Probabilistic Simulation-Based Analysis of Complex Real-Time Systems

Many industrial real-time systems have evolved over a long period of time and were initially so simple that it was possible to predict consequences of adding new functionality by common sense. However, as the system evolves the possibility to predict the consequences of changes becomes more and more difficult unless models and analysis method can be used. Moreover, traditional real-time models, e.g., fixed priority analysis, may be too simple for accurately capturing a complex system’s characteristics. For instance, assuming worst-case execution time may not be realistic. Hence, analyses based on these models may give an overly pessimistic result. In this paper we describe our approach to introducing analyzability into complex real-time control systems. The proposed method is based on analytical models and discrete-event based simulation of the system behavior based on these models. The models describe execution times as statistical distributions which are measured and calculated ...

• Type: Conference
• Year: 2003
• Where: ISORC
• Authors: Anders Wall, Johan Andersson, Christer Norström
• Keywords: Difficult Unless Models, Execution Times, ISORC 2003, Software Engineering, Traditional Real-time Models