BOLD Server

Quickstart

To run the server:

gradle install
cd build/install/bold-server
bin/bold-server

Alternatively, with Docker:

docker build . -t bold-server
docker run -p 8080:8080 -it bold-server

Then, go to http://localhost:8080 for a tutorial.

Benchmark Run

To evaluate agents against one of the tasks of the benchmark, run the server with an argument:

bin/bold-server <taskname>

Alternatively, with Docker:

docker run -p 8080:8080 -e TASKNAME=<taskname> -it bold-server

The first argument of the server command is a task name, e.g. bin/bold-benchmark ts1 will load ts1.properties. Default server configuration (when no argument is given) is stored in sim.properties.

To start/stop a simulation run, send the following HTTP requests to the server:

• PUT /sim with payload data/sim.ttl (or any RDF graph giving a number of iterations to run, with predicate sim:iterations)
• DELETE /sim (or any request that deletes that number of iterations)

See also run.sh (to execute after the server has started on port 8080).

While running, simulated time is available under /sim as follows:

@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix sim: <http://ti.rw.fau.de/sim#> .

<sim> sim:currentTime "2020-05-21T09:12:00Z"^xsd:dateTime ;
      sim:currentIteration 72 .

At the end of a simulation run, results are stored in the following two files:

• faults.tsv: first column gives the iteration number, following columns give a number of faults for each registered query
• interactions.tsv: first column also gives the iteration number, second column gives the total execution time for registered updates and the number of GET, PUT, DELETE, POST interactions with agents (included average processing time for each)

Results for any two successive runs are separated by \n\n (Gnuplot convention for multi-dataset files). Each dataset, i.e. data for a single run, includes a header line starting with # (Gnuplot comment symbol).

Acknowledgments

This work was partially funded by the German Federal Ministry of Education and Research through the MOSAIK project (grant no. 01IS18070A).