Published in Ramaprasad, H., & Mueller, F. (2009). Bounding Worst-Case Response Times of Tasks under PIP. 15th IEEE Real-Time and Embedded Technology and Applications Symposium, 2009, RTAS 2009. 183 - 192. DOI: 10.1109/RTAS.2009.28 ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


Schedulability theory in real-time systems requires prior knowledge of the worst-case execution time (WCET) of every task in the system. One method to determine the WCET is known as static timing analysis. Determination of the priorities among tasks in such a system requires a scheduling policy, which could be either preemptive or nonpreemptive.

While static timing analysis and data cache analysis are simplified by using a fully non-preemptive scheduling policy, it results in decreased schedulability. In prior work, a methodology was proposed to bound the data-cache related delay for real-time tasks that, beside having a non-preemptive region (critical section), can otherwise be scheduled preemptively.

While the prior approach improves schedulability in comparison to fully non-preemptive methods, it is still conservative in its approach due to its fundamental assumption that a task executing in a critical section may not be preempted by any other task. In this paper, we propose a methodology that incorporates resource sharing policies such as the Priority Inheritance Protocol (PIP) into the calculation of data-cache related delay. In this approach, access to shared resources, which is the primary reason for critical sections within tasks, is controlled by the resource sharing policy. In addition to maintaining correctness of access, such policies strive to limit resource access conflicts, thereby improving the responsiveness of tasks. To the best of our knowledge, this is the first framework that integrates data-cache related delay calculations with resource sharing policies in the context of real-time systems.