def test_pkt_loss_analysis():
trial_name = '8_7_2018_1533690234'
hm = mapper.HostMapper([cfg.dns_server_ip], cfg.of_controller_ip,
cfg.of_controller_port)
of_proc = ofp.OFProcessor(cfg.of_controller_ip, cfg.of_controller_port)
st_proc = stp.StatsProcessor(hm, of_proc)
st_proc.calc_loss_rates(trial_name)
def plot_test():
of_proc = ofp.OFProcessor(cfg.of_controller_ip, cfg.of_controller_port)
hm = mapper.HostMapper([cfg.dns_server_ip], cfg.of_controller_ip,
cfg.of_controller_port)
st_proc = stp.StatsProcessor(hm, of_proc)
grapher = stp.Grapher()
trial_name = read_trial_name('./name_hints.txt')
tx_file = './tx_stats.p'
rx_file = './rx_stats.p'
tx_stats = pickle.load(open(tx_file, 'rb'))
rx_stats = pickle.load(open(rx_file, 'rb'))
stats_list = st_proc.calc_link_util_per_t(tx_stats, cfg.pkt_size,
cfg.time_slice,
stp.Units.MegaBitsPerSecond)
stats_avg = st_proc.calc_link_util(tx_stats, cfg.pkt_size, cfg.time_slice,
stp.Units.MegaBitsPerSecond)
stats_loss = st_proc.calc_loss_rates(read_trial_name('./name_hints.txt'))
stats_uplink = st_proc.calc_ingress_util_per_t(rx_stats, cfg.pkt_size,
cfg.time_slice,
stp.Units.MegaBitsPerSecond)
stats_tput = st_proc.calc_flow_rate(trial_name, cfg.pkt_size,
cfg.sample_freq, cfg.trial_length)
grapher.graph_util_over_time(stats_list, 'util_per_ts', show_plot=True)
fig, ax = plt.subplots(1, 1)
grapher.graph_loss_cdf(ax, stats_loss, 'loss_plot')
fig.savefig('loss_plot.png')
grapher.graph_util_over_time(stats_uplink, 'uplink_ports')
def print_loss_array(hm, of_proc, trial_length):
trial_name = read_trial_name('./name_hints.txt')
st_proc = stp.StatsProcessor(hm, of_proc)
loss_dict = st_proc.calc_loss_rates(trial_name)
loss_arr = [
v for d1 in loss_dict.values() for d2 in d1.values()
for v in d2.values()
]
p.pprint(loss_arr)
def print_local_loss():
st_proc = stp.StatsProcessor(None, None, '/home/alexj/packet_counts/')
trial_name = ''
print('LOSS RATES')
p.pprint(st_proc.calc_loss_rates(trial_name))
print(
'*******************************************************************')
print('GOODPUT FOR FLOWS')
p.pprint(
st_proc.calc_flow_rate(trial_name, cfg.pkt_size, cfg.sample_freq,
cfg.trial_length))
print(
'*******************************************************************')
def test_stats_processor(hm, of_proc, trial_length):
trial_name = read_trial_name('./name_hints.txt')
tx_file = './tx_stats.p'
rx_file = './rx_stats.p'
stats = pickle.load(open(tx_file, 'rb'))
rx_stats = pickle.load(open(rx_file, 'rb'))
st_proc = stp.StatsProcessor(hm, of_proc)
# p.pprint(stats)
st_dict = st_proc.calc_link_util(stats,
cfg.pkt_size,
cfg.sample_freq,
units=stp.Units.MegaBitsPerSecond)
ingress_flows_dict = st_proc.calc_ingress_util(
rx_stats,
cfg.pkt_size,
cfg.sample_freq,
units=stp.Units.MegaBitsPerSecond)
egress_flows_dict = st_proc.calc_ingress_util(
stats,
cfg.pkt_size,
cfg.sample_freq,
units=stp.Units.MegaBitsPerSecond)
print(
'*******************************************************************')
print('CORE LINK UTILIZATION')
#p.pprint(st_dict)
print('test_driver: ' + str(st_dict))
print(
'*******************************************************************')
print('HOST UPLINK UTILIZATION')
#p.pprint(ingress_flows_dict)
print('test_driver: ' + str(ingress_flows_dict))
print(
'*******************************************************************')
print('HOST EGRESS UTILIZATION')
#p.pprint(egress_flows_dict)
