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Self-Healing Protocol: Repairing Scheduels Online after Link Failures in Time-Triggered Networks
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1228-5176
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-4987-7669
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-7235-6888
(engelsk)Inngår i: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050Artikkel i tidsskrift (Fagfellevurdert) Submitted
Abstract [en]

The time-triggered paradigm is not adaptive, a static schedule determines the time-triggered communication and, then, any unpredicted change, like a link failure, might result in the loss of frames. Using spatial redundancy or recomputing a new schedule for replacement achieves fault tolerance only in moderate-size networks. With the increase in size and complexity of cyber-physical systems, more scalable and cost-efficient mechanisms are needed in order to complement conventional solutions. We propose a distributed Self-Healing Protocol that instead of recomputing the whole schedule, repairs the existent schedule at runtime. The basis of our protocol is the collaboration of nodes in the network to individually adjust their local schedules for rerouting the frames affected by link failures. Our protocol exhibits a high success rate compared to full rescheduling, as well as remarkable scalability; it repairs the schedule in milliseconds, whereas rescheduling requires minutes.

HSV kategori
Forskningsprogram
datavetenskap
Identifikatorer
URN: urn:nbn:se:mdh:diva-45127OAI: oai:DiVA.org:mdh-45127DiVA, id: diva2:1347769
Tilgjengelig fra: 2019-09-02 Laget: 2019-09-02 Sist oppdatert: 2019-09-13bibliografisk kontrollert
Inngår i avhandling
1. Methods for Efficient and Adaptive Scheduling of Next-Generation Time-Triggered Networks
Åpne denne publikasjonen i ny fane eller vindu >>Methods for Efficient and Adaptive Scheduling of Next-Generation Time-Triggered Networks
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Västerås: Mälardalen University, 2019
Serie
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 296
HSV kategori
Forskningsprogram
datavetenskap
Identifikatorer
urn:nbn:se:mdh:diva-45165 (URN)978-91-7485-436-7 (ISBN)
Disputas
2019-10-24, Milos, Mälardalens högskola, Västerås, 13:30 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-09-10 Laget: 2019-09-06 Sist oppdatert: 2019-09-24bibliografisk kontrollert

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