Prediction of end-to-end deadline missing in distributed threads systems

Distributed real-time threads are schedulable entities with an end-to-end deadline that traverse nodes, carrying their scheduling context. In each node, the thread will be locally scheduled and predictions about deadline missing allow that actions are carried out to improve system performance. This paper presents a task model and deadline partitioning algorithms that consider the possibility of a distributed thread to follow different paths. The future execution flow of the distributed thread is only probabilistic known before its execution. End-to-end deadline missing prediction mechanisms can be carried out through definition of estimated local deadlines. Simulations show that the proposed prediction mechanism presents good results in overloaded systems.