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plot_SER_ttl.py
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plot_SER_ttl.py
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import numpy as np
import matplotlib.pyplot as plt
from constants import *
time_epochs = 5
msg_files = 2
puser_files = 5
# arrays for broadcast
geo_opt = np.zeros(shape=(time_epochs, msg_files, puser_files))
geo_pes = np.zeros(shape=(time_epochs, msg_files, puser_files))
geo_wei = np.zeros(shape=(time_epochs, msg_files, puser_files))
bro_opt_PQ = np.zeros(shape=(time_epochs, msg_files, puser_files))
bro_pes_PQ = np.zeros(shape=(time_epochs, msg_files, puser_files))
bro_wei_PQ = np.zeros(shape=(time_epochs, msg_files, puser_files))
snw_wei_PQ = np.zeros(shape=(time_epochs, msg_files, puser_files))
Epidemic_TV = np.zeros(shape=(time_epochs, msg_files, puser_files))
Epidemic_LTE = np.zeros(shape=(time_epochs, msg_files, puser_files))
Epidemic_CBRS = np.zeros(shape=(time_epochs, msg_files, puser_files))
Epidemic_ISM = np.zeros(shape=(time_epochs, msg_files, puser_files))
num_mules = 92
TTLs = [30, 90, 180, 240, 360]
num_channels = 6
num_Pusers = 200
msg_mean = 15
T = 360
max_mem = 100
startTime = 1
days = "50"
dataset = "Lexington"
buffer_type = ["FIFO", "FIFO"]
weighted_approach = "weighted_0.5"
smart_settings = [weighted_approach, "TV", "LTE", "CBRS", "ISM"]
protocols = ["broadcast", "geo", "SnW"]
# protocols = ["Epidemic_Smart_optimistic"]
# fwd_strat = ["geo_3"]
num_replicas = 1
num_replicas_snw = 20
metrics_file = "metrics.txt"
sim_round = 6
p_id = 2 # p_id = 1 for PDR, = 2 for latency, and 3 for Energy, and 4 for overhead
for i in range(msg_files):
for j in range(puser_files):
for ttl in TTLs:
for setting in smart_settings:
for protocol in protocols:
t = TTLs.index(ttl)
path_exists = False
if setting in [weighted_approach]: #ALL Bands
if protocol in ["geo"]:
protocol = protocol + "_" + str(num_replicas)
if protocol in ["SnW"]:
protocol = protocol + "_" + str(num_replicas_snw)
path_exists = True
else:
if protocol in ["geo"]:
protocol = protocol + "_" + str(num_replicas)
path_exists = True
if path_exists:
path = "DataMules/" + dataset + "/" + days + "/" + str(sim_round) + "/Link_Exists/LE_" + str(startTime) + \
"_" + str(T) + "/Epidemic_Smart_" + setting + "/" + buffer_type[0] + "/" + protocol + "/mules_" + \
str(num_mules) + "/channels_" + str(num_channels) + "/P_users_" + str(num_Pusers) + \
"/msgfile_" + str(i) + "_" + str(msg_mean) + "/puserfile_" + str(j) + "/TTL_" + str(ttl) + "/BuffSize_" + str(max_mem) + "/"
with open(path + metrics_file, "r") as f:
lines = f.readlines()[1:]
for line in lines:
line_arr = line.strip().split()
if int(line_arr[0]) == 360:
# if "optimistic" in setting and "geo" in protocol:
# Epidemic_opt_PQ[t, i, j] = float(line_arr[p_id])
# elif "pessimistic" in setting and "geo" in protocol:
# Epidemic_pes_PQ[t, i, j] = float(line_arr[p_id])
if "weighted" in setting and "geo" in protocol:
geo_wei[t, i, j] = float(line_arr[p_id])
elif "weighted" in setting and "SnW" in protocol:
