def main():
url = os.getenv("TARGET_URL")
tg = TrafficGenerator(url)
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop.run_until_complete(
tg.run()
)
def initialize_config(config_file):
config = read_config(config_file)
sumo = sumo_config(config['simulation']['gui'], \
config['simulation']['max_steps'])
traffic_generator = TrafficGenerator(int(config['simulation']['nb_cars_generated']), \
int(config['simulation']['max_steps']))
return config, sumo, traffic_generator
def setUpClass(cls):
gov_uk_url = os.getenv("GOV_UK_URL",
"https://www.gov.uk.glasswall-icap.com")
file_drop_url = os.getenv(
"FILE_DROP_URL", "https://glasswall-file-drop.azurewebsites.net")
num_files = int(os.getenv("NUM_FILES", 10))
tg = TrafficGenerator(gov_uk_url)
asyncio.get_event_loop().run_until_complete(
tg.run(num_files=num_files))
cls.file_drop = FileDrop(file_drop_url)
def setUpClass(cls):
gov_uk_url = os.getenv("GOV_UK_URL", "https://www.gov.uk.glasswall-icap.com")
file_drop_url = os.getenv("FILE_DROP_URL", "https://glasswall-file-drop.azurewebsites.net")
num_files = int(os.getenv("NUM_FILES", 1))
elastic_host = os.getenv("ELASTIC_HOST", "localhost")
elastic_port = os.getenv("ELASTIC_PORT", "9200")
elastic_username = os.getenv("ELASTIC_USER")
elastic_password = os.getenv("ELASTIC_PASSWORD")
cls.index_name = os.getenv("INDEX_NAME", "tg_test_results")
tg = TrafficGenerator(gov_uk_url)
asyncio.get_event_loop().run_until_complete(tg.run(num_files=num_files))
cls.file_drop = FileDrop(file_drop_url)
cls.ship_test_results_to_elastic = os.getenv("SHIP_TO_ELASTIC", "0")
if cls.ship_test_results_to_elastic == "1":
cls.es = ElasticService(elastic_host, elastic_port, elastic_username, elastic_password)
cls.es.create_index(cls.index_name)
def main():
# *** INITIALIZATION PHASE ***
## set constant variables
traffic_distribution_per_cos = [COS0, COS1, COS2]
## import data & preprocessing
geant_traffic_data = import_csv(TRAFFIC_FILE)
throughput = preprocess_data(geant_traffic_data)
## setup a traffic generator
tg = TrafficGenerator(throughput, traffic_distribution_per_cos)
## initialize variables for plots
estimated_tot_throughput = np.array([])
estimated_cos0_percent = np.array([])
estimated_cos1_percent = np.array([])
estimated_cos2_percent = np.array([])
# *** EXECUTION PHASE ***
x = 1
for t in range(len(throughput)):
traffic_t = tg.traffic[t]
oom_t = morris_algo(traffic_t)
sample_t = vitter_algo(traffic_t, SLOTS)
estimated_results_t = estimate_throughput_and_cos(sample_t, oom_t)
#! TROUBLESHOOTING PURPOSE
#print("{} --> ESTIMATED = {}K || REAL = {}K || OOM RATIO (real/est) = {} || SAMPLING RATIO (slots/real) {} || COS DISTRO {}".format(t,estimated_throughput_t[0]//10**3, throughput[t]//10**3,
#get_digits(len(traffic_t))/oom_t, SLOTS/len(traffic_t), "{}|{}|{}".format(int(100*estimated_throughput_t[1]/estimated_throughput_t[0]),int(100*estimated_throughput_t[2]/estimated_throughput_t[0]),int(100*estimated_throughput_t[3]/estimated_throughput_t[0]))))
# SAVE DATA FOR PLOTS
estimated_tot_throughput = np.append(estimated_tot_throughput,
estimated_results_t[0])
estimated_cos0_percent = np.append(estimated_cos0_percent,
estimated_results_t[1])
estimated_cos1_percent = np.append(estimated_cos1_percent,
estimated_results_t[2])
estimated_cos2_percent = np.append(estimated_cos2_percent,
estