Worst-case temperature analysis for real-time systems

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-deadline-first (EDF), rate-monotonie (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.