def avg_degree():
x = range(30, 110, 10)
y = []
y_dia = []
y_mlpt = []
y_deba = []
y_eftcg = []
for i in x:
print("The number of nodes:", i)
Node.n = i
y_dia_ = []
y_mlpt_ = []
y_deba_ = []
y_eftcg_ = []
for j in range(3):
print("The count:", j)
np.random.seed(j)
init()
G, N = dia()
a = Simulator.average_degree(len(N), G)
y_dia_.append(a)
G, N = mlpt()
a = Simulator.average_degree(len(N), G)
y_mlpt_.append(a)
G, N = deba()
a = Simulator.average_degree(len(N), G)
y_deba_.append(a)
G, N = my(1)
a = Simulator.average_degree(len(N), G)
y_eftcg_.append(a)
###########################################
y_dia.append(np.mean(y_dia_))
y_mlpt.append(np.mean(y_mlpt_))
y_deba.append(np.mean(y_deba_))
y_eftcg.append(np.mean(y_eftcg_))
###############################################
y = [[y_dia, "DIA"], [y_mlpt, "MLPT"], [y_deba, "DEBA"],
[y_eftcg, "EFTCG"]]
plot.plot_performance(x, y, ylabel="Avarage Degree")
def performance_k():
x = range(40, 110, 10)
num = 5 # number of evaluation-index
times = 10 # number of iterations
y_deba = [[] for x in range(num)]
y_k1 = [[] for x in range(num)]
y_k2 = [[] for x in range(num)]
for i in x:
print("The number of nodes:", i)
Node.n = i
y_deba_ = [[] for x in range(num)]
y_k1_ = [[] for x in range(num)]
y_k2_ = [[] for x in range(num)]
for j in range(times):
print("The count:", j)
init()
n = Node.n
size_ = 10
fault_node = random.sample(range(n - 2), size_)
G, N = deba()
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.survival_time(len(N), N, G)
d, e = fault_k(len(N), G, fault_node)
y_deba_[0].append(a)
y_deba_[1].append(b)
y_deba_[2].append(c)
y_deba_[3].append(d)
y_deba_[4].append(e)
G, N = my(1)
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.survival_time(len(N), N, G)
d, e = fault_k(len(N), G, fault_node)
y_k1_[0].append(a)
y_k1_[1].append(b)
y_k1_[2].append(c)
y_k1_[3].append(d)
y_k1_[4].append(e)
G, N = my(2)
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.survival_time(len(N), N, G)
d, e = fault_k(len(N), G, fault_node)
y_k2_[0].append(a)
y_k2_[1].append(b)
y_k2_[2].append(c)
y_k2_[3].append(d)
y_k2_[4].append(e)
###########################################
# power
##########################################
y_deba[0].append(np.mean(y_deba_[0]))
y_k1[0].append(np.mean(y_k1_[0]))
y_k2[0].append(np.mean(y_k2_[0]))
###########################################
# degree
##########################################
y_deba[1].append(np.mean(y_deba_[1]))
y_k1[1].append(np.mean(y_k1_[1]))
y_k2[1].append(np.mean(y_k2_[1]))
##########################################
# survive time
##########################################
y_deba[2].append(np.mean(y_deba_[2]))
y_k1[2].append(np.mean(y_k1_[2]))
y_k2[2].append(np.mean(y_k2_[2]))
###########################################
# failure rate
##########################################
y_deba[3].append(np.mean(y_deba_[3]))
y_k1[3].append(np.mean(y_k1_[3]))
y_k2[3].append(np.mean(y_k2_[3]))
###########################################
# links rate
##########################################
y_deba[4].append(np.mean(y_deba_[4]))
y_k1[4].append(np.mean(y_k1_[4]))
y_k2[4].append(np.mean(y_k2_[4]))
###############################################
y0 = [
[y_deba[0], "DEBA"],
[y_k1[0], "EFTCG-1"],
[y_k2[0], "EFTCG-2"],
]
y1 = [
[y_deba[1], "DEBA"],
[y_k1[1], "EFTCG-1"],
[y_k2[1], "EFTCG-2"],
]
y2 = [
[y_deba[2], "DEBA"],
[y_k1[2], "EFTCG-1"],
[y_k2[2], "EFTCG-2"],
]
y3 = [
[y_deba[3], "DEBA"],
