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Plots.py
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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
'''
This module provides to plot the results based on the produced .csv files after the experiments.
It can be easily extended to different calculations based on the conducted research.
'''
class Plots(object):
def __init__(self, numberOfServers,
numberOfUsers,
numberOfUAVs,
uavFlyPolicy,
uavWaitingPolicy,
):
self.appResults = pd.read_csv("AppResults.csv")
self.edgeResults = pd.read_csv("EdgeResults.csv")
self.uavResults = pd.read_csv("UavResults.csv")
self.scenarioResults = pd.read_csv("ScenarioResults.csv")
self.numberOfEdgeServersList = numberOfServers
self.numberOfUsersList = numberOfUsers
self.numberOfUAVsList = numberOfUAVs
self.uavFlyPoliciesList = uavFlyPolicy
self.uavWaitingPoliciesList = uavWaitingPolicy
self.apps = ["Entertainment", "Multimedia", "Rendering", "ImageClassification"]
def getEdgeCloudUAVRatio(self, numberOfUAVs):
edge = []
uav = []
cloud = []
for i, numberOfUsers in enumerate(self.numberOfUsersList):
testRes = self.appResults.loc[(self.appResults["NumberOfUsers"] == numberOfUsers)
& (self.appResults["NumberOfUAVs"] == numberOfUAVs)
& (self.appResults["UAVWaitingPolicy"] == 100)]
edge.append(testRes["OffloadedToEdge"].sum() / testRes["TotalTasks"].sum())
uav.append(testRes["OffloadedToUAV"].sum() / testRes["TotalTasks"].sum())
cloud.append(testRes["OffloadedToCloud"].sum() / testRes["TotalTasks"].sum())
#print("Normal: ", testRes["TotalTasks"].sum() / len(testRes["TestNo"].unique()))
barWidth = 0.25
# Set position of bar on X axis
br1 = np.arange(len(self.numberOfUsersList))
br2 = [x + barWidth for x in br1]
br3 = [x + barWidth for x in br2]
plt.figure()
plt.bar(br1, edge, width=barWidth, label="Edge")
plt.bar(br2, uav, width=barWidth, label="UAV")
plt.bar(br3, cloud, width=barWidth, label="Cloud")
plt.legend()
plt.xlabel("Number of Users")
plt.ylabel("Offloaded Tasks (%)")
plt.ylim(0, 1.05)
plt.xticks([r + barWidth for r in range(len(self.numberOfUsersList))], self.numberOfUsersList)
plt.savefig("OffloadedTaskPercentage-"+str(numberOfUAVs)+"-UAVs.pdf")
def getNumberOfTasks(self):
res = []
for i, numberOfUsers in enumerate(self.numberOfUsersList):
testRes = self.appResults.loc[(self.appResults["NumberOfUsers"] == numberOfUsers)
& (self.appResults["UAVWaitingPolicy"] == 100)]
res.append(testRes["TotalTasks"].sum() / len(testRes["TestNo"].unique()))
plt.figure()
plt.plot(self.numberOfUsersList, res)
plt.xlabel("Number of Users")
plt.ylabel("Avg Number of Tasks")
plt.savefig("TotalTask.pdf")
def getAppResults(self, numberOfUsers):
res = np.zeros((len(self.numberOfUAVsList), len(self.apps)))
for i, numberOfUAVs in enumerate(self.numberOfUAVsList):
for j, app in enumerate(self.apps):
testRes = self.appResults.loc[(self.appResults["ApplicationTypes"] == app) &
(self.appResults["NumberOfUsers"] == numberOfUsers)
& (self.appResults["NumberOfUAVs"] == numberOfUAVs)
& (self.appResults["UAVWaitingPolicy"] == 100)]
res[i, j] = (testRes["SuccessfulTasks"].sum() / testRes["TotalTasks"].sum()) * 100
plt.figure()
for i in range(0, len(self.apps)):
plt.plot(self.numberOfUAVsList, res[:, i], label=(self.apps[i]))
plt.legend()
plt.xlabel("Number of UAVs")
plt.ylabel("Avg Task Success Rate")
plt.ylim(0, 105)
plt.xticks(self.numberOfUAVsList)
plt.savefig("AppBasedTaskSuccess-"+str(numberOfUsers)+"-Users.pdf")
def getGeneralResults(self, uavWaitingTime):
res = np.zeros((len(self.numberOfUsersList), len(self.numberOfUAVsList)))
for i, numberOfUsers in enumerate(self.numberOfUsersList):
for j, numberOfUAVs in enumerate(self.numberOfUAVsList):
testRes = self.appResults.loc[(self.appResults["NumberOfUsers"] == numberOfUsers)
& (self.appResults["NumberOfUAVs"] == numberOfUAVs)
& (self.appResults["UAVWaitingPolicy"] == uavWaitingTime)]
res[i, j] = (testRes["SuccessfulTasks"].sum() / testRes["TotalTasks"].sum()) * 100
plt.figure()
for i in range(0, len(self.numberOfUAVsList)):
plt.plot(self.numberOfUsersList, res[:, i], label=(str(self.numberOfUAVsList[i]) + " UAVs"))
plt.legend()
plt.xlabel("Number of Users")
plt.ylabel("Avg Task Success Rate")
plt.ylim(0, 105)
plt.savefig("Overall-res-waiting-"+str(uavWaitingTime)+"-time.pdf")
def getEdgeUtilization(self):
res = np.zeros((len(self.numberOfUsersList), len(self.numberOfUAVsList)))
for i, numberOfUsers in enumerate(self.numberOfUsersList):
for j, numberOfUAVs in enumerate(self.numberOfUAVsList):
testRes = self.edgeResults.loc[(self.edgeResults["NumberOfUsers"] == numberOfUsers)
& (self.edgeResults["NumberOfUAVs"] == numberOfUAVs)
& (self.edgeResults["UAVWaitingPolicy"] == 100)]
res[i, j] = testRes["EdgeUtilization"].mean()
plt.figure()
for i in range(0, len(self.numberOfUAVsList)):
plt.plot(self.numberOfUsersList, res[:, i], label=(str(self.numberOfUAVsList[i]) + " UAVs"))
plt.legend()
plt.xlabel("Number of Users")
plt.ylabel("Avg Edge Utilization")
plt.ylim(0, 105)
plt.savefig("EdgeUtilization.pdf")
def getUAVUtilization(self):
res = np.zeros((len(self.numberOfUsersList), len(self.numberOfUAVsList)))
for i, numberOfUsers in enumerate(self.numberOfUsersList):
for j, numberOfUAVs in enumerate(self.numberOfUAVsList):
testRes = self.uavResults.loc[(self.uavResults["NumberOfUsers"] == numberOfUsers)
& (self.uavResults["NumberOfUAVs"] == numberOfUAVs)
& (self.uavResults["UAVWaitingPolicy"] == 100)]
res[i, j] = testRes["UAVUtilization"].mean()
plt.figure()
for i in range(0, len(self.numberOfUAVsList)):
plt.plot(self.numberOfUsersList, res[:, i], label=(str(self.numberOfUAVsList[i]) + " UAVs"))
plt.legend()
plt.xlabel("Number of Users")
plt.ylabel("Avg UAV Utilization")
plt.ylim(0, 105)
plt.savefig("UAVUtilization.pdf")
def getAvgServiceTime(self):
# QueueingDelays
res = np.zeros((len(self.numberOfUsersList), len(self.numberOfUAVsList)))
for i, numberOfUsers in enumerate(self.numberOfUsersList):
for j, numberOfUAVs in enumerate(self.numberOfUAVsList):
testRes = self.appResults.loc[(self.appResults["NumberOfUsers"] == numberOfUsers)
& (self.appResults["NumberOfUAVs"] == numberOfUAVs)
& (self.appResults["UAVWaitingPolicy"] == 100)]
res[i, j] = testRes["QueueingDelays"].mean()
plt.figure()
for i in range(0, len(self.numberOfUAVsList)):
plt.plot(self.numberOfUsersList, res[:, i], label=(str(self.numberOfUAVsList[i]) + " UAVs"))
plt.legend()
plt.xlabel("Number of Users")
plt.ylabel("Avg Service Time (s)")
plt.savefig("AvgServiceTime.pdf")
if __name__ == '__main__':
# TODO: Take these from a configuration file based on a scenario
numberOfUsers = [20, 40, 60, 80, 100]
numberOfServers = [4]
numberOfUAVs = [0, 5, 10, 15, 20]
uavFlyPolicy = ["LSI"]
uavWaitingPolicy = [100] # seconds
#edgeServerRadius = [50, 100, 150, 200]
uavRadius = [80]
userMobilityPolicy = ["Mobile"]
plots = Plots(numberOfServers=numberOfServers,
numberOfUsers=numberOfUsers,
numberOfUAVs=numberOfUAVs,
uavFlyPolicy=uavFlyPolicy,
uavWaitingPolicy=uavWaitingPolicy)
for waitingTime in uavWaitingPolicy:
plots.getGeneralResults(waitingTime)
plots.getEdgeUtilization()
plots.getUAVUtilization()
plots.getAvgServiceTime()
for userCount in numberOfUsers:
plots.getAppResults(userCount)
plots.getNumberOfTasks()
for uavCount in numberOfUAVs:
plots.getEdgeCloudUAVRatio(uavCount)