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Methods for large-scale time-triggered network scheduling
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1228-5176
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-4987-7669
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-7235-6888
2019 (English)In: Electronics (Switzerland), ISSN 2079-9292, Vol. 8, no 7, article id 738Article in journal (Refereed) Published
Abstract [en]

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 by up to two orders of magnitude.

Place, publisher, year, edition, pages
MDPI AG , 2019. Vol. 8, no 7, article id 738
Keywords [en]
Cyber-physical systems, Real-time networks, Scheduling, SMT solvers, Time-triggered
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45101DOI: 10.3390/electronics8070738ISI: 000482063200063Scopus ID: 2-s2.0-85070718684OAI: oai:DiVA.org:mdh-45101DiVA, id: diva2:1346661
Available from: 2019-08-28 Created: 2019-08-28 Last updated: 2019-09-12Bibliographically approved
In thesis
1. Methods for Efficient and Adaptive Scheduling of Next-Generation Time-Triggered Networks
Open this publication in new window or tab >>Methods for Efficient and Adaptive Scheduling of Next-Generation Time-Triggered Networks
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Real-time networks play a fundamental role in embedded systems. To meet timing requirements, provide low jitter and bounded latency in such networks the time-triggered communication paradigm is frequently applied in such networks. In this paradigm, a schedule specifying the transmission times of all the traffic is synthesized a priori. Given the steady increase in size and complexity of embedded systems, coupled with the addition of wireless communication, a new time-triggered network model of larger and mixed wired-wireless network isdeveloping. Developing such next-generation networks entails significant research challenges, especially concerning scalability, i.e., allowing generation of schedules of the very large next-generation networks in a reasonable time. A second challenge concerns a well-known limitation of the time-triggered paradigm: its lack of flexibility. Large networks exacerbate this problem, as the number of changes during network operation increases with the number of components, which renders static scheduling approaches unsuitable.

In this thesis, we first propose a remedy to the scalability challenge that the synthesis of next-generation network schedules introduces. We propose a family of divide-and-conquer approaches that segment the entire scheduling problem into small enough subproblems that can be effectively and efficiently solved by state-of-the-art schedulers. Second, we investigate how adaptive behaviours can be introduced into the time-triggered paradigm with the implementation of a Self-Healing Protocol. This protocol addresses the flexibility challenge by only updating a small segment of the schedule in response to changes during runtime. This provides a significant advantage compared to current approaches that fully reschedule the network. In the course of our research, we found that our protocol become more effective when the slack in the original schedule is evenly distributed during the schedule synthesis. As a consequence, we also propose a new scheduling approach that maximizes the distances between frames, increasing the success rate of our protocol.

The divide-and-conquer approaches developed in this thesis were able to synthesize schedules of two orders of magnitude more traffic and one order of magnitude more nodes in less than four hours. Moreover, when applied to current industrial size networks, they reduced the synthesis time from half an hour to less than one minute compared with state-of-the-art schedulers. The Self-Healing Protocol opened a path towards adaptive time-triggered being able to heal schedules online after link and switch failures in less than ten milliseconds.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2019
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 296
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-45165 (URN)978-91-7485-436-7 (ISBN)
Public defence
2019-10-24, Milos, Mälardalens högskola, Västerås, 13:30 (English)
Opponent
Supervisors
Available from: 2019-09-10 Created: 2019-09-06 Last updated: 2019-09-13Bibliographically approved

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Pozo Pérez, Francisco ManuelRodriguez-Navas, GuillermoHansson, Hans

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