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Interface Theories for Causality Analysis in Actor Networks
Ye Zhou

Citation
Ye Zhou. "Interface Theories for Causality Analysis in Actor Networks". PhD thesis, University of California, Berkeley, May, 2007.

Abstract
This dissertation focuses on 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, dataflow 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 dissertation studies formal analysis of such components to include such causality information. A causality interface framework, which focuses on functional actors, is presented. I show how this causality interface can be algebraically composed so that compositions of components acquire causality interfaces that are inferred from their components and the interconnections. I illustrate the use of these causality interfaces to statically analyze timed models and synchronous language compositions for causality loops and dataflow models for deadlock. I 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. Later, I present another framework called ordering dependency. Ordering dependency captures causality properties that are not captured by the functional abstraction of actors. I illustrate the use of ordering dependencies to analyze rendezvous of sequential programs, and its use in scheduling of distributed timed systems.

Electronic downloads

Citation formats  
  • HTML
    Ye Zhou. <a
    href="http://chess.eecs.berkeley.edu/pubs/302.html"
    ><i>Interface Theories for Causality Analysis in
    Actor Networks</i></a>, PhD thesis,  University
    of California, Berkeley, May, 2007.
  • Plain text
    Ye Zhou. "Interface Theories for Causality Analysis in
    Actor Networks". PhD thesis,  University of California,
    Berkeley, May, 2007.
  • BibTeX
    @phdthesis{Zhou07_InterfaceTheoriesForCausalityAnalysisInActorNetworks,
        author = {Ye Zhou},
        title = {Interface Theories for Causality Analysis in Actor
                  Networks},
        school = {University of California, Berkeley},
        month = {May},
        year = {2007},
        abstract = {This dissertation focuses on 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, dataflow 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 dissertation studies formal
                  analysis of such components to include such
                  causality information. A causality interface
                  framework, which focuses on functional actors, is
                  presented. I show how this causality interface can
                  be algebraically composed so that compositions of
                  components acquire causality interfaces that are
                  inferred from their components and the
                  interconnections. I illustrate the use of these
                  causality interfaces to statically analyze timed
                  models and synchronous language compositions for
                  causality loops and dataflow models for deadlock.
                  I 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. Later, I present
                  another framework called ordering dependency.
                  Ordering dependency captures causality properties
                  that are not captured by the functional
                  abstraction of actors. I illustrate the use of
                  ordering dependencies to analyze rendezvous of
                  sequential programs, and its use in scheduling of
                  distributed timed systems.},
        URL = {http://chess.eecs.berkeley.edu/pubs/302.html}
    }
    

Posted by Christopher Brooks on 7 Jun 2007.
Groups: ptolemy
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