Latency-Aware Generation of Single-Rate DAGs from Multi-Rate Task Sets

Modern automotive and avionics embedded systems integrate several functionalities that are subject to complex timing requirements. A typical application in these fields is composed of sensing, computation, and actuation. The ever increasing complexity of heterogeneous sensors implies the adoption of multi-rate task models scheduled onto parallel platforms. Aspects like freshness of data or first reaction to an event are crucial for the performance of the system. The Directed Acyclic Graph (DAG) is a suitable model to express the complexity and the parallelism of these tasks. However, deriving age and reaction timing bounds is not trivial when DAG tasks have multiple rates. In this paper, a method is proposed to convert a multi-rate DAG task-set with timing constraints into a single-rate DAG that optimizes schedulability, age and reaction latency, by inserting suitable synchronization constructs. An experimental evaluation is presented for an autonomous driving benchmark, validating the proposed approach against state-of-the-art solutions.

I. Introduction

Modern automotive and avionics real-time embedded systems are composed of applications including sensors, control algorithms and actuators to regulate the state of a system in its environment within given timing constraints. Task chains are commonly adopted to model a sequence of steps performed along the control path. Complex data dependencies may exist between task chains with different activation rates, making it very hard to find reliable upper bounds on the end-to-end latency of critical effect chains [1].