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126 lines
4.1 KiB
Python
126 lines
4.1 KiB
Python
import networkx as nx
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import random
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import matplotlib.pyplot as plt
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import sys
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import numpy as np
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from datetime import datetime
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import os
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from joblib import Parallel, delayed
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def plotData(conf):
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for key, value in conf['y'].items():
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plt.plot(conf['x'], value, label=f"{conf['label']}: {key}")
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plt.xlabel(conf['xlabel'])
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plt.ylabel(conf['ylabel'])
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plt.title(conf['title'])
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plt.legend()
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plt.grid(True)
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plt.savefig(conf['plotPath'])
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plt.clf()
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def isGConnected(deg, nodes, mal):
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G = nx.random_regular_graph(deg, sum(nodes))
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malNodes = random.sample(list(G.nodes()), k=mal * sum(nodes) // 100)
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for mn in malNodes:
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G.remove_node(mn)
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return nx.is_connected(G)
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def getNodeCountPerColumn(config, numOfNodes):
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numberOfCols = config['numberOfColumns']
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chiC1 = config['custodyC'] * config['validatorPerNode1']
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chiC2 = config['custodyC'] * config['validatorPerNode2']
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node1Count = int(numOfNodes * config['class1ratio'])
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nodeCountPerColumn = dict()
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for _ in range(numOfNodes):
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colsSelected = random.sample(list(range(1, numberOfCols + 1)), chiC1 if _ < node1Count else chiC2)
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for col in colsSelected:
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if col in nodeCountPerColumn.keys():
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nodeCountPerColumn[col][0 if _ < node1Count else 1] += 1
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else:
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nodeCountPerColumn[col] = [0, 0]
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nodeCountPerColumn[col][0 if _ < node1Count else 1] = 1
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return nodeCountPerColumn
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def runOnce(deg, nodeCountPerCol, malNodesPercentage):
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isParted = False
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partCount = 0
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isPartedCount = 0
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for col in nodeCountPerCol.keys():
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nodes = nodeCountPerCol[col]
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if not isGConnected(deg, nodes, malNodesPercentage):
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if not isParted: isParted = True
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partCount += 1
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if isParted: isPartedCount += 1
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return isPartedCount, partCount
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def study(config):
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nnPartPercentages = dict()
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nnAvgDisconnectedCols = dict()
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for nn in config['numberOfNodes']:
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print(f"\nNumber of Nodes: {nn}")
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partPercentages = list()
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avgDisconnectedCols = list()
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for mal in config['mals']:
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isPartedCount = partCount = 0
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nodeCountPerColumn = getNodeCountPerColumn(config, nn)
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results = Parallel(-1)(delayed(runOnce)(config['deg'], nodeCountPerColumn, mal) for _run in range(config['runs']))
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isPartedCount = sum([res[0] for res in results])
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partCount = sum([res[1] for res in results])
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partPercentages.append(isPartedCount * 100 / config['runs'])
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avgDisconnectedCols.append(partCount / config['runs'])
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print(f"Malicious Nodes: {mal}%, Partition Percentage: {partPercentages[-1]}, Avg. Partitions: {avgDisconnectedCols[-1]}")
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nnPartPercentages[nn] = partPercentages
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nnAvgDisconnectedCols[nn] = avgDisconnectedCols
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now = datetime.now()
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execID = now.strftime("%Y-%m-%d_%H-%M-%S_")+str(random.randint(100,999))
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newpath = f"ConnectivityTest/MaliciousNodesVsNumberOfNodes/results/{execID}/"
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if not os.path.exists(newpath): os.makedirs(newpath)
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conf1 = {
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'x': config['mals'],
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'y': nnPartPercentages,
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'label': "Nodes",
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'xlabel': "Malicious Node (%)",
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'ylabel': "Partition Possibility (%)",
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"title": "Possibility of Network Graph Get Partitioned for Malicious Nodes",
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"plotPath": f"{newpath}prob.png"
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}
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conf2 = {
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'x': config['mals'],
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'y': nnAvgDisconnectedCols,
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'label': "Nodes",
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'xlabel': "Malicious Node (%)",
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'ylabel': "Avg. Disconnected Columns",
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"title": "Malicious Nodes (%) vs. Disconnected Columns",
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"plotPath": f"{newpath}num.png"
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}
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plotData(conf1)
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plotData(conf2)
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# Configuration
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config = {
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'runs': 20,
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'deg': 8,
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'mals': range(5, 100, 5),
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'numberOfColumns': 128,
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'custodyC': 4,
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'class1ratio': 0.8,
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'validatorPerNode1': 1,
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'validatorPerNode2': 8,
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'numberOfNodes': [int(_) for _ in (np.logspace(2, 4, 5, endpoint=True, base=10) * 5)]
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}
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if __name__ == "__main__":
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study(config) |