def search_norm_xpercent_latency(arrival_rate, bandwidth, period, percentile,
N):
if (arrival_rate >= bandwidth):
print "Unstable!"
return -1
budget = period * bandwidth
(x_bd, y_bd) = get_MDDS1_from_BDDS1(arrival_rate, 1.0, budget, period, N)
i = 0
while (y_bd[i] < percentile):
i = i + 1
x = x_bd[i - 1] + (x_bd[i] - x_bd[i - 1]) * (percentile - y_bd[i - 1]) / (
y_bd[i] - y_bd[i - 1])
print "P=[%f] W=[%f], [%2d-th] percentile latency [%f]" % (
period, bandwidth, int(100 * percentile), x)
return x
# For paper 3.5x2.8 for PPT 5x4
figwidth = 3.5
figheight = 2.8
plt.figure(figsize=(figwidth, figheight))
# For paper: Enable
plt.subplots_adjust(left=0.18, top=0.95, bottom=0.18)
for i in range(0, 4):
norm_lambda = arrival_rate * service_durs[i]
norm_p = period / service_durs[i]
norm_b = budget / service_durs[i]
(x_bd, y_bd) = get_MDDS1_from_BDDS1(norm_lambda, 1.0, norm_b, norm_p, N)
x_bd = x_bd * service_durs[i]
x_bd = x_bd[0:int(x_lim * N)]
y_bd = y_bd[0:int(x_lim * N)]
plt.plot(x_bd,
y_bd,
linestyle=lstyles[i],
color=colors[i],
drawstyle='steps',
clip_on=True,
linewidth=2.0)
#====================== Draw Figure ======================
N = 20
x_lim = 20.0
y_lim = 1.0
xy_lim = (x_lim, y_lim)
# For paper 3.5x2.8 for PPT 5x4
figwidth = 3.5
figheight = 2.8
plt.figure(figsize=(figwidth, figheight))
# For paper: Enable
plt.subplots_adjust(left=0.18,top=0.95, bottom=0.18)
for i in range(0, 4):
(x_bd, y_bd) = get_MDDS1_from_BDDS1(arrival_rates[i], 1.0, budget, period, N)
x_bd = x_bd[0 : int(x_lim * N)]
y_bd = y_bd[0 : int(x_lim * N)]
plt.plot(x_bd, y_bd, linestyle=lstyles[i], color=colors[i], drawstyle='steps', clip_on=False, linewidth=2.0)
#====================== Draw Figure ======================
#if (True == ISVARBANDWIDTH):
# mytitle = "Numerical CDF: P=%.1f, %c=%.1f, %c=%.1f" % (period, u'\u03BB', arrival_rate, u'\u03BC', service_rate)
#else:
# mytitle = "Numerical CDF: W=%2d%%, %c=%.1f, %c=%.1f" % (int(bandwidth * 100), u'\u03BB', arrival_rate, u'\u03BC', service_rate)
plt.xlabel('Normalized Response Time', fontsize = 12)
plt.ylabel('Proportion', fontsize = 12)
service_rate = 1.0
period = period_real / service_dur_real
budget = period * bandwidth
GEN_NEW_DATA = False
N = 60
runfile = 'redis_sort'
x_lim = 20.0
y_lim = 1.0
xy_lim = (x_lim, y_lim)
#================= M/D(DS)/1 Theoretical ==================
(x_bd, y_bd) = get_MDDS1_from_BDDS1(arrival_rate, 1.0, budget, period, N)
#
x_bd = x_bd[0:int(x_lim * N)]
y_bd = y_bd[0:int(x_lim * N)]
#================= M/D(DS)/1 Theoretical ==================
# Normalization
service_dur_worst = 10.0
arrival_rate_2 = arrival_rate_real * service_dur_worst
period_2 = period_real / service_dur_worst
budget_2 = period_2 * bandwidth
(x_bd2, y_bd2) = get_MDDS1_from_BDDS1(arrival_rate_2, 1.0, budget_2, period_2,
N)
x_bd2 = x_bd2[0:int(x_lim * N)] * service_dur_worst / service_dur_real
y_bd2 = y_bd2[0:int(x_lim * N)]
