Abstract | ||
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This paper explores bounded-time recovery (BTR), a new approach to making cyber-physical systems robust to crash faults. Rather than trying to mask the symptoms of a fault with massive redundancy, BTR detects faults at runtime and enables the system to recover from them – e.g., by transferring tasks to other nodes that are still working correctly. When a fault does occur, there is a brief period of instability during which the system can produce incorrect outputs. However, many cyber-physical systems have physical properties – such as inertia or thermal capacity – that limit the rate at which the state of the system can change; thus, a very brief outage is often acceptable, as long as its duration can be bounded, to perhaps a few milliseconds.BTR has some interesting properties: for instance, it has a much lower overhead than Paxos, and, unlike Paxos, it can take useful actions even when the system partitions or a majority of the nodes fails. However, it also poses a very unusual scheduling problem that involves creating sets of interrelated schedules for different failure modes. We present a scheduling algorithm called Cascade that can quickly find suitable schedules. Using a prototype implementation, we show that Cascade scales far better than a baseline algorithm and reduces the scheduling time from hours to a few seconds, without sacrificing quality. |
Year | DOI | Venue |
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2020 | 10.1109/RTAS48715.2020.00-13 | 2020 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) |
Keywords | DocType | ISSN |
design space exploration for RT for latency-sensitive systems,scheduling and resource allocation for RT or latency-sensitive systems,system-level optimization and co-design techniques for RT or latency-sensitive systems | Conference | 1545-3421 |
ISBN | Citations | PageRank |
978-1-7281-5500-5 | 0 | 0.34 |
References | Authors | |
24 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Neeraj Gandhi | 1 | 1 | 1.37 |
Edo Roth | 2 | 5 | 2.74 |
Robert Gifford | 3 | 3 | 1.75 |
Linh Thi Xuan Phan | 4 | 9 | 5.54 |
Andreas Haeberlen | 5 | 47 | 5.75 |