a comparatively low number of measurement runs of\ud the program under analysis; less than 650 runs were needed for\ud the benchmarks presented in this paper

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Power dissipation has been an important design issue for a wide range of computer systems in the past decades. Dynamic power consumption due to signal switching activities and static power consumption due to leakage current are the two major sources of power consumption in a CMOS circuit. As CMOS technology advances towards deep sub-micron domain, static power dissipation is comparable to or even more than dynamic power dissipation. This article explores how to apply dynamic power management to reduce static power for hard real-time systems. We propose online algorithms that adaptively control the power mode of a system, procrastinating the processing of arrived events as late as possible. To cope with multiple event streams with different characteristics, we provide solutions for preemptive earliest-deadline-first and fixed-priority scheduling policies. By adopting a worstcase interval-based abstraction, our approach can not only tackle arbitrary event ar-164 Real-Time Syst (2011) 47: 163-193 rivals, e.g., with burstiness, but also guarantee hard real-time requirements with respect to both timing and backlog constraints. We also present extensive simulation results to demonstrate the effectiveness of our approaches.