Time-Triggered Co-Scheduling of Computation and Communication with Jitter Requirements

TL;DR

This paper addresses the challenge of co-scheduling computation and communication in automotive embedded systems with jitter constraints, proposing models and heuristics that improve resource utilization while managing timing jitter.

Contribution

It introduces ILP and SMT models for jitter-constrained scheduling and a scalable heuristic, enhancing schedulability and resource efficiency in complex real-world applications.

Findings

Jitter-constrained scheduling increases resource utilization by up to 28%.

Heuristic approach scales to 10,000 tasks and messages.

Relaxed jitter requirements allow longer computation times with better resource use.

Abstract

The complexity of embedded application design is increasing with growing user demands. In particular, automotive embedded systems are highly complex in nature, and their functionality is realized by a set of periodic tasks. These tasks may have hard real-time requirements and communicate over an interconnect. The problem is to efficiently co-schedule task execution on cores and message transmission on the interconnect so that timing constraints are satisfied. Contemporary works typically deal with zero-jitter scheduling, which results in lower resource utilization, but has lower memory requirements. This article focuses on jitter-constrained scheduling that puts constraints on the tasks jitter, increasing schedulability over zero- jitter scheduling. The contributions of this article are: 1) Integer Linear Programming and Satisfiability Modulo Theory model exploiting problem-specific information to reduce the formulations complexity to schedule small applications. 2) A heuristic approach, employing three levels of scheduling scaling to real-world use-cases with 10000 tasks and messages. 3) An experimental evaluation of the proposed approaches on a case-study and on synthetic data sets showing the efficiency of both zero-jitter and jitter- constrained scheduling. It shows that up to 28% higher resource utilization can be achieved by having up to 10 times longer computation time with relaxed jitter requirements.