diff --git a/DAS/__init__.py b/DAS/__init__.py index ef4ca24..8dd11bf 100644 --- a/DAS/__init__.py +++ b/DAS/__init__.py @@ -1 +1,3 @@ from DAS.simulator import * +from DAS.configuration import * +from DAS.shape import * diff --git a/DAS/block.py b/DAS/block.py index 76379d8..aa5fe01 100644 --- a/DAS/block.py +++ b/DAS/block.py @@ -9,8 +9,8 @@ class Block: blockSize = 0 data = bitarray() - def __init__(self, size): - self.blockSize = size + def __init__(self, blockSize): + self.blockSize = blockSize self.data = zeros(self.blockSize*self.blockSize) def fill(self): diff --git a/DAS/configuration.py b/DAS/configuration.py new file mode 100644 index 0000000..91df16f --- /dev/null +++ b/DAS/configuration.py @@ -0,0 +1,48 @@ +#!/bin/python3 + +import configparser + +class Configuration: + + deterministic = 0 + + def __init__(self, fileName): + + config = configparser.RawConfigParser() + config.read(fileName) + + self.nvStart = int(config.get("Simulation Space", "numberValidatorStart")) + self.nvStop = int(config.get("Simulation Space", "numberValidatorStop")) + self.nvStep = int(config.get("Simulation Space", "numberValidatorStep")) + + self.blockSizeStart = int(config.get("Simulation Space", "blockSizeStart")) + self.blockSizeStop = int(config.get("Simulation Space", "blockSizeStop")) + self.blockSizeStep = int(config.get("Simulation Space", "blockSizeStep")) + + self.netDegreeStart = int(config.get("Simulation Space", "netDegreeStart")) + self.netDegreeStop = int(config.get("Simulation Space", "netDegreeStop")) + self.netDegreeStep = int(config.get("Simulation Space", "netDegreeStep")) + + self.failureRateStart = int(config.get("Simulation Space", "failureRateStart")) + self.failureRateStop = int(config.get("Simulation Space", "failureRateStop")) + self.failureRateStep = int(config.get("Simulation Space", "failureRateStep")) + + self.chiStart = int(config.get("Simulation Space", "chiStart")) + self.chiStop = int(config.get("Simulation Space", "chiStop")) + self.chiStep = int(config.get("Simulation Space", "chiStep")) + + self.numberRuns = int(config.get("Advanced", "numberRuns")) + self.deterministic = config.get("Advanced", "deterministic") + + if self.nvStop < (self.blockSizeStart*4): + print("ERROR: The number of validators cannot be lower than the block size * 4") + exit(1) + if self.chiStart < 1: + print("Chi has to be greater than 0") + exit(1) + if self.chiStop > self.blockSizeStart: + print("Chi (%d) has to be smaller or equal to block the size (%d)" % (self.chiStop, self.blockSizeStart)) + exit(1) + + + diff --git a/DAS/observer.py b/DAS/observer.py index f905af3..ad9052b 100644 --- a/DAS/observer.py +++ b/DAS/observer.py @@ -5,40 +5,40 @@ from DAS.block import * class Observer: block = [] - blockSize = 0 rows = [] columns = [] goldenData = [] broadcasted = [] + config = [] logger = [] - def __init__(self, blockSize, logger): + def __init__(self, logger, config): + self.config = config self.format = {"entity": "Observer"} - self.blockSize = blockSize self.logger = logger def reset(self): - self.block = [0] * self.blockSize * self.blockSize - self.goldenData = [0] * self.blockSize * self.blockSize - self.rows = [0] * self.blockSize - self.columns = [0] * self.blockSize - self.broadcasted = Block(self.blockSize) + self.block = [0] * self.config.blockSize * self.config.blockSize + self.goldenData = [0] * self.config.blockSize * self.config.blockSize + self.rows = [0] * self.config.blockSize + self.columns = [0] * self.config.blockSize + self.broadcasted = Block(self.config.blockSize) def checkRowsColumns(self, validators): for val in validators: - if val.proposer == 0: + if val.amIproposer == 0: for r in val.rowIDs: self.rows[r] += 1 for c in val.columnIDs: self.columns[c] += 