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Fixing the global random uniform distribution of topics across validators

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This commit is contained in:
Leonardo Bautista-Gomez 2023-03-21 15:16:19 +01:00
parent 125ba2ad4a
commit 3642083f22
2 changed files with 35 additions and 10 deletions
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33
DAS/simulator.py
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@ -30,15 +30,27 @@ class Simulator:
self.glob.reset() self.glob.reset()
self.validators = [] self.validators = []
if self.config.evenLineDistribution: if self.config.evenLineDistribution:
rows = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberNodes/self.shape.blockSize)
columns = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberNodes/self.shape.blockSize) lightVal = int(self.shape.numberNodes * self.shape.class1ratio * self.shape.vpn1)
heavyVal = int(self.shape.numberNodes * (1-self.shape.class1ratio) * self.shape.vpn2)
totalValidators = lightVal + heavyVal
rows = list(range(self.shape.blockSize)) * (int(totalValidators/self.shape.blockSize)+1)
columns = list(range(self.shape.blockSize)) * (int(totalValidators/self.shape.blockSize)+1)
offset = heavyVal*self.shape.chi
random.shuffle(rows) random.shuffle(rows)
random.shuffle(columns) random.shuffle(columns)
for i in range(self.shape.numberNodes): for i in range(self.shape.numberNodes):
if self.config.evenLineDistribution: if self.config.evenLineDistribution:
val = Validator(i, int(not i!=0), self.logger, self.shape, if i < int(heavyVal/self.shape.vpn2): # First start with the heavy nodes
rows[(i*self.shape.chi):((i+1)*self.shape.chi)], start = i *self.shape.chi*self.shape.vpn2
columns[(i*self.shape.chi):((i+1)*self.shape.chi)]) end = (i+1)*self.shape.chi*self.shape.vpn2
else: # Then the solo stakers
j = i - int(heavyVal/self.shape.vpn2)
start = offset+( j *self.shape.chi)
end = offset+((j+1)*self.shape.chi)
r = rows[start:end]
c = columns[start:end]
val = Validator(i, int(not i!=0), self.logger, self.shape, r, c, self.config.evenLineDistribution)
else: else:
val = Validator(i, int(not i!=0), self.logger, self.shape) val = Validator(i, int(not i!=0), self.logger, self.shape)
if i == self.proposerID: if i == self.proposerID:
@ -47,6 +59,7 @@ class Simulator:
else: else:
val.logIDs() val.logIDs()
self.validators.append(val) self.validators.append(val)
self.logger.debug("Validators initialized.", extra=self.format)
def initNetwork(self): def initNetwork(self):
"""It initializes the simulated network.""" """It initializes the simulated network."""
@ -59,6 +72,14 @@ class Simulator:
for id in v.columnIDs: for id in v.columnIDs:
columnChannels[id].append(v) columnChannels[id].append(v)
# Check rows/columns distribution
#totalR = 0
#totalC = 0
#for r in rowChannels:
# totalR += len(r)
#for c in columnChannels:
# totalC += len(c)
for id in range(self.shape.blockSize): for id in range(self.shape.blockSize):
# If the number of nodes in a channel is smaller or equal to the # If the number of nodes in a channel is smaller or equal to the
@ -178,7 +199,7 @@ class Simulator:
# log TX and RX statistics # log TX and RX statistics
statsTxInSlot = [v.statsTxInSlot for v in self.validators] statsTxInSlot = [v.statsTxInSlot for v in self.validators]
statsRxInSlot = [v.statsRxInSlot for v in self.validators] statsRxInSlot = [v.statsRxInSlot for v in self.validators]
self.logger.debug("step %d: TX_prod=%.1f, RX_prod=%.1f, TX_avg=%.1f, TX_max=%.1f, Rx_avg=%.1f, Rx_max=%.1f" % self.logger.debug("step %d: TX_prod=%.1f, RX_prod=%.1f, TX_avg=%.1f, TX_max=%.1f, Rx_avg=%.1f, Rx_max=%.1f" %
(steps, statsTxInSlot[0], statsRxInSlot[0], (steps, statsTxInSlot[0], statsRxInSlot[0],
mean(statsTxInSlot[1:]), max(statsTxInSlot[1:]), mean(statsTxInSlot[1:]), max(statsTxInSlot[1:]),
mean(statsRxInSlot[1:]), max(statsRxInSlot[1:])), extra=self.format) mean(statsRxInSlot[1:]), max(statsRxInSlot[1:])), extra=self.format)

12
DAS/validator.py
View File

@ -38,7 +38,7 @@ class Validator:
"""It returns the validator ID.""" """It returns the validator ID."""
return str(self.ID) return str(self.ID)
def __init__(self, ID, amIproposer, logger, shape, rows = None, columns = None): def __init__(self, ID, amIproposer, logger, shape, rows = None, columns = None, globalRandomness = True):
"""It initializes the validator with the logger shape and rows/columns. """It initializes the validator with the logger shape and rows/columns.
If rows/columns are specified these are observed, otherwise (default) If rows/columns are specified these are observed, otherwise (default)
@ -66,9 +66,13 @@ class Validator:
else: else:
#if shape.deterministic: #if shape.deterministic:
# random.seed(self.ID) # random.seed(self.ID)
vpn = self.shape.vpn1 if (self.ID <= shape.numberNodes * shape.class1ratio) else self.shape.vpn2 if globalRandomness:
self.rowIDs = rows if rows else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn) self.rowIDs = rows
self.columnIDs = columns if columns else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn) self.columnIDs = columns
else:
vpn = self.shape.vpn1 if (self.ID <= shape.numberNodes * shape.class1ratio) else self.shape.vpn2
self.rowIDs = rows if rows else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
self.columnIDs = columns if columns else unionOfSamples(range(self.shape.blockSize), self.shape.chi, vpn)
self.rowNeighbors = collections.defaultdict(dict) self.rowNeighbors = collections.defaultdict(dict)
self.columnNeighbors = collections.defaultdict(dict) self.columnNeighbors = collections.defaultdict(dict)