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

• http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-148.html. (Previous Version as a Technical Memorandum)
• http://doi.acm.org/10.1145/1347375.1347382

• 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
   �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-�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-�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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