1 - for i in range(self.blockSize): + for i in range(self.config.blockSize): self.logger.debug("Row/Column %d have %d and %d validators assigned." % (i, self.rows[i], self.columns[i]), extra=self.format) if self.rows[i] == 0 or self.columns[i] == 0: self.logger.warning("There is a row/column that has not been assigned", extra=self.format) def setGoldenData(self, block): - for i in range(self.blockSize*self.blockSize): + for i in range(self.config.blockSize*self.config.blockSize): self.goldenData[i] = block.data[i] def checkBroadcasted(self): @@ -54,7 +54,7 @@ class Observer: arrived = 0 expected = 0 for val in validators: - if val.proposer == 0: + if val.amIproposer == 0: (a, e) = val.checkStatus() arrived += a expected += e diff --git a/DAS/results.py b/DAS/results.py new file mode 100644 index 0000000..8468b09 --- /dev/null +++ b/DAS/results.py @@ -0,0 +1,17 @@ +#!/bin/python3 + + +class Result: + + config = [] + missingVector = [] + blockAvailable = -1 + + def __init__(self, config): + self.config = config + self.blockAvailable = -1 + self.missingVector = [] + + + def addMissing(self, missingVector): + self.missingVector = missingVector diff --git a/DAS/shape.py b/DAS/shape.py new file mode 100644 index 0000000..2918422 --- /dev/null +++ b/DAS/shape.py @@ -0,0 +1,19 @@ +#!/bin/python3 + +class Shape: + numberValidators = 0 + failureRate = 0 + blockSize = 0 + netDegree = 0 + chi = 0 + + def __init__(self, blockSize, numberValidators, failureRate, chi, netDegree): + self.numberValidators = numberValidators + self.failureRate = failureRate + self.blockSize = blockSize + self.netDegree = netDegree + self.chi = chi + + + + diff --git a/DAS/simulator.py b/DAS/simulator.py index fcfeb2e..3701167 100644 --- a/DAS/simulator.py +++ b/DAS/simulator.py @@ -1,40 +1,39 @@ #!/bin/python import networkx as nx -import logging +import logging, random from datetime import datetime from DAS.tools import * +from DAS.results import * from DAS.observer import * from DAS.validator import * class Simulator: - chi = 8 - blockSize = 256 - numberValidators = 8192 - failureRate = 0 proposerID = 0 logLevel = logging.INFO - deterministic = 0 validators = [] glob = [] + result = [] + shape = [] logger = [] format = {} - steps = 0 - def __init__(self, failureRate): - self.failureRate = failureRate + def __init__(self, shape): + self.shape = shape self.format = {"entity": "Simulator"} - self.steps = 0 + self.result = Result(self.shape) def initValidators(self): - if not self.deterministic: - random.seed(datetime.now()) - self.glob = Observer(self.blockSize, self.logger) + self.glob = Observer(self.logger, self.shape) self.glob.reset() self.validators = [] - for i in range(self.numberValidators): - val = Validator(i, self.chi, self.blockSize, int(not i!=0), self.failureRate, self.deterministic, self.logger) + rows = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberValidators/self.shape.blockSize) + columns = list(range(self.shape.blockSize)) * int(self.shape.chi*self.shape.numberValidators/self.shape.blockSize) + random.shuffle(rows) + random.shuffle(columns) + for i in range(self.shape.numberValidators): + val = Validator(i, int(not i!=0), self.logger, self.shape, rows, columns) if i == self.proposerID: val.initBlock() self.glob.setGoldenData(val.block) @@ -42,27 +41,34 @@ class Simulator: val.logIDs() self.validators.append(val) - def initNetwork(self, d=6): - rowChannels = [[] for i in range(self.blockSize)] - columnChannels = [[] for i in range(self.blockSize)] + def initNetwork(self): + self.shape.netDegree = 6 + rowChannels = [[] for i in range(self.shape.blockSize)] + columnChannels = [[] for i in range(self.shape.blockSize)] for v in self.validators: for id in v.rowIDs: rowChannels[id].append(v) for