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Period Optimization for Hard Real-time Distributed Automotive Systems
Abhijit Davare, Qi Zhu, Marco Di Natale, Claudio Pinello, Sri Kanajan, Alberto Sangiovanni-Vincentelli

Citation
Abhijit Davare, Qi Zhu, Marco Di Natale, Claudio Pinello, Sri Kanajan, Alberto Sangiovanni-Vincentelli. "Period Optimization for Hard Real-time Distributed Automotive Systems". Design Automation Conference, 278-283, June, 2007.

Abstract
The complexity and physical distribution of modern active-safety automotive applications requires the use of distributed architectures. These architectures consist of multiple electronic control units (ECUs) connected with standardized buses. The most common configuration features periodic activation of tasks and messages coupled with run-time priority-based scheduling. The correct deployment of applications on such architectures requires end-to end latency deadlines to be met. This is challenging since deadlines must be enforced across a set of ECUs and buses, each of which supports multiple functionality. The need for accommodating legacy tasks and messages further complicates the scenario. In this work, we automatically assign task and message periods for distributed automotive systems. This is accomplished by leveraging schedulability analysis within a convex optimization framework to simultaneously assign periods and satisfy end-to-end latency constraints. Our approach is applied to an industrial case study as well as an example taken from the literature and is shown to be both effective and efficient.

Electronic downloads

Citation formats  
  • HTML
    Abhijit Davare, Qi Zhu, Marco Di Natale, Claudio Pinello,
    Sri Kanajan, Alberto Sangiovanni-Vincentelli. <a
    href="http://chess.eecs.berkeley.edu/pubs/227.html"
    >Period Optimization for Hard Real-time Distributed
    Automotive Systems</a>, Design Automation Conference,
    278-283, June, 2007.
  • Plain text
    Abhijit Davare, Qi Zhu, Marco Di Natale, Claudio Pinello,
    Sri Kanajan, Alberto Sangiovanni-Vincentelli. "Period
    Optimization for Hard Real-time Distributed Automotive
    Systems". Design Automation Conference, 278-283, June,
    2007.
  • BibTeX
    @inproceedings{DavareZhuDiNatalePinelloKanajanSangiovanniVincentelli07_PeriodOptimizationForHardRealtimeDistributedAutomotive,
        author = {Abhijit Davare and Qi Zhu and Marco Di Natale and
                  Claudio Pinello and Sri Kanajan and Alberto
                  Sangiovanni-Vincentelli},
        title = {Period Optimization for Hard Real-time Distributed
                  Automotive Systems},
        booktitle = {Design Automation Conference},
        pages = {278-283},
        month = {June},
        year = {2007},
        abstract = {The complexity and physical distribution of modern
                  active-safety automotive applications requires the
                  use of distributed architectures. These
                  architectures consist of multiple electronic
                  control units (ECUs) connected with standardized
                  buses. The most common configuration features
                  periodic activation of tasks and messages coupled
                  with run-time priority-based scheduling. The
                  correct deployment of applications on such
                  architectures requires end-to end latency
                  deadlines to be met. This is challenging since
                  deadlines must be enforced across a set of ECUs
                  and buses, each of which supports multiple
                  functionality. The need for accommodating legacy
                  tasks and messages further complicates the
                  scenario. In this work, we automatically assign
                  task and message periods for distributed
                  automotive systems. This is accomplished by
                  leveraging schedulability analysis within a convex
                  optimization framework to simultaneously assign
                  periods and satisfy end-to-end latency
                  constraints. Our approach is applied to an
                  industrial case study as well as an example taken
                  from the literature and is shown to be both
                  effective and efficient.},
        URL = {http://chess.eecs.berkeley.edu/pubs/227.html}
    }
    

Posted by Abhijit Davare on 11 May 2007.
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