snw_wei_PQ[t, i, j] = float(line_arr[p_id])
elif "weighted" in setting and "broadcast" in protocol:
bro_wei_PQ[t, i, j] = float(line_arr[p_id])
elif "TV" in setting and "geo" in protocol:
Epidemic_TV[t, i, j] = float(line_arr[p_id])
elif "LTE" in setting and "geo" in protocol:
Epidemic_LTE[t, i, j] = float(line_arr[p_id])
elif "CBRS" in setting and "geo" in protocol:
Epidemic_CBRS[t, i, j] = float(line_arr[p_id])
elif "ISM" in setting and "geo" in protocol:
Epidemic_ISM[t, i, j] = float(line_arr[p_id])
# for protocol in ["optimistic", "pessimistic", "weighted"]:
# t = TTLs.index(ttl)
# # if fwd_strat > 0:
# path = "DataMules/" + dataset + "/" + days + "/" + str(sim_round) + "/Link_Exists/LE_" + str(startTime) + \
# "_" + str(T) + "/Epidemic_Smart_" + protocol + "/" + buffer_type[0] + "/geo_" + str(num_replicas) + "/mules_" + \
# str(num_mules) + "/channels_" + str(num_channels) + "/P_users_" + str(num_Pusers) + \
# "/msgfile_" + str(i) + "_" + str(msg_mean) + "/puserfile_" + str(j) + "/TTL_" + str(ttl) + "/BuffSize_" + str(max_mem) + "/"
# # else:
# # path = "DataMules/" + dataset + "/" + days + "/3/Link_Exists/LE_" + str(startTime) + \
# # "_" + str(T) + "/Epidemic_Smart_" + protocol + "/" + buffer_type + "/broadcast/mules_" + \
# # str(num_mules) + "/channels_" + str(num_channels) + "/P_users_" + str(num_Pusers) + \
# # "/msgfile" + str(i) + "_" + str(msg_mean) + "/puserfile" + str(j) + "/TTL_" + str(ttl) + "/BuffSize_" + str(max_mem) + "/"
# with open(path + metrics_file, "r") as f:
# lines = f.readlines()[1:]
# for line in lines:
# line_arr = line.strip().split()
# if int(line_arr[0]) == 360:
# if "optimistic" in protocol:
# geo_opt[t, i, j] = float(line_arr[p_id])
# elif "pessimistic" in protocol:
# geo_pes[t, i, j] = float(line_arr[p_id])
# elif "weighted" in protocol:
# geo_wei[t, i, j] = float(line_arr[p_id])
# for i in range(msg_files):
# for j in range(puser_files):
# for ttl in TTLs:
# for protocol in ["optimistic", "pessimistic", "weighted", "TV", "LTE", "CBRS", "ISM"]:
# t = TTLs.index(ttl)
# if protocol in ["optimistic", "pessimistic", "weighted"]:
# path = "DataMules/" + dataset + "/" + days + "/" + str(sim_round) + "/Link_Exists/LE_" + str(startTime) + \
# "_" + str(T) + "/Epidemic_Smart_" + protocol + "/" + buffer_type[0] + "/broadcast/mules_" + \
# str(num_mules) + "/channels_" + str(num_channels) + "/P_users_" + str(num_Pusers) + \
# "/msgfile_" + str(i) + "_" + str(msg_mean) + "/puserfile_" + str(j) + "/TTL_" + str(ttl) + "/BuffSize_" + str(max_mem) + "/"
# else:
# path = "DataMules/" + dataset + "/" + days + "/" + str(sim_round) + "/Link_Exists/LE_" + str(startTime) + \
# "_" + str(T) + "/Epidemic_Smart_" + protocol + "/" + buffer_type[1] + "/broadcast/mules_" + \
# str(num_mules) + "/channels_" + str(num_channels) + "/P_users_" + str(num_Pusers) + \
# "/msgfile_" + str(i) + "_" + str(msg_mean) + "/puserfile_" + str(j) + "/TTL_" + str(ttl) + "/BuffSize_" + str(max_mem) + "/"
# with open(path + metrics_file, "r") as f:
# lines = f.readlines()[1:]
# for line in lines:
# line_arr = line.strip().split()
