Probabilistic worst-case response-time analysis for the controller area network

Nolte, Thomas; Hansson, Hans; Norström, Christer

doi:10.1109/rttas.2003.1203052

Cited by 64 publications

(34 citation statements)

References 9 publications

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“…Tindell's seminal research heavily influenced the design of on-chip CAN peripherals such as Motorola msCAN (Motorola, 1998) and has lead to a large body of work into schedulability theory and error models for CAN (Punnekkat et al, 2000;Nolte et al, 2002Nolte et al, , 2003Broster et al, 2002Broster et al, , 2005Hansson et al, 2002;Broster and Burns, 2003), including at least two PhD theses (Broster, 2003;Nolte, 2006). Overall, this research into CAN scheduling has been cited in over 200 2 subsequent papers.…”

Section: Research and Real-time Analysismentioning

confidence: 99%

Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised

et al. 2007

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Controller Area Network (CAN) is used extensively in automotive applications, with in excess of 400 million CAN enabled microcontrollers manufactured each year. In 1994 schedulability analysis was developed for CAN, showing how worst-case response times of CAN messages could be calculated and hence guarantees provided that message response times would not exceed their deadlines. This seminal research has been cited in over 200 subsequent papers and transferred to industry in the form of commercial CAN schedulability analysis tools. These tools have been used by a large number of major automotive manufacturers in the design of in-vehicle networks for a wide range of cars, millions of which have been manufactured during the last decade. This paper shows that the original schedulability analysis given for CAN messages is flawed. It may provide guarantees for messages that will in fact miss their deadlines in the worst-case. This paper provides revised analysis resolving the problems with the original approach. Further, it highlights that the priority assignment policy, previously claimed to be optimal for CAN, is not in fact optimal and cites a method of obtaining an optimal priority ordering that is applicable to CAN. The paper discusses the possible impact on commercial CAN systems designed and developed using flawed schedulability analysis and makes recommendations for the revision of CAN schedulability analysis tools. R. I. Davis ( ) . A. Burns

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Section: Research and Real-time Analysismentioning

confidence: 99%

Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised

et al. 2007

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“…The seminal work of Tindell et al lead to a large body of research into scheduling theory for CAN (Rufino et al, 1998;Broster et al, 2002;Broster and Burns, 2003;Broster, 2003;Broster et al, 2005;Ferreira et al, 2004;Nolte et al, 2002;Nolte et al, 2003;Nolte, 2006), and was used as the basis for commercial CAN schedulability analysis tools (Casparsson et al, 1998). Davis et al (2007) found and corrected significant flaws in the schedulability analysis given by Tindell and Burns, (1994), , and Tindell et al, (1995).…”

Section: Related Workmentioning

confidence: 99%

Schedulability analysis for Controller Area Network (CAN) with FIFO queues priority queues and gateways

et al. 2012

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Controller Area Network (CAN) • Section 4.6 has been added, providing formal proofs that the schedulability tests given in Sections 4.1, 4.2 and 4.3 are sufficient (Theorems 2 and 3) and selfsustainable (Theorems 4 and 5). This section also shows how more precise analysis can be achieved when the priorities of messages in a FIFO queue span those of messages in a priority queue or another FIFO queue, which is often the case in practice. Extended version• In Section 5.2, we have added a formal proof that transmission deadline monotonic priority ordering is optimal when all messages have the same maximum transmission time (Theorem 7).• In Section 7, we have extended the experimental evaluation to show how the performance degradation due to FIFO queues depends on the number of messages in each queue.• Sections 6.1 and 7.1 have been added, exploring the effects of implementing one or more FIFO queues in gateway nodes that are responsible for transferring messages from one network to another.

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“…in [7] and [8]. Some studies were addressing probabilistic analysis, and specifically response time distributions as a consequence of 1) all the possible phasing configurations between ECUs [9], [10] and 2) CAN bit-stuffing mechanism [11]. None of these works assumed the possibility of ECU clock drifts though they are a subject of interest in the field of wireless sensor networks [12].…”

Section: Previous Workmentioning

confidence: 99%

Impact of clock drifts on CAN frame response time distributions

2011

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Abstract:The response time distributions of the frames sent on a Controller Area Network (CAN) bus are of prime interest to dimension and validate automotive electronic architectures. However, the existing work on the timing behaviour of the CAN network does not take into account that all the data exchanges between the Electronic Control Units (ECUs) are driven by different and independent clocks which are subject to clock drifts. This paper proposes a model for clock drifts and describes their impact on the CAN frame response time distributions. By implementing the clock drifts in a CAN simulation tool, we show experimentally that the response time distributions converge, for drift values chosen randomly within the same range on all ECUs, whatever the initial phasings between the sending nodes. Furthermore, we show that, as a result of the clock drifts, the situations leading to the worst case response times are transient.

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Probabilistic worst-case response-time analysis for the controller area network

Cited by 64 publications

References 9 publications

Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised

Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised

Schedulability analysis for Controller Area Network (CAN) with FIFO queues priority queues and gateways

Impact of clock drifts on CAN frame response time distributions

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