| Abstract: |
With the evolution of today’s semiconductor technology, chip temperature increases rapidly mainly due to the growth in power density. For modern embedded real-time systems, it is
crucial to estimate maximal temperatures in order to take mapping or other design decisions to avoid burnout, and still be able to guarantee meeting real-time constraints. This paper provides
answers to the question: When work-conserving scheduling algorithms, such as earliest-deadlinefirst (EDF), rate-monotonic (RM), deadline-monotonic (DM), are applied, what is the worst-case peak
temperature of a real-time embedded system under all possible scenarios of task executions? We propose an analytic framework, which considers a general event model based on network and real-time
calculus. This analysis framework has the capability to handle a broad range of uncertainties in terms of task execution times, task invocation periods, and jitter in task arrivals. Simulations
show that our framework is a cornerstone to design real-time systems that have guarantees on both schedulability and maximal temperatures. |
