Preprint Article Version 1 This version is not peer-reviewed

Methods for Large-Scale Time-Triggered Network Scheduling

Version 1 : Received: 7 May 2019 / Approved: 8 May 2019 / Online: 8 May 2019 (11:53:33 CEST)

How to cite: Pozo, F.; Rodriguez-Navas, G.; Hansson, H. Methods for Large-Scale Time-Triggered Network Scheduling. Preprints 2019, 2019050099 (doi: 10.20944/preprints201905.0099.v1). Pozo, F.; Rodriguez-Navas, G.; Hansson, H. Methods for Large-Scale Time-Triggered Network Scheduling. Preprints 2019, 2019050099 (doi: 10.20944/preprints201905.0099.v1).

Abstract

Future cyber-physical systems may extend over broad geographical areas, like cities or regions, thus requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time up to two orders of magnitude.

Subject Areas

Real-Time Networks; Scheduling; Time-Triggered; SMT Solvers; Cyber-Physical Systems

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.