Periodic Scheduling of Grouped Time-Triggered Signals on a Single Resource

TL;DR

This paper addresses the complex problem of efficiently grouping and scheduling time-triggered signals into messages on a single resource to optimize bandwidth and delivery success in critical communication systems.

Contribution

It introduces a novel approach for grouping signals into messages considering size constraints and develops a scheduling method for periodic message transmission.

Findings

Improved resource utilization through signal grouping.

Enhanced scheduling efficiency for time-triggered messages.

Reduced message transmission failures in critical systems.

Abstract

Time-triggered messages are of crucial importance in modern communication networks. Offline-generated schedules, which specify start times for periodic messages, enable us to achieve deterministic behavior in critical applications. In automotive and avionics domains, so-called signals (measurements and commands) are periodically generated and communicated (via messages) among sensors, controllers, and actuators. However, the message contains not only the useful signal data, but also necessary metadata, e.g., message ID. Metadata is stored as a header or tail and extends the message size; when the signal is very short (as it often is in applications), sending each in a separate message is inefficient. Thus, several signals are grouped into a single message, depending on their periodicity and length, and sent with just one header. Such an approach increases the utilization of the communication resource (link or bus), since less bandwidth is wasted on headers (Kuaban et al. 2021). However, grouping the signals into messages is complicated. The maximum size of the message (including the metadata) is finite, since longer messages have a lower probability of successful delivery. Also, longer messages are less flexible for scheduling in a periodic setting. This is similar to the work of Huan et al. (2019), where the compromise between energy efficiency and latency for IoT devices was investigated. In this paper, we study the fundamental problem of grouping time-triggered signals into messages and periodic scheduling of messages on a single resource.