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Causality Interfaces for Actor Networks
Ye Zhou, Edward A. Lee

Citation
Ye Zhou, Edward A. Lee. "Causality Interfaces for Actor Networks". ACM Transactions on Embedded Computing Systems (TECS), 7(3):1-35, April 2008.

Abstract
We consider concurrent models of computation where “actors” (components that are in charge of their own actions) communicate by exchanging messages. The interfaces of actors principally consist of “ports,” which mediate the exchange of messages. Actor-oriented architectures contrast with and complement object-oriented models by emphasizing the exchange of data between concurrent components rather than transformation of state. Examples of such models of computation include the classical actor model, synchronous languages, data-flow models, process networks, and discrete- event models. Many experimental and production languages used to design embedded systems are actor oriented and based on one of these models of computation. Many of these models of computation benefit considerably from having access to causality information about the components. This paper augments the interfaces of such components to include such causality information. It shows how this causality information can be algebraically composed so that compositions of components acquire causality interfaces that are inferred from their components and the interconnections. We illustrate the use of these causality interfaces to statically analyze timed models and synchronous language compositions for causality loops and data-flow models for deadlock. We also show that that causality analysis for each communication cycle can be performed independently and in parallel, and it is only necessary to analyze one port for each cycle. Finally, we give a conservative approximation technique for handling dynamically changing causality properties.

Electronic downloads

Citation formats  
  • HTML
    Ye Zhou, Edward A. Lee. <a
    href="http://chess.eecs.berkeley.edu/pubs/473.html"
    >Causality Interfaces for Actor Networks</a>,
    <i>ACM Transactions on Embedded Computing Systems
    (TECS)</i>, 7(3):1-35, April 2008.
  • Plain text
    Ye Zhou, Edward A. Lee. "Causality Interfaces for Actor
    Networks". <i>ACM Transactions on Embedded
    Computing Systems (TECS)</i>, 7(3):1-35, April 2008.
  • BibTeX
    @article{ZhouLee08_CausalityInterfacesForActorNetworks,
        author = {Ye Zhou and Edward A. Lee},
        title = {Causality Interfaces for Actor Networks},
        journal = {ACM Transactions on Embedded Computing Systems
                  (TECS)},
        volume = {7},
        number = {3},
        pages = {1-35},
        month = {April},
        year = {2008},
        abstract = {We consider concurrent models of computation where
                  âactorsâ (components that are in charge of
                  their own actions) communicate by exchanging
                  messages. The interfaces of actors principally
                  consist of âports,â which mediate the exchange
                  of messages. Actor-oriented architectures contrast
                  with and complement object-oriented models by
                  emphasizing the exchange of data between
                  concurrent components rather than transformation
                  of state. Examples of such models of computation
                  include the classical actor model, synchronous
                  languages, data-ï¬ow models, process networks,
                  and discrete- event models. Many experimental and
                  production languages used to design embedded
                  systems are actor oriented and based on one of
                  these models of computation. Many of these models
                  of computation benefit considerably from having
                  access to causality information about the
                  components. This paper augments the interfaces of
                  such components to include such causality
                  information. It shows how this causality
                  information can be algebraically composed so that
                  compositions of components acquire causality
                  interfaces that are inferred from their components
                  and the interconnections. We illustrate the use of
                  these causality interfaces to statically analyze
                  timed models and synchronous language compositions
                  for causality loops and data-ï¬ow models for
                  deadlock. We also show that that causality
                  analysis for each communication cycle can be
                  performed independently and in parallel, and it is
                  only necessary to analyze one port for each cycle.
                  Finally, we give a conservative approximation
                  technique for handling dynamically changing
                  causality properties.},
        URL = {http://chess.eecs.berkeley.edu/pubs/473.html}
    }
    

Posted by Mary Stewart on 30 Jul 2008.
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