diff --git a/DAS/simulator.py b/DAS/simulator.py index 06ebd8e..30c0d86 100644 --- a/DAS/simulator.py +++ b/DAS/simulator.py @@ -30,15 +30,27 @@ class Simulator: self.glob.reset() self.validators = [] 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(columns) for i in range(self.shape.numberNodes): if self.config.evenLineDistribution: - val = Validator(i, int(not i!=0), self.logger, self.shape, - rows[(i*self.shape.chi):((i+1)*self.shape.chi)], - columns[(i*self.shape.chi):((i+1)*self.shape.chi)]) + if i < int(heavyVal/self.shape.vpn2): # First start with the heavy nodes + start = i *self.shape.chi*self.shape.vpn2 + 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) else: val = Validator(i, int(not i!=0), self.logger, self.shape) if i == self.proposerID: @@ -47,6 +59,7 @@ class Simulator: else: val.logIDs() self.validators.append(val) + self.logger.debug("Validators initialized.", extra=self.format) def initNetwork(self): """It initializes the simulated network.""" @@ -59,6 +72,14 @@ class Simulator: for id in v.columnIDs: 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): # 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 statsTxInSlot = [v.statsTxInSlot 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], mean(statsTxInSlot[1:]), max(statsTxInSlot[1:]), mean(statsRxInSlot[1:]), max(statsRxInSlot[1:])), extra=self.format) diff --git a/config_example.py b/config_example.py index b54dff1..af55fc2 100644 --- a/config_example.py +++ b/config_example.py @@ -28,7 +28,7 @@ numJobs = 3 # distribute rows/columns evenly between validators (True) # or generate it using local randomness (False) -evenLineDistribution = False +evenLineDistribution = True # Number of simulation runs with the same parameters for statistical relevance runs = range(10)