# if int(line_arr[0]) == 360:
# if "optimistic" in protocol:
# bro_opt_PQ[t, i, j] = float(line_arr[p_id])
# elif "pessimistic" in protocol:
# bro_pes_PQ[t, i, j] = float(line_arr[p_id])
# elif "weighted" in protocol:
# bro_wei_PQ[t, i, j] = float(line_arr[p_id])
# elif "TV" in protocol:
# Epidemic_TV[t, i, j] = float(line_arr[p_id])
# elif "LTE" in protocol:
# Epidemic_LTE[t, i, j] = float(line_arr[p_id])
# elif "CBRS" in protocol:
# Epidemic_CBRS[t, i, j] = float(line_arr[p_id])
# elif "ISM" in protocol:
# Epidemic_ISM[t, i, j] = float(line_arr[p_id])
optB_mean = []
optB_sd = []
pesB_mean = []
pesB_sd = []
weiB_mean = []
weiB_sd = []
optBro_mean = []
optBro_sd = []
pesBro_mean = []
pesBro_sd = []
weiBro_mean = []
weiBro_sd = []
weiSnW_mean = []
weiSnW_sd = []
TV_mean = []
TV_sd = []
LTE_mean = []
LTE_sd = []
CBRS_mean = []
CBRS_sd = []
ISM_mean = []
ISM_sd = []
optB_temp = []
pesB_temp = []
weiB_temp = []
optBro_temp = []
pesBro_temp = []
weiBro_temp = []
weiSnW_temp = []
TV_temp = []
LTE_temp = []
CBRS_temp = []
ISM_temp = []
for t in range(len(geo_opt)):
t_arr_optB = []
t_arr_pesB = []
t_arr_weiB = []
t_arr_optBro = []
t_arr_pesBro = []
t_arr_weiBro = []
t_arr_weiSnW = []
t_arr_tv = []
t_arr_lte = []
t_arr_cbrs = []
t_arr_ism = []
for i in range(len(geo_opt[t])):
for j in range(len(geo_opt[t][i])):
t_arr_optB.append(geo_opt[t,i,j])
t_arr_pesB.append(geo_pes[t,i,j])
t_arr_weiB.append(geo_wei[t,i,j])
t_arr_optBro.append(bro_opt_PQ[t, i, j])
t_arr_pesBro.append(bro_pes_PQ[t, i, j])
t_arr_weiBro.append(bro_wei_PQ[t, i, j])
t_arr_weiSnW.append(snw_wei_PQ[t, i, j])
t_arr_tv.append(Epidemic_TV[t, i, j])
t_arr_lte.append(Epidemic_LTE[t, i, j])
t_arr_cbrs.append(Epidemic_CBRS[t, i, j])
t_arr_ism.append(Epidemic_ISM[t, i, j])
optB_temp.append(t_arr_optB)
pesB_temp.append(t_arr_pesB)
weiB_temp.append(t_arr_weiB)
optBro_temp.append(t_arr_optBro)
pesBro_temp.append(t_arr_pesBro)
weiBro_temp.append(t_arr_weiBro)
weiSnW_temp.append(t_arr_weiSnW)
TV_temp.append(t_arr_tv)
LTE_temp.append(t_arr_lte)
CBRS_temp.append(t_arr_cbrs)
ISM_temp.append(t_arr_ism)
for i in range(len(optB_temp)):
optB_mean.append(np.mean(optB_temp[i]))
pesB_mean.append(np.mean(pesB_temp[i]))
weiB_mean.append(np.mean(weiB_temp[i]))
optB_sd.append(np.std(optB_temp[i]))
pesB_sd.append(np.std(pesB_temp[i]))
weiB_sd.append(np.std(weiB_temp[i]))
optBro_mean.append(np.mean(optBro_temp[i]))
pesBro_mean.append(np.mean(pesBro_temp[i]))
weiBro_mean.append(np.mean(weiBro_temp[i]))
optBro_sd.append(np.std(optBro_temp[i]))
pesBro_sd.append(np.std(pesBro_temp[i]))
weiBro_sd.append(np.std(weiBro_temp[i]))
weiSnW_mean.append(np.mean(weiSnW_temp[i]))
weiSnW_sd.append(np.mean(weiSnW_temp[i]))
TV_mean.append(np.mean(TV_temp[i]))
TV_sd.append(np.std(TV_temp[i]))
LTE_mean.append(np.mean(LTE_temp[i]))
LTE_sd.append(np.std(LTE_temp[i]))
CBRS_mean.append(np.mean(CBRS_temp[i]))
CBRS_sd.append(np.std(CBRS_temp[i]))
ISM_mean.append(np.mean(ISM_temp[i]))
ISM_sd.append(np.std(ISM_temp[i]))
x = TTLs
# x.append(0)
plt.xticks(fontsize=15)
plt.yticks(fontsize=15)
plt.xticks(TTLs)
