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Schedule reparability: Enhancing time-triggered network recovery upon link failures
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: Proceedings - 2018 IEEE 24th International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 147-156Conference paper, Published paper (Refereed)
Abstract [en]

The time-triggered communication paradigm has been shown to satisfy temporal isolation while providing end to end delay guarantees through the synthesis of an offline schedule. However, this paradigm has severe flexibility limitations as any unpredicted change not anticipated by the schedule, such as a component failure, might result in a loss of frames. A typical solution is to use redundancy or replace and update the schedule offline anew. With the ever increase in size of networks and the need to reduce costs, supplementary solutions that enhance the reliability of such networks are also desired. In this paper, we introduce a repair algorithm capable of reacting to unpredicted link failures. The algorithm quickly modifies the schedule such that all frames are transmitted again within their timing guarantees. We found that the success of our algorithm increases significantly with the existence of empty slots spread over the schedule, an opposite approach compared to packing frames, commonly used in the literature. We propose a new ILP formulation that includes a maximization of frame and link intermissions to stretch empty slots over the schedule. Our results show that we can repair with 90% success rate within milliseconds to a valid schedule compared to a few minutes needed to re-schedule the whole network. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. p. 147-156
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-42810DOI: 10.1109/RTCSA.2018.00026ISI: 000458980300017Scopus ID: 2-s2.0-85061771050ISBN: 9781538677599 (print)OAI: oai:DiVA.org:mdh-42810DiVA, id: diva2:1292444
Conference
24th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2018; Hakodate; Japan; 29 August 2018 through 31 August 2018
Available from: 2019-02-28 Created: 2019-02-28 Last updated: 2019-09-06Bibliographically 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: 2019-09-24Bibliographically approved

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Pozo Pérez, Francisco ManuelRodriguez-Navas, GuillermoHansson, Hans

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