#!/bin/python import networkx as nx import logging from datetime import datetime from DAS.tools import * from DAS.results import * from DAS.observer import * from DAS.validator import * class Simulator: proposerID = 0 logLevel = logging.INFO validators = [] glob = [] result = [] config = [] logger = [] format = {} def __init__(self, config): self.config = config self.format = {"entity": "Simulator"} self.result = Result(self.config) def initValidators(self): if not self.config.deterministic: random.seed(datetime.now()) self.glob = Observer(self.logger, self.config) self.glob.reset() self.validators = [] for i in range(self.config.numberValidators): val = Validator(i, int(not i!=0), self.logger, self.config) if i == self.proposerID: val.initBlock() self.glob.setGoldenData(val.block) else: val.logIDs() self.validators.append(val) def initNetwork(self, d=6): rowChannels = [[] for i in range(self.config.blockSize)] columnChannels = [[] for i in range(self.config.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.config.blockSize): G = nx.random_regular_graph(d, len(rowChannels[id])) if not nx.is_connected(G): 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 not nx.is_connected(G): 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] val1.columnNeighbors[id].append(val2) val2.columnNeighbors[id].append(val1) def initLogger(self): logger = logging.getLogger("DAS") logger.setLevel(self.logLevel) ch = logging.StreamHandler() ch.setLevel(self.logLevel) ch.setFormatter(CustomFormatter()) logger.addHandler(ch) self.logger = logger def resetFailureRate(self, failureRate): self.config.failureRate = failureRate for val in self.validators: val.config.failureRate = failureRate def resetChi(self, chi): self.config.chi = chi for val in self.validators: val.config.chi = chi def run(self): self.glob.checkRowsColumns(self.validators) self.validators[self.proposerID].broadcastBlock() arrived, expected = self.glob.checkStatus(self.validators) missingSamples = expected - arrived missingVector = [] steps = 0 while(missingSamples > 0): missingVector.append(missingSamples) oldMissingSamples = missingSamples for i in range(1,self.config.numberValidators): self.validators[i].receiveRowsColumns() for i in range(1,self.config.numberValidators): self.validators[i].restoreRows() self.validators[i].restoreColumns() self.validators[i].sendRows() self.validators[i].sendColumns() self.validators[i].logRows() self.validators[i].logColumns() arrived, expected = self.glob.checkStatus(self.validators) missingSamples = expected - arrived missingRate = missingSamples*100/expected 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: steps += 1 self.result.addMissing(missingVector) if missingSamples == 0: self.result.blockAvailable = 1 self.logger.debug("The entire block is available at step %d, with failure rate %d !" % (steps, self.config.failureRate), extra=self.format) return self.result else: self.result.blockAvailable = 0 self.logger.debug("The block cannot be recovered, failure rate %d!" % self.config.failureRate, extra=self.format) return self.result