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https://github.com/jonhoo/simio

I/O Automata Simulator
https://github.com/jonhoo/simio

automata distributed-systems simulation visualization

Last synced: 4 months ago
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I/O Automata Simulator

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README 

        
simio is an [I/O Automata](http://groups.csail.mit.edu/tds/papers/Lynch/ioa-leavens.pdf)

simulator, that aims to provide students of distributed systems with

tools for visualizing the behaviour of I/O automata in arbitrary

networks.



To build the toolkit, run `make` in the root of the repository.



## Writing automata



The simulator expects automata definitions to be written in a thin

Domain-Specific Language that wraps Python. Example implementations of

common distributed algorithms can be seen in

[`examples/specs`](examples/specs/). The language and simulation is more

thoroughly described in the tech report, which can be generated in the

`doc/` directory using `make report.pdf`.



When writing specifications, there are a few special pieces of state

available to you:



 - `self.i` is a unique per-node identifier

 - in outgoing transitions (i.e., those defined as tasks that have a

   `Transition-Output`), a variable named `to` holds the unique

   identifier of the neighbour currently being sent to.

 - in incoming transitions (i.e., those that appear in

   `Signature-Input`, and `connect` with an outgoing transition), a

   variable named `fr` holds the unique identifier of the neighbour that

   sent the current message.



In addition, an automata can, at any point, call the `mark` function to

change the color of the current node in the visualization, or the

`label` function to change the textual annotation for that node.



The simio parser, `src/parser/parser.py`, should be invoked on the

automaton specification to generate an executable automaton file:



    # Note that the output file *must* currently be called wtf.py

    ./src/parser/parser.py -f examples/specs/paxos.ioa > wtf.py



## Defining network graphs



A network graph should first be defined using the Graphviz [DOT

format](http://www.graphviz.org/content/dot-language). All edges

represent a FIFO channel, and all nodes in the graph will be running a

single instance of the automaton. Example graphs can be seen in

[`examples/graphs`](examples/graphs/).



## Visualizing behavior



To visualize how a given automaton behaves on a given graph, invoke the

simulator using:



    ./src/simulator/simulator.py -s .2 -g examples/graphs/complete.gv



This will open up a live view of the simulation in a new window, powered

by the simio [renderer](src/renderer/src/renderer/). If nothing opens,

you're probably missing `python2-pyinotify`. The `-s` option specifies

the time delay between each step of the simulation, and allows speeding

up or slowing down the visualization. `-t` can be used to keep every

intermediate visualization of the run.



The simulator's `STDOUT` will contain anything printed inside the

running automaton instances, while `STDERR` will contain messages from

the simulator.



## Included examples



To run one of the included examples, call `make`, and then run one of

the scripts in [`examples/demos`](examples/demos). Demos for

Bellman-Ford, Paxos, Peterson's leader-election algorithm, and Luby

Maximal Independent Set are given. You might want to run the examples

with `-s .2` so the simulation does not run too quickly to follow.