EMPRESS: an Efficient and Effective Method for PREdictable Stack Sharing

Stack sharing between tasks may significantly reduce the amount of memory required in resource-constrained real-time embedded systems. On the downside, stack sharing decreases the predictability of a system, e.g. may give rise to a substantial variation in the address space for the memory locations used for the stack of a task. As a result, the precision of execution-time bounds may be reduced, the pessimism in schedulability analysis increased, and optimizations to increase schedulability hampered. In this paper, we present EMPRESS, an Efficient and effective Method for PREdictable Stack Sharing. We assume priority-based scheduled systems, where the binary pre-emption relation on tasks is a strict partial order, and static bounds on each task's stack usage. Both assumptions are common in the embedded real-time domain. For such systems, EMPRESS provides a predictable stack sharing between tasks, i.e. the stack of every task is always located in the very same memory area, even for tasks sharing a stack. It therefore combines the predictability of dedicated stack spaces with the reduced memory need of a shared stack. We exemplify the benefits of EMPRESS using as a case study an implementation of an unmanned aerial vehicle, and explain how EMPRESS can be realized within t.he Erika Enterprise RTOS without additional overheads.