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simulation.py
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"""
This module runs the set of simulations as mentioned in the paper
"""
import matplotlib.pyplot as plt
from system import system
import sys
import argparse
import os
num = 5 # Number of simulations currently in the system
def run_simulations(simulation='all'):
"""
Run all simulations in order
Parameters
----------
simulation : `int`
Defines which simulation to run
"""
length = 8
number = 50000
delay_tolerance = 16
feedback_interval = 1
baseline = 'repetition'
degree_not_feedback = 2
if simulation == 'all':
for i in range(1, num+1):
run_simulations(str(i))
elif simulation == '1':
"""
Simulation 1:
Constants:
size = 2
prob_feedback = 0.25 TODO: Check with the simulation in paper. This
should be different I guess
other parameters = default
Sweep Over:
"Packet Sucess Probability"
"""
print("###################################################")
print("Simulation 1: DFR vs Packet Delivery Probability (Bernouli) (Size = 2, Feedback Erasure = 0.75)")
print("###################################################")
packet_success = [i/50 for i in range(51)]
dfr_icc = []
for success in packet_success:
dfr_icc.append(system(
length = length,
number = number,
size = 2,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = success,
prob_feedback = 0.25,
scheme='ICC',
degree_not_feedback = degree_not_feedback
))
dfr_rr = []
for success in packet_success:
dfr_rr.append(system(
length = length,
number = number,
size = 2,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = success,
prob_feedback = 0.25,
scheme=baseline,
degree_not_feedback = degree_not_feedback
))
plt.figure(figsize=(10,10))
plt.title("Simulation 1: DFR vs Packet Delivery Probability (Bernouli) (Size = 2, Feedback Probability = 0.25)", fontsize=12)
plt.plot(packet_success, dfr_icc, label='Windowed Coding')
plt.plot(packet_success, dfr_rr, label='Repetition Redundancy')
plt.xlabel('Packet Delivery Probability')
plt.ylabel('Delivery Failure Rate')
plt.yscale('log')
plt.grid()
plt.tight_layout()
plt.legend(loc='upper right')
plt.savefig('./plots/Simulation 1.png')
print("###################################################")
elif simulation == '2':
"""
Simulation 2:
Constants:
size = 3
prob_feedback = 0.75 TODO: Check with the simulation in paper. This
should be different I guess
other parameters = default
Sweep Over:
"Packet Sucess Probability"
"""
print("###################################################")
print("Simulation 2: DFR vs Packet Delivery Probability (Bernouli) (Size = 3, Feedback Erasure = 0.25)")
print("###################################################")
packet_success = [i/50 for i in range(51)]
dfr_icc = []
for success in packet_success:
dfr_icc.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = success,
prob_feedback = 0.75,
scheme='ICC',
degree_not_feedback = degree_not_feedback
))
dfr_rr = []
for success in packet_success:
dfr_rr.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = success,
prob_feedback = 0.75,
scheme=baseline,
degree_not_feedback = degree_not_feedback
))
plt.figure(figsize=(10,10))
plt.title("Simulation 2: DFR vs Packet Delivery Probability (Bernouli) (Size = 3, Feedback Probability = 0.75)", fontsize=12)
plt.plot(packet_success, dfr_icc, label='Windowed Coding')
plt.plot(packet_success, dfr_rr, label='Repetition Redundancy')
plt.xlabel('Packet Delivery Probability')
plt.ylabel('Delivery Failure Rate')
plt.yscale('log')
plt.grid()
plt.tight_layout()
plt.legend(loc='upper right')
plt.savefig('./plots/Simulation 2.png')
print("###################################################")
elif simulation == '3':
"""
Simulation 3:
Constants:
size = 3
packet_success_prob = 0.4 TODO: Check with the simulation in paper. This
should be different I guess
other parameters = default
Sweep Over:
"Feedback Reception Probability"
"""
print("###################################################")
print("Simulation 3: DFR vs Feedback Reception Probability (Bernouli) (Size = 4, Erasure = 0.4)")
print("###################################################")
feedback_prob = [i/50 for i in range(51)]
dfr_icc = []
for prob in feedback_prob:
dfr_icc.append(system(
length = length,
