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AImplemente 2D EC in Malicious Nodes vs Number of Nodes connectivity test

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Sudipta Basak 2024-04-08 14:43:35 +00:00
parent bf15ec97ab
commit 54ade6f429
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1 changed files with 27 additions and 6 deletions
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33
ConnectivityTest/MaliciousNodesVsNumberOfNodes/prog.py
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@ -19,13 +19,30 @@ def plotData(conf):
plt.savefig(conf['plotPath'])
plt.clf()
def isGConnected(deg, nodes, mal):
def isGroupRecoverable(group, nodes, chi1, chi2, size, sizeK):
uniqueLines = set()
for g in group:
linesSelected = set(random.sample(list(range(1, size + 1)), chi1 if g < nodes[0] else chi2))
uniqueLines.union(linesSelected)
return len(uniqueLines) >= sizeK
def isGConnected(deg, nodes, mal, config):
G = nx.random_regular_graph(deg, sum(nodes))
malNodes = random.sample(list(G.nodes()), k=mal * sum(nodes) // 100)
for mn in malNodes:
G.remove_node(mn)
return nx.is_connected(G)
if nx.is_connected(G): return True
else:
isRecoverable = True
chiR1 = config['custodyR'] * config['validatorPerNode1']
chiR2 = config['custodyR'] * config['validatorPerNode2']
rows = config['numberOfRows']
rowsK = config['numberOfRowsK']
for group in nx.connected_components(G):
isRecoverable = isRecoverable and isGroupRecoverable(group, nodes, chiR1, chiR2, rows, rowsK)
return isRecoverable
def getNodeCountPerColumn(config, numOfNodes):
numberOfCols = config['numberOfColumns']
@ -44,13 +61,13 @@ def getNodeCountPerColumn(config, numOfNodes):
return nodeCountPerColumn
def runOnce(deg, nodeCountPerCol, malNodesPercentage):
def runOnce(deg, nodeCountPerCol, malNodesPercentage, config):
isParted = False
partCount = 0
isPartedCount = 0
for col in nodeCountPerCol.keys():
nodes = nodeCountPerCol[col]
if not isGConnected(deg, nodes, malNodesPercentage):
if not isGConnected(deg, nodes, malNodesPercentage, config):
if not isParted: isParted = True
partCount += 1
@ -70,7 +87,7 @@ def study(config):
for mal in config['mals']:
isPartedCount = partCount = 0
nodeCountPerColumn = getNodeCountPerColumn(config, nn)
results = Parallel(-1)(delayed(runOnce)(config['deg'], nodeCountPerColumn, mal) for _run in range(config['runs']))
results = Parallel(-1)(delayed(runOnce)(config['deg'], nodeCountPerColumn, mal, config) for _run in range(config['runs']))
isPartedCount = sum([res[0] for res in results])
partCount = sum([res[1] for res in results])
partPercentages.append(isPartedCount * 100 / config['runs'])
@ -111,11 +128,15 @@ def study(config):
# Configuration
config = {
'runs': 10,
'runs': 20,
'deg': 8,
'mals': range(5, 100, 5),
'numberOfColumns': 128,
'numberOfColumnsK': 64,
'numberOfRows': 128,
'numberOfRowsK': 64,
'custodyC': 4,
'custodyR': 4,
'class1ratio': 0.8,
'validatorPerNode1': 1,
'validatorPerNode2': 8,