WIP: Gossipsub to full nodes (as in SubnetDAS)

DAS/simulator.py

@@ -48,6 +48,8 @@ def initValidators(self):
         self.glob = Observer(self.logger, self.shape)
         self.validators = []
         if self.config.evenLineDistribution:
+            self.logger.error("evenLineDistribution NOT YET SUPPORTED.", extra=self.format)
+            exit(1)
 
             lightNodes = int(self.shape.numberNodes * self.shape.class1ratio)
             heavyNodes = self.shape.numberNodes - lightNodes
@@ -102,12 +104,18 @@ def initValidators(self):
                 elif self.shape.chiR > self.shape.blockSizeC:
                     self.logger.error("ChiR has to be smaller than %d" % self.shape.blockSizeC)
 
-                vs = []
                 nodeClass = 1 if (i <= self.shape.numberNodes * self.shape.class1ratio) else 2
-                vpn = self.shape.vpn1 if (nodeClass == 1) else self.shape.vpn2
-                for v in range(vpn):
-                    vs.append(initValidator(self.shape.blockSizeC, self.shape.chiR, self.shape.blockSizeR, self.shape.chiC))
-                val = Node(i, int(not i!=0), self.logger, self.shape, self.config, vs)
+                if nodeClass == 1: # nodes
+                    validators = []
+                    rows = set()
+                    columns = set(random.sample(range(self.shape.blockSizeR), self.shape.chiC))
+                    val = Node(i, int(not i!=0), self.logger, self.shape, self.config, validators, rows, columns)
+                else: # validators
+                    validators = []
+                    vpn = self.shape.vpn1 if (nodeClass == 1) else self.shape.vpn2
+                    for _ in range(vpn):
+                        validators.append(initValidator(self.shape.blockSizeC, self.shape.chiR, self.shape.blockSizeR, 0))
+                    val = Node(i, int(not i!=0), self.logger, self.shape, self.config, validators)
             if i == self.proposerID:
                 val.initBlock()
             else:

subnetDas.py

@@ -0,0 +1,119 @@
+"""Example configuration file
+
+This file illustrates how to define options and simulation parameter ranges.
+It also defines the traversal order of the simulation space. As the file
+extension suggests, configuration is pure python code, allowing complex
+setups. Use at your own risk.
+
+To use this example, run
+   python3 study.py config_example
+
+Otherwise copy it and modify as needed. The default traversal order defined
+in the nested loop of nextShape() is good for most cases, but customizable
+if needed.
+"""
+
+import logging
+import itertools
+import numpy as np
+from DAS.shape import Shape
+
+# Dump results into XML files
+dumpXML = 1
+
+# save progress and row/column distribution vectors to XML
+saveProgress = 1
+
+# plot progress for each run to PNG
+plotProgress = 1
+
+# Save row and column distributions
+saveRCdist = 1
+
+# Plot all figures
+visualization = 1
+
+# Verbosity level
+logLevel = logging.INFO
+
+# number of parallel workers. -1: all cores; 1: sequential
+# for more details, see joblib.Parallel
+numJobs = -1
+
+# distribute rows/columns evenly between validators (True)
+# or generate it using local randomness (False)
+evenLineDistribution = False
+
+# Number of simulation runs with the same parameters for statistical relevance
+runs = [1]
+
+# Number of validators
+numberNodes = [1000]
+
+# select failure model between: "random, sequential, MEP, MEP+1, DEP, DEP+1, MREP, MREP-1"
+failureModels = ["random"]
+
+# Percentage of block not released by producer
+failureRates = [0]
+
+# Block size parameters. 
+## columnsN: number of columns (or row size)
+## columnsK: original row size, before erasure coding
+## BlockSizeC: number of rows (or column size)
+## BlockSizeCK: original number of rows, before erasure coding            
+columnsK = 1024
+columnsN = 2 * columnsK
+rowsK = 128
+rowsN = rowsK
+
+# Per-topic mesh neighborhood size
+netDegrees = [8]
+
+# number of rows and columns a validator is interested in
+chiR = 1 # Number of rows observed by validators (not Beacon nodes with validators, but individual validators)
+chiC = 16 # Number of columns observed by full nodes
+
+# ratio of class1 nodes (see below for parameters per class)
+class1ratios = [.5]
+
+# Number of validators per beacon node
+validatorsPerNode1 = [0] # Full nodes, without validators 
+validatorsPerNode2 = [500] # Nodes with validators
+
+# Set uplink bandwidth in megabits/second
+bwUplinksProd = [200]
+bwUplinks1 = [10] # Full nodes
+bwUplinks2 = [200] # Nodes with validators
+
+# Step duration in miliseconds (Classic RTT is about 100ms)
+stepDuration = 50
+
+# Segment size in bytes (with proof)
+segmentSize = 560
+
+# Set to True if you want your run to be deterministic, False if not
+deterministic = True
+
+# If your run is deterministic you can decide the random seed. This is ignore otherwise.
+randomSeed = "DAS"
+
+# Number of steps without progress to stop simulation
+steps4StopCondition = 7
+
+# Number of validators ready to assume block is available
+successCondition = 0.9
+
+# If True, print diagnostics when the block is not available
+diagnostics = False
+
+# True to save git diff and git commit
+saveGit = False
+
+def nextShape():
+    for run, fm, fr, class1ratio, vpn1, vpn2, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
+        runs, failureModels, failureRates, class1ratios, validatorsPerNode1, validatorsPerNode2, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
+        # Network Degree has to be an even number
+        if netDegree % 2 == 0:
+
+            shape = Shape(columnsN, columnsK, rowsN, rowsK, nn, fm, fr, class1ratio, chiR, chiC, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
+            yield shape