[y_k1[3], "EFTCG-1"],
[y_k2[3], "EFTCG-2"],
]
y4 = [
[y_deba[4], "DEBA"],
[y_k1[4], "EFTCG-1"],
[y_k2[4], "EFTCG-2"],
]
plot.plot_performance(x, y0, ylabel="Average Transmit Power")
plot.plot_performance(x, y1, ylabel="Average Node Degree")
plot.plot_performance(x, y2, ylabel="Network Lifetime")
plot.plot_performance(x, y3, ylabel="Rate of Survival Nodes")
plot.plot_performance(x, y4, ylabel="Rate of Connectable Node Pairs")
def performance():
x = range(30, 110, 10)
num = 4 # number of evaluation-index
times = 10 # number of iterations
y_dia = [[] for x in range(num)]
y_mlpt = [[] for x in range(num)]
y_deba = [[] for x in range(num)]
y_eftcg = [[] for x in range(num)]
for i in x:
print("The number of nodes:", i)
Node.n = i
y_dia_ = [[] for x in range(num)]
y_mlpt_ = [[] for x in range(num)]
y_deba_ = [[] for x in range(num)]
y_eftcg_ = [[] for x in range(num)]
for j in range(times):
print("The count:", j)
init()
G, N = dia()
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.average_hop(len(N), G)
d = Simulator.survival_time(len(N), N, G)
y_dia_[0].append(a)
y_dia_[1].append(b)
y_dia_[2].append(c)
y_dia_[3].append(d)
G, N = mlpt()
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.average_hop(len(N), G)
d = Simulator.survival_time(len(N), N, G)
y_mlpt_[0].append(a)
y_mlpt_[1].append(b)
y_mlpt_[2].append(c)
y_mlpt_[3].append(d)
G, N = deba()
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.average_hop(len(N), G)
d = Simulator.survival_time(len(N), N, G)
y_deba_[0].append(a)
y_deba_[1].append(b)
y_deba_[2].append(c)
y_deba_[3].append(d)
G, N = my(1)
a = Simulator.average_power(len(N), N)
b = Simulator.average_degree(len(N), G)
c = Simulator.average_hop(len(N), G)
d = Simulator.survival_time(len(N), N, G)
y_eftcg_[0].append(a)
y_eftcg_[1].append(b)
y_eftcg_[2].append(c)
y_eftcg_[3].append(d)
###########################################
# power
##########################################
y_dia[0].append(np.mean(y_dia_[0]))
y_mlpt[0].append(np.mean(y_mlpt_[0]))
y_deba[0].append(np.mean(y_deba_[0]))
y_eftcg[0].append(np.mean(y_eftcg_[0]))
###########################################
# degree
##########################################
y_dia[1].append(np.mean(y_dia_[1]))
y_mlpt[1].append(np.mean(y_mlpt_[1]))
y_deba[1].append(np.mean(y_deba_[1]))
y_eftcg[1].append(np.mean(y_eftcg_[1]))
###########################################
# hop
##########################################
y_dia[2].append(np.mean(y_dia_[2]))
y_mlpt[2].append(np.mean(y_mlpt_[2]))
y_deba[2].append(np.mean(y_deba_[2]))
y_eftcg[2].append(np.mean(y_eftcg_[2]))
##########################################
y_dia[3].append(np.mean(y_dia_[3]))
y_mlpt[3].append(np.mean(y_mlpt_[3]))
y_deba[3].append(np.mean(y_deba_[3]))
y_eftcg[3].append(np.mean(y_eftcg_[3]))
###############################################
y0 = [[y_dia[0], "DIA"], [y_mlpt[0], "MLPT"], [y_deba[0], "DEBA"],
[y_eftcg[0], "EFTCG"]]
y1 = [[y_dia[1], "DIA"], [y_mlpt[1], "MLPT"], [y_deba[1], "DEBA"],
[y_eftcg[1], "EFTCG"]]
y2 = [[y_dia[2], "DIA"], [y_mlpt[2], "MLPT"], [y_deba[2], "DEBA"],
[y_eftcg[2], "EFTCG"]]
y3 = [[y_dia[3], "DIA"], [y_mlpt[3], "MLPT"], [y_deba[3], "DEBA"],
[y_eftcg[3], "EFTCG"]]
plot.plot_performance(x, y0, ylabel="Average Transmit Power")
plot.plot_performance(x, y1, ylabel="Average Node Degree")
plot.plot_performance(x, y2, ylabel="Average Hop")
plot.plot_performance(x, y3, ylabel="Network Lifetime")
