Performance Prediction for Embedded Systems
Jens Happe · 2005
In this paper, we discuss dierent approaches to performance prediction of embedded systems. We distinguish two categories of prediction models depending on the system type. First we consider prediction models for hard real-time systems. These are systems whose correctness depends on the ability to meet all deadlines. Therefore, methods to compute the worst case execution time of each process are required. Then the worst case execution times are used in combination with scheduling algorithms to proof the feasibility of the system on a given set of processors. Second we consider prediction models for soft real-time systems whose deadlines can be missed occasionally. Stochastic approaches which determine the probability of meeting a deadline are used in this case. We discuss these approaches with an example based on Stochastic Automaton Networks. Finally, we discuss the applicability of performance prediction models for embedded systems on general software systems.