def drawEvenGraph(nodes, tasks):
xs = []
ys = []
fx = []
fy = []
i = 0
for _ in range(nodes):
n = next(generateFileIDs())
n = i / nodes * MAX
x = math.sin(2 * math.pi * n / MAX)
y = math.cos(2 * math.pi * n / MAX)
xs.append(x)
ys.append(y)
i += 1
for _ in range(tasks):
n = next(generateFileIDs())
x = math.sin(2 * math.pi * n / MAX)
y = math.cos(2 * math.pi * n / MAX)
fx.append(x)
fy.append(y)
#plt.axes([-1.0,1.0,-1.0,1.0] )
plt.plot(xs, ys, 'ro')
plt.plot(fx, fy, 'b+')
plt.show()
def drawEvenGraph(nodes, tasks):
xs = []
ys = []
fx = []
fy = []
i = 0
for _ in range(nodes):
n = next(generateFileIDs())
n = i/nodes * MAX
x = math.sin(2*math.pi*n/ MAX)
y = math.cos(2*math.pi*n/ MAX)
xs.append(x)
ys.append(y)
i += 1
for _ in range(tasks):
n = next(generateFileIDs())
x = math.sin(2*math.pi*n/ MAX)
y = math.cos(2*math.pi*n/ MAX)
fx.append(x)
fy.append(y)
#plt.axes([-1.0,1.0,-1.0,1.0] )
plt.plot(xs,ys, 'ro')
plt.plot(fx,fy, 'b+')
plt.show()
def setupSimulation(self, strategy= None, homogeneity= None, workMeasurement=None , numNodes = 100, numTasks = 10000, churnRate = 0.01, adaptationRate = 5, maxSybil = 10, sybilThreshold = 0.1, numSuccessors=5):
self.strategy = strategy
self.nodeIDs = [] # the network topology
self.superNodes = [] # the nodes that will do the sybilling
self.sybils = {} # (node, [] of sybils)
self.pool = []
self.nodes = {} # (id: int, Node: object)
self.numNodes = numNodes
self.numTasks = numTasks
self.churnRate = churnRate # chance of join/leave per tick per node
self.adaptationRate = adaptationRate # number of ticks
self.maxSybil = maxSybil
self.sybilThreshold = int((self.numTasks/self.numNodes) * sybilThreshold)
self.numSuccessors = numSuccessors
self.homogeneity = homogeneity
self.workMeasurement = workMeasurement
self.perfectTime = self.numTasks/self.numNodes
self.numDone = 0
self.time = 0
self.numSybils = 0
#self.nodeIDs = builder.createStaticIDs(self.numNodes)
for _ in range(self.numNodes):
id = next(builder.generateFileIDs())
self.nodeIDs.append(id)
self.superNodes.append(id)
self.addToPool(self.numNodes)
self.nodeIDs = sorted(self.nodeIDs)
self.superNodes = sorted(self.superNodes)
#print("Creating Nodes")
expectedWorkPerTick = 0
for id in self.superNodes:
n = SimpleNode(id, self.maxSybil, self.homogeneity)
self.nodes[id] = n
if workMeasurement == "perStrength":
expectedWorkPerTick += n.strength
if workMeasurement == "perStrength":
self.perfectTime = self.numTasks/expectedWorkPerTick
#print("Creating Tasks")
for key in [next(builder.generateFileIDs()) for _ in range(self.numTasks)]:
id, _ = self.whoGetsFile(key)
#print(id % 10000)
self.nodes[id].addTask(key)
def addSybil(self, superNode, sybilID = None):
if sybilID is None:
sybilID = next(builder.generateFileIDs())
if superNode not in self.sybils:
self.sybils[superNode] = [sybilID]
else:
self.sybils[superNode].append(sybilID)
self.nodes[sybilID] = self.nodes[superNode]
self.numSybils += 1
self.insertWorker(sybilID, self.nodes[sybilID])
def addSybil(self, superNode, sybilID=None):
if sybilID is None:
sybilID = next(builder.generateFileIDs())
if superNode not in self.sybils:
self.sybils[superNode] = [sybilID]
else:
self.sybils[superNode].append(sybilID)
self.nodes[sybilID] = self.nodes[superNode]
self.numSybils += 1
self.insertWorker(sybilID, self.nodes[sybilID])
def addToPool(self, num):
# Adds num nodes to the pool of possible joining nodes
for _ in range(num):
x = next(builder.generateFileIDs())
assert(x not in self.nodeIDs)
self.pool.append(x)
def addToPool(self, num):
# Adds num nodes to the pool of possible joining nodes
for _ in range(num):
x = next(builder.generateFileIDs())
assert (x not in self.nodeIDs)
self.pool.append(x)
def setupSimulation(self,
strategy=None,
homogeneity=None,
workMeasurement=None,
numNodes=100,
numTasks=10000,
churnRate=0.01,
adaptationRate=5,
maxSybil=10,
sybilThreshold=0.1,
numSuccessors=5):
self.strategy = strategy
self.nodeIDs = [] # the network topology
self.superNodes = [] # the nodes that will do the sybilling
self.sybils = {} # (node, [] of sybils)
self.pool = []
self.nodes = {} # (id: int, Node: object)
self.numNodes = numNodes
self.numTasks = numTasks
self.churnRate = churnRate # chance of join/leave per tick per node
self.adaptationRate = adaptationRate # number of ticks
self.maxSybil = maxSybil
self.sybilThreshold = int(
(self.numTasks / self.numNodes) * sybilThreshold)
self.numSuccessors = numSuccessors
self.homogeneity = homogeneity
self.workMeasurement = workMeasurement
self.perfectTime = self.numTasks / self.numNodes
self.numDone = 0
self.time = 0
self.numSybils = 0
#self.nodeIDs = builder.createStaticIDs(self.numNodes)
for _ in range(self.numNodes):
id = next(builder.generateFileIDs())
self.nodeIDs.append(id)
self.superNodes.append(id)
self.addToPool(self.numNodes)
self.nodeIDs = sorted(self.nodeIDs)
self.superNodes = sorted(self.superNodes)
#print("Creating Nodes")
expectedWorkPerTick = 0
for id in self.superNodes:
n = SimpleNode(id, self.maxSybil, self.homogeneity)
self.nodes[id] = n
if workMeasurement == "perStrength":
expectedWorkPerTick += n.strength
if workMeasurement == "perStrength":
self.perfectTime = self.numTasks / expectedWorkPerTick
#print("Creating Tasks")
for key in [
next(builder.generateFileIDs()) for _ in range(self.numTasks)
]:
id, _ = self.whoGetsFile(key)
#print(id % 10000)
self.nodes[id].addTask(key)