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Code and documentation to reproduce experimental results of the paper "Connecting the Dots: Selective Fragment Recovery in ICNLoWPAN" published in Proc. of ACM ICN 2020

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Connecting the Dots: Selective Fragment Recovery in ICNLoWPAN

Code and documentation to reproduce our experimental results.

Code

The explicit RIOT version is included as a submodule in this repository (RIOT). It is based on the 2020.04 release of RIOT (including hot-fixes) but also contains all relevant changes to conduct the experiments. The PRs these changes came from are documented within the git history. For more information use

git -C RIOT/ log

The app directory contains the RIOT application required for the experiments. It can be configured to be either an NDN consumer, forwarder, or producer. Please refer to its README for its usage.

The scripts directory contains both scripts to conduct the experiments, and to plot their results. Please also refer to their respective READMEs for their usage.

To handle the rather specific dependencies of the scripts, we recommend using virtualenv:

virtualenv -p python3 env
source env/bin/activate

Usage

You can look into all the code and its documentation to figure everything out, but the quickest way to start the experiments is to just run (given the nodes in descs.example.yaml are bookable on the IoT-LAB and all requirements on the OS side are fulfilled, see scripts README's):

rm -rf env
virtualenv -p python3 env
source env/bin/activate
pip install -r ./scripts/experiment_ctrl/requirements.txt
cp ./scripts/experiment_ctrl/descs.example.yaml \
    ./scripts/experiment_ctrl/descs.yaml
./scripts/experiment_ctrl/setup_exp.sh

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Code and documentation to reproduce experimental results of the paper "Connecting the Dots: Selective Fragment Recovery in ICNLoWPAN" published in Proc. of ACM ICN 2020

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