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add cortze/py-dht as submodule + add DHT related parameters to the DAS conf/shape

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cortze 2023-08-04 10:28:48 +02:00
parent db5fd6c157
commit 808f857659
6 changed files with 45 additions and 4 deletions
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1
.gitignore vendored
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@ -5,3 +5,4 @@ myenv*/
doc/_build
!results/plots.py
Frontend/
.idea

3
.gitmodules vendored Normal file
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@ -0,0 +1,3 @@
[submodule "py-dht"]
path = py-dht
url = https://github.com/cortze/py-dht.git

2
README.md
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@ -26,7 +26,7 @@ cd das-research
```
python3 -m venv myenv
source myenv/bin/activate
pip3 install -r DAS/requirements.txt
bash install_dependencies.sh
```
## Run the simulator

20
install_dependencies.sh Normal file
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VENV="./myenv"
echo "Installing dependencies for DAS..."
# activate the venv or raise error if error
source $VENV/bin/activate
if [ $? -eq 0 ]; then
echo "venv successfully sourced"
else
echo "unable to source venv at $VENV , does it exist?"
exit 1
fi
# make sure that the submodule module is correctly downloaded
git submodule update --init
# install requirements for DAS and py-dht and install the dht module from py-dht
pip3 install -r DAS/requirements.txt
pip3 install -r py-dht/requirements.txt
pip3 install -e py-dht

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py-dht Submodule

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Subproject commit 3f7d75451905b7bd9e6207a1168b3086b244f890

22
smallConf.py
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@ -101,10 +101,26 @@ diagnostics = False
# True to save git diff and git commit
saveGit = False
# --- DHT Parameters ---
# True to simulate the distribution of the BlockSegments over a simulated DHTNetwork
dhtSimulation = True
# K replication factor, in how many DHT nodes are we going to store the block segments
# reused as how many DHT nodes will fit into each Kbucket to the routing table
ks = [20]
# Number of concurrent DHT nodes that will be contacted during a Lookup
alphas = [1]
# Number of steps without finding any closer DHT nodes to a Hash will the DHT lookup perform before finishing it
# Not using steps4StopCondition as 7 steps looks too much for the DHT (although it could be changed :))
nilStepsToStopLookup = 3
def nextShape():
for run, fm, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
runs, failureModels, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
for run, fm, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2, k, alpha in itertools.product(
runs, failureModels, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2, ks, alphas):
# Network Degree has to be an even number
if netDegree % 2 == 0:
shape = Shape(blockSize, nn, fm, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
shape = Shape(blockSize, nn, fm, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, k, alpha, run)
yield shape