Generalized and Scalable Offset-Based Response Time Analysis of Fixed Priority Systems

Abstract Offset-based response time analysis techniques obtain tight worst-case response time (WCRT) bounds by accounting release time dependencies between tasks. The maximum response time variation of a task or a message (i.e., the difference between the worst-case and best-case response time) is used to compute the end-to-end delays of distributed systems (Palencia and Harbour, 1998), (Tindell and Clark, 1994). Hence, the WCRT evaluation plays an important role in determining tight end-to-end delays of distributed systems. In real-time theory, there exist two approaches for computing the WCRT of a task: the classical response time analysis (RTA) approach and the modular performance analysis with the Real-Time Calculus (MPA-RTC). MPA-RTC has its roots in Network Calculus (NC). MPA-RTC offers more powerful abstraction than RTA based techniques and allows composition in terms of tasks, event streams, and resource sharing which makes it a strong candidate to analyze distributed systems (Wandeler, 2006), (Perathoner, 2011). However, one of the key limitations of the MPA-RTC is its inability to handle offset dependencies between tasks, whereas the classical RTA techniques can handle them. In this paper, we propose a method to consider offset dependencies between tasks using an MPA-RTC framework for a fixed priority scheduler in a uniprocessor system. Hence, our approach leverages the advantages of the expressive MPA-RTC framework model. We propose novel heuristics and approximation to reduce the inherent complexity of an offset-based RTA. We quantitatively evaluate the effectiveness of our approach to the state-of-the-art classical offset-based RTA techniques.