number = number,
size = 4,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = 0.4,
prob_feedback = prob,
scheme='ICC',
degree_not_feedback = degree_not_feedback
))
dfr_rr = []
for prob in feedback_prob:
dfr_rr.append(system(
length = length,
number = number,
size = 4,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Bernouli',
Pbg = 0.4,
prob_feedback = prob,
scheme=baseline,
degree_not_feedback = degree_not_feedback
))
plt.figure(figsize=(10,10))
plt.title("Simulation 3: DFR vs Feedback Reception Probability (Bernouli) (Size = 4, Packet Reception = 0.4)", fontsize=12)
plt.plot(feedback_prob, dfr_icc, label='Windowed Coding')
plt.plot(feedback_prob, dfr_rr, label='Repetition Redundancy')
plt.xlabel('Feedback Reception Probability')
plt.ylabel('Delivery Failure Rate')
plt.yscale('log')
plt.grid()
plt.tight_layout()
plt.legend(loc='upper right')
plt.savefig('./plots/Simulation 3.png')
print("###################################################")
elif simulation == '4':
"""
Simulation 4:
Constants:
Pgb = 0.2
other parameters = default
Sweep Over:
Pbg
"""
print("###################################################")
print("Simulation 4: DFR vs Pbg (Gilbert-Elliot) (Size = 3, Feedback Erasure = 0.7)")
print("###################################################")
erasures = [i/50 for i in range(51)]
dfr_icc = []
for erasure_prob in erasures:
dfr_icc.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Gilbert-Elliot',
Pbg = erasure_prob,
Pgb = 0.2,
prob_feedback = 0.3,
scheme='ICC',
degree_not_feedback = degree_not_feedback
))
dfr_rr = []
for erasure_prob in erasures:
dfr_rr.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay_tolerance,
feedback_interval = feedback_interval,
channel_erasure_model = 'Gilbert-Elliot',
Pbg = erasure_prob,
Pgb = 0.2,
prob_feedback = 0.3,
scheme=baseline,
degree_not_feedback = degree_not_feedback
))
plt.figure(figsize=(10,10))
plt.title("Simulation 4: DFR vs Pbg (Gilbert-Elliot) (Size = 3, Probability Feedback = 0.3)", fontsize=12)
plt.plot(erasures, dfr_icc, label='Windowed Coding')
plt.plot(erasures, dfr_rr, label='Repetition Redundancy')
plt.xlabel('Probability bad to good')
plt.ylabel('Delivery Failure Rate')
plt.yscale('log')
plt.grid()
plt.tight_layout()
plt.legend(loc='upper right')
plt.savefig('./plots/Simulation 4.png')
print("###################################################")
elif simulation == '5':
"""
Simulation 5:
Constants:
Pgb = 0.3
Pbg = 0.6
prob_feedback = 0.5
other parameters = default
Sweep Over:
delay_tolerance
"""
print("###################################################")
print("Simulation 5: DFR vs Delay Tolerance")
print("###################################################")
delays_list = [i for i in range(4,19)]
dfr_icc = []
for delay in delays_list:
dfr_icc.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay,
feedback_interval = feedback_interval,
channel_erasure_model = 'Gilbert-Elliot',
Pbg = 0.6,
Pgb = 0.3,
prob_feedback = 0.5,
scheme='ICC',
degree_not_feedback = degree_not_feedback
))
dfr_rr = []
for delay in delays_list:
dfr_rr.append(system(
length = length,
number = number,
size = 3,
delay_tolerance = delay,
feedback_interval = feedback_interval,
channel_erasure_model = 'Gilbert-Elliot',
Pbg = 0.6,
Pgb = 0.3,
prob_feedback = 0.5,
scheme=baseline,
degree_not_feedback = degree_not_feedback
))
plt.figure(figsize=(10,10))
plt.title("Simulation 5: DFR vs Delay Tolerance (Size = 3, Probability Feedback = 0.5)", fontsize=12)
plt.plot(delays_list, dfr_icc, label='Windowed Coding')
plt.plot(delays_list, dfr_rr, label='Repetition Redundancy')
plt.xlabel('Delay Tolerance')
plt.ylabel('Delivery Failure Rate')
plt.yscale('log')
plt.ylim(0.00001, 1)
plt.grid()
plt.tight_layout()
plt.legend(loc='upper right')
plt.savefig('./plots/Simulation 5.png')
print("###################################################")
if __name__=='__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-n", "--number", help="Run the particular simulation", default='all')
args = parser.parse_args()
if not os.path.exists('logs'):
os.makedirs('logs')
if not os.path.exists('plots'):
os.makedirs('plots')
sys.stdout = open('./logs/simulation_'+ args.number +'_results.txt', 'w')
run_simulations(args.number)
plt.show()
sys.stdout.close()