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

• http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-53.html

• 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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