fig_name = "dummy.eps"
plt.xlabel('TTL', fontsize=25)
if p_id == 1:
plt.ylabel('Message delivery ratio', fontsize=25)
plt.ylim(-0.1,1.0)
fig_name = "Plots/pdr_ttl_SER.eps"
if p_id == 2:
plt.ylabel('Network delay (min)', fontsize=25)
fig_name = "Plots/latency_ttl_SER.eps"
if p_id == 3:
plt.ylabel('Energy per packet (J)', fontsize=25)
fig_name = "Plots/energy_ttl_SER.eps"
if p_id == 4:
plt.ylabel('Message overhead', fontsize=25)
fig_name = "Plots/overhead_ttl_SER.eps"
if p_id == 3:
# plt.errorbar(x, [y/1000 for y in optB_mean], 0, marker='o', markersize=5, linestyle='-', linewidth=1)
# plt.errorbar(x, [y/1000 for y in pesB_mean], 0, marker='x', markersize=5, linestyle='--', linewidth=1)
plt.errorbar(x, [y/1000 for y in weiB_mean], 0, marker='d', markersize=5, linestyle='-', linewidth=2)
# plt.errorbar(x, [y/1000 for y in optBro_mean], 0, marker='o', markersize=5, linestyle='-', linewidth=1)
# plt.errorbar(x, [y/1000 for y in pesBro_mean], 0, marker='x', markersize=5, linestyle='--', linewidth=1)
plt.errorbar(x, [y/1000 for y in weiBro_mean], 0, marker='d', markersize=5, linestyle='-', linewidth=2)
plt.errorbar(x, [y/1000 for y in weiSnW_mean], 0, marker='d', markersize=5, linestyle='-', linewidth=2)
plt.errorbar(x, [y/1000 for y in TV_mean], 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, [y/1000 for y in LTE_mean], 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, [y/1000 for y in CBRS_mean], 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, [y/1000 for y in ISM_mean], 0, marker='*', markersize=5, linestyle=':', linewidth=2)
else:
# plt.errorbar(x, optB_mean, 0, marker='o', markersize=5, linestyle='-', linewidth=1)
# plt.errorbar(x, pesB_mean, 0, marker='x', markersize=5, linestyle='--', linewidth=1)
plt.errorbar(x, weiB_mean, 0, marker='d', markersize=5, linestyle='-', linewidth=2)
# plt.errorbar(x, optBro_mean, 0, marker='o', markersize=5, linestyle='-', linewidth=1)
# plt.errorbar(x, pesBro_mean, 0, marker='x', markersize=5, linestyle='--', linewidth=1)
plt.errorbar(x, weiBro_mean, 0, marker='d', markersize=5, linestyle='-', linewidth=2)
plt.errorbar(x, weiSnW_mean, 0, marker='d', markersize=5, linestyle='-', linewidth=2)
plt.errorbar(x, TV_mean, 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, LTE_mean, 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, CBRS_mean, 0, marker='*', markersize=5, linestyle=':', linewidth=2)
plt.errorbar(x, ISM_mean, 0, marker='*', markersize=5, linestyle=':', linewidth=2)
routing_name_list = ["S-GR", "S-ER", "S-SnW(20)", "GR(TV)", "GR(LTE)", "GR(CBRS)", "GR(ISM)"]
if p_id == 1:
plt.legend(routing_name_list, loc="lower left", fontsize=12, ncol = 3, frameon=False)
elif p_id == 2:
plt.legend(routing_name_list, loc="upper left", fontsize=12, ncol = 1, frameon=False)
elif p_id ==3:
plt.legend(routing_name_list, loc="upper left", fontsize=12, ncol = 3, frameon=False)
elif p_id ==4:
plt.legend(routing_name_list, loc="upper left", bbox_to_anchor=(0.01, 0.5), fontsize=12, ncol = 3, frameon=False)
plt.tight_layout()
plt.savefig(fig_name)
plt.show()