adding scenario configs

Signed-off-by: Csaba Kiraly <csaba.kiraly@gmail.com>

config_failuremodel.py

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+"""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
+
+dumpXML = 1
+
+# save progress vectors to XML
+saveProgress = 1
+# plot progress for each run to PNG
+plotProgress = 1
+
+visualization = 1
+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 = range(1)
+
+# Number of validators
+numberNodes = [1000]
+
+failureModels = ["random", "sequential", "MEP", "MEP+1", "DEP", "DEP+1", "MREP", "MREP-1"]
+
+# Percentage of block not released by producer
+failureRates = [50]
+
+# Block size in one dimension in segments. Block is blockSizes * blockSizes segments.
+blockSizes = [256]
+
+# Per-topic mesh neighborhood size
+netDegrees = [4]
+
+gsChannelFailureRate = 0
+gsEdgeFailureRate = 0
+
+# number of rows and columns a validator is interested in
+chis = [1,2,3]
+
+# ratio of class1 nodes (see below for parameters per class)
+class1ratios = [0.8]
+
+# Number of validators per beacon node
+validatorsPerNode1 = [1]
+validatorsPerNode2 = [100]
+
+# Set uplink bandwidth. In segments (~560 bytes) per timestep (50ms?)
+# 1 Mbps ~= 1e6 / 20 / 8 / 560 ~= 11
+bwUplinksProd = [200]
+bwUplinks1 = [10]
+bwUplinks2 = [200]
+
+# Step duration in milliseconds (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 = 10
+
+def nextShape():
+    for run, fm, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
+        runs, failureModels, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
+        # Network Degree has to be an even number
+        if netDegree % 2 == 0:
+            shape = Shape(blockSize, nn, fm, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
+            yield shape

config_scenario1.py

@@ -0,0 +1,97 @@
+"""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
+
+dumpXML = 1
+
+# save progress vectors to XML
+saveProgress = 1
+# plot progress for each run to PNG
+plotProgress = 1
+
+visualization = 1
+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 = range(1)
+
+# Number of validators
+numberNodes = [8000]
+
+#failureModels = ["random", "sequential", "MEP", "MEP+1", "DEP", "DEP+1", "MREP", "MREP-1"]
+failureModels = ["random"]
+
+# Percentage of block not released by producer
+failureRates = [0]
+
+# Block size in one dimension in segments. Block is blockSizes * blockSizes segments.
+blockSizes = [512]
+
+# Per-topic mesh neighborhood size
+netDegrees = [4]
+
+gsChannelFailureRate = 0
+gsEdgeFailureRate = 0
+
+# number of rows and columns a validator is interested in
+chis = [2]
+
+# ratio of class1 nodes (see below for parameters per class)
+class1ratios = [0.8]
+
+# Number of validators per beacon node
+validatorsPerNode1 = [1]
+validatorsPerNode2 = [500]
+
+# Set uplink bandwidth. In segments (~560 bytes) per timestep (50ms?)
+# 1 Mbps ~= 1e6 / 20 / 8 / 560 ~= 11
+bwUplinksProd = [1000]
+bwUplinks1 = [50]
+bwUplinks2 = [1000]
+
+# Step duration in milliseconds (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 = 4
+
+def nextShape():
+    for run, fm, fr, class1ratio, chi, vpn1, vpn2, blockSize, nn, netDegree, bwUplinkProd, bwUplink1, bwUplink2 in itertools.product(
+        runs, failureModels, failureRates, class1ratios, chis, validatorsPerNode1, validatorsPerNode2, blockSizes, numberNodes, netDegrees, bwUplinksProd, bwUplinks1, bwUplinks2):
+        # Network Degree has to be an even number
+        if netDegree % 2 == 0:
+            shape = Shape(blockSize, nn, fm, fr, class1ratio, chi, vpn1, vpn2, netDegree, bwUplinkProd, bwUplink1, bwUplink2, run)
+            yield shape