print('test_driver: ' + str(egress_flows_dict))
print(
'*******************************************************************')
print('LOSS RATES')
#p.pprint(st_proc.calc_loss_rates(trial_name))
print('test_driver: ' + str(st_proc.calc_loss_rates(trial_name)))
print(
'*******************************************************************')
print('GOODPUT FOR FLOWS')
#p.pprint(st_proc.calc_flow_rate(trial_name, cfg.pkt_size, cfg.sample_freq, trial_length))
print(
st_proc.calc_flow_rate(trial_name, cfg.pkt_size, cfg.sample_freq,
trial_length))
print(
'*******************************************************************')
def gen_lossplot(input_files):
of_proc = ofp.OFProcessor(cfg.of_controller_ip, cfg.of_controller_port)
hm = mapper.HostMapper([cfg.dns_server_ip], cfg.of_controller_ip,
cfg.of_controller_port)
st_proc = stp.StatsProcessor(hm, of_proc)
grapher = stp.Grapher()
fig, ax = plt.subplots(1, 1)
stats_avg = []
for i, f in enumerate(input_files):
trial_name = f + '/name_hints.txt'
loss_stats = st_proc.calc_loss_rates(read_trial_name(trial_name))
grapher.graph_loss_cdf(ax, loss_stats, f)
legend = ax.legend(loc='bottom right', shadow=True, fontsize='medium')
plt.show()
def calc_stats_list():
trial_name = read_trial_name('./name_hints.txt')
hm = mapper.HostMapper([cfg.dns_server_ip], cfg.of_controller_ip,
cfg.of_controller_port)
tx_file = './tx_stats.p'
rx_file = './rx_stats.p'
stats = pickle.load(open(tx_file, 'rb'))
rx_stats = pickle.load(open(rx_file, 'rb'))
of_proc = ofp.OFProcessor(cfg.of_controller_ip, cfg.of_controller_port)
st_proc = stp.StatsProcessor(hm, of_proc)
st_dict = st_proc.calc_link_util_per_t(stats,
cfg.pkt_size,
cfg.sample_freq,
units=stp.Units.MegaBitsPerSecond)
p.pprint(st_dict)
def print_util_array(hm, of_proc, trial_length):
tx_file = './tx_stats.p'
tx_stats = pickle.load(open(tx_file, 'rb'))
st_proc = stp.StatsProcessor(hm, of_proc)
st_dict = st_proc.calc_link_util(tx_stats,
cfg.pkt_size,
cfg.sample_freq,
units=stp.Units.MegaBitsPerSecond)
# Print link utilization as a list of percentages.
ordered = defaultdict(float)
for src, d in st_dict.items():
for dst, util in d.items():
k = (src, dst) if src < dst else (dst, src)
ordered[k] = ordered[k] + util
util_arr = [v for v in ordered.values()]
p.pprint(util_arr)
def gen_boxplot(input_files):
of_proc = ofp.OFProcessor(cfg.of_controller_ip, cfg.of_controller_port)
hm = mapper.HostMapper([cfg.dns_server_ip], cfg.of_controller_ip,
cfg.of_controller_port)
st_proc = stp.StatsProcessor(hm, of_proc)
grapher = stp.Grapher()
fig, ax = plt.subplots(1, 1)
stats_avg = []
for i, f in enumerate(input_files):
stat_path = f + '/tx_stats.p'
tx_stats = pickle.load(open(stat_path, 'rb'))
link_util = st_proc.calc_link_util(tx_stats, cfg.pkt_size,
cfg.time_slice,
stp.Units.MegaBitsPerSecond)
flat = [util for v in link_util.values() for util in v.values()]
stats_avg.append(flat)
grapher.graph_timeframes(ax, stats_avg, input_files)
plt.show()
fig, ax = plt.subplots(1, 1)
stats_avg = []
for i, f in enumerate(input_files):
stat_path = f + '/tx_stats.p'
tx_stats = pickle.load(open(stat_path, 'rb'))
trial_name = read_trial_name(f + '/name_hints.txt')
flow_rate = st_proc.calc_flow_rate(trial_name, cfg.pkt_size,
cfg.sample_freq, cfg.trial_length)
flat = [
rate for v in flow_rate.values() for u in v.values()
for rate in u.values()
]
stats_avg.append(flat)
grapher.graph_timeframes(ax, stats_avg, input_files)
plt.show()