id in v.columnIDs: columnChannels[id].append(v) - for id in range(self.blockSize): - G = nx.random_regular_graph(d, len(rowChannels[id])) + for id in range(self.shape.blockSize): + + if (len(rowChannels[id]) < self.shape.netDegree): + self.logger.error("Graph degree higher than %d" % len(rowChannels[id]), extra=self.format) + G = nx.random_regular_graph(self.shape.netDegree, len(rowChannels[id])) if not nx.is_connected(G): - self.logger.error("graph not connected for row %d !" % id, extra=self.format) + self.logger.error("Graph not connected for row %d !" % id, extra=self.format) for u, v in G.edges: val1=rowChannels[id][u] val2=rowChannels[id][v] val1.rowNeighbors[id].append(val2) val2.rowNeighbors[id].append(val1) - G = nx.random_regular_graph(d, len(columnChannels[id])) + + if (len(columnChannels[id]) < self.shape.netDegree): + self.logger.error("Graph degree higher than %d" % len(columnChannels[id]), extra=self.format) + G = nx.random_regular_graph(self.shape.netDegree, len(columnChannels[id])) if not nx.is_connected(G): - self.logger.error("graph not connected for column %d !" % id, extra=self.format) + self.logger.error("Graph not connected for column %d !" % id, extra=self.format) for u, v in G.edges: val1=columnChannels[id][u] val2=columnChannels[id][v] @@ -78,20 +84,27 @@ class Simulator: logger.addHandler(ch) self.logger = logger - def resetFailureRate(self, failureRate): - self.failureRate = failureRate + + def resetShape(self, shape): + self.shape = shape + for val in self.validators: + val.shape.failureRate = shape.failureRate + val.shape.chi = shape.chi + def run(self): self.glob.checkRowsColumns(self.validators) self.validators[self.proposerID].broadcastBlock() arrived, expected = self.glob.checkStatus(self.validators) missingSamples = expected - arrived - self.steps = 0 + missingVector = [] + steps = 0 while(missingSamples > 0): + missingVector.append(missingSamples) oldMissingSamples = missingSamples - for i in range(1,self.numberValidators): + for i in range(1,self.shape.numberValidators): self.validators[i].receiveRowsColumns() - for i in range(1,self.numberValidators): + for i in range(1,self.shape.numberValidators): self.validators[i].restoreRows() self.validators[i].restoreColumns() self.validators[i].sendRows() @@ -102,18 +115,21 @@ class Simulator: arrived, expected = self.glob.checkStatus(self.validators) missingSamples = expected - arrived missingRate = missingSamples*100/expected - self.logger.info("step %d, missing %d of %d (%0.02f %%)" % (self.steps, missingSamples, expected, missingRate), extra=self.format) + self.logger.debug("step %d, missing %d of %d (%0.02f %%)" % (steps, missingSamples, expected, missingRate), extra=self.format) if missingSamples == oldMissingSamples: break elif missingSamples == 0: break else: - self.steps += 1 + steps += 1 + self.result.addMissing(missingVector) if missingSamples == 0: - self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (self.steps, self.failureRate), extra=self.format) - return 0 + self.result.blockAvailable = 1 + self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (steps, self.shape.failureRate), extra=self.format) + return self.result else: - self.logger.debug("The block cannot be recovered, failure rate %d!" % self.failureRate, extra=self.format) - return 1 + self.result.blockAvailable = 0 + self.logger.debug("The block cannot be recovered, failure rate %d!" % self.shape.failureRate, extra=self.format) + return self.result diff --git a/DAS/validator.py b/DAS/validator.py index eaeb0a0..af16df5 100644 --- a/DAS/validator.py +++ b/DAS/validator.py @@ -10,44 +10,40 @@ from bitarray.util import zeros class Validator: ID = 0 - chi = 0 + amIproposer = 0 + shape = [] format = {} - blocksize = 0 - proposer = 0 - failureRate = 0 logger = [] - def __init__(self, ID, chi, blockSize, proposer, failureRate, deterministic, logger): + def __init__(self, ID, amIproposer, logger, shape, rows, columns): + self.shape = shape FORMAT = "%(levelname)s : %(entity)s : %(message)s" self.ID = ID self.format = {"entity": "Val "+str(self.ID)} - self.blockSize = blockSize - self.block = Block(blockSize) - self.receivedBlock = Block(blockSize) - self.proposer = proposer - self.failureRate = failureRate + self.block = Block(self.shape.blockSize) + self.receivedBlock = Block(self.shape.blockSize) + self.amIproposer = amIproposer self.logger = logger - if chi < 1: + if self.shape.chi < 1: self.logger.error("Chi has to be greater than 0", extra=self.format) - elif chi > blockSize: + elif self.shape.chi > self.shape.blockSize: self.logger.error("Chi has to be smaller than %d" % blockSize, extra=self.format) else: - self.chi = chi - if proposer: - self.rowIDs = range(blockSize) - self.columnIDs = range(blockSize) + if amIproposer: + self.rowIDs = range(shape.blockSize) + self.columnIDs = range(shape.blockSize) else: - self.rowIDs = [] - self.columnIDs = [] - if deterministic: - random.seed(self.ID) - self.rowIDs = random.sample(range(self.blockSize), self.chi) - self.columnIDs = random.sample(range(self.blockSize), self.chi) + self.rowIDs = rows[(self.ID*self.shape.chi):(self.ID*self.shape.chi + self.shape.chi)] + self.columnIDs = rows[(self.ID*self.shape.chi):(self.ID*self.shape.chi + self.shape.chi)] + #if shape.deterministic: + # random.seed(self.ID) + #self.rowIDs = random.sample(range(self.shape.blockSize), self.shape.chi) + #self.columnIDs = random.sample(range(self.shape.blockSize), self.shape.chi) self.rowNeighbors = collections.defaultdict(list) self.columnNeighbors = collections.defaultdict(list) def logIDs(self): - if self.proposer == 1: + if self.amIproposer == 1: self.logger.warning("I am a block proposer."% self.ID) else: self.logger.debug("Selected rows: "+str(self.rowIDs), extra=self.format) @@ -55,30 +51,30 @@ class Validator: def initBlock(self): self.logger.debug("I am a block proposer.", extra=self.format) - self.block = Block(self.blockSize) + self.block = Block(self.shape.blockSize) self.block.fill() #self.block.print() def broadcastBlock(self): - if self.proposer == 0: + if self.amIproposer == 0: self.logger.error("I am NOT a block proposer", extra=self.format) else: self.logger.debug("Broadcasting my block...", extra=self.format) - order = [i for i in range(self.blockSize * self.blockSize)] + order = [i for i in range(self.shape.blockSize * self.shape.blockSize)] random.shuffle(order) while(order): i = order.pop() - if (random.randint(0,99) >= self.failureRate): + if (random.randint(0,99) >= self.shape.failureRate): self.block.data[i] = 1 else: self.block.data[i] = 0 nbFailures = self.block.data.count(0) - measuredFailureRate = nbFailures * 100 / (self.blockSize * self.blockSize) - self.logger.info("Number of failures: %d (%0.02f %%)", nbFailures, measuredFailureRate, extra=self.format) + measuredFailureRate = nbFailures * 100 / (self.shape.blockSize * self.shape.blockSize) + self.logger.debug("Number of failures: %d (%0.02f %%)", nbFailures, measuredFailureRate, extra=self.format) #broadcasted.print() - for id in range(self.blockSize): + for id in range(self.shape.blockSize): self.sendColumn(id) - for id in range(self.blockSize): + for id in range(self.shape.blockSize): self.sendRow(id) def getColumn(self, index): @@ -101,7 +97,7 @@ class Validator: def receiveRowsColumns(self): - if self.proposer == 1: + if self.amIproposer == 1: self.logger.error("I am a block proposer", extra=self.format) else: self.logger.debug("Receiving the data...", extra=self.format) @@ -124,7 +120,7 @@ class Validator: n.receiveRow(rowID, line) def sendRows(self): - if self.proposer == 1: + if self.amIproposer == 1: self.logger.error("I am a block proposer", extra=self.format) else: self.logger.debug("Sending restored rows...", extra=self.format) @@ -132,7 +128,7 @@ class Validator: self.sendRow(r) def sendColumns(self): - if self.proposer == 1: + if self.amIproposer == 1: self.logger.error("I am a block proposer", extra=self.format) else: self.logger.debug("Sending restored columns...", extra=self.format) diff --git a/README.md b/README.md index 1b41851..97846ce 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -# DAS Research +# DAS Research -This repository hosts all the research on DAS for the collaboration between Codex and the EF. +This repository hosts all the research on DAS for the collaboration between Codex and the EF. ## Prepare the environment @@ -16,11 +16,11 @@ $ cd das-research ``` $ python3 -m venv myenv $ source myenv/bin/activate -$ pip3 install -r DAS/requeriments.txt +$ pip3 install -r DAS/requirements.txt ``` ## Run the simulator ``` -$ python3 study.py +$ python3 study.py config.das ``` diff --git a/config.das b/config.das new file mode 100644 index 0000000..f5d608e --- /dev/null +++ b/config.das @@ -0,0 +1,27 @@ +[Simulation Space] + +numberValidatorStart = 256 +numberValidatorStop = 512 +numberValidatorStep = 128 + +failureRateStart = 10 +failureRateStop = 90 +failureRateStep = 40 + +blockSizeStart = 32 +blockSizeStop = 64 +blockSizeStep = 16 + +netDegreeStart = 6 +netDegreeStop = 8 +netDegreeStep = 1 + +chiStart = 4 +chiStop = 8 +chiStep = 2 + + +[Advanced] + +deterministic = 0 +numberRuns = 2 diff --git a/study.py b/study.py index 04578de..ae27e5c 100644 --- a/study.py +++ b/study.py @@ -1,35 +1,45 @@ #! /bin/python3 -import time +import time, sys from DAS import * def study(): - sim = Simulator(0) + if len(sys.argv) < 2: + print("You need to pass a configuration file in parameter") + exit(1) + + config = Configuration(sys.argv[1]) + sim = Simulator(config) sim.initLogger() - maxTries = 10 - step = 20 - frRange = [] - resultRange = [] + results = [] simCnt = 0 + sim.logger.info("Starting simulations:", extra=sim.format) start = time.time() - for fr in range(0, 100, step): - if fr % 10 == 0: - sim.logger.info("Failure rate %d %% ..." % fr, extra=sim.format) - sim.resetFailureRate(fr) - result = 0 - for i in range(maxTries): - sim.initValidators() - sim.initNetwork() - result += sim.run() - simCnt += 1 - frRange.append(fr) - resultRange.append((maxTries-result)*100/maxTries) + + for run in range(config.numberRuns): + for fr in range(config.failureRateStart, config.failureRateStop+1, config.failureRateStep): + for chi in range(config.chiStart, config.chiStop+1, config.chiStep): + for blockSize in range(config.blockSizeStart, config.blockSizeStop+1, config.blockSizeStep): + for nv in range(config.nvStart, config.nvStop+1, config.nvStep): + for netDegree in range(config.netDegreeStart, config.netDegreeStop+1, config.netDegreeStep): + + if not config.deterministic: + random.seed(datetime.now()) + + shape = Shape(blockSize, nv, fr, chi, netDegree) + sim.resetShape(shape) + sim.initValidators() + sim.initNetwork() + result = sim.run() + sim.logger.info("Run %d, FR: %d %%, Chi: %d, BlockSize: %d, Nb.Val: %d, netDegree: %d ... Block Available: %d" % (run, fr, chi, blockSize, nv, netDegree, result.blockAvailable), extra=sim.format) + results.append(result) + simCnt += 1 + end = time.time() sim.logger.info("A total of %d simulations ran in %d seconds" % (simCnt, end-start), extra=sim.format) - for i in range(len(frRange)): - sim.logger.info("For failure rate of %d we got %d %% success rate in DAS!" % (frRange[i], resultRange[i]), extra=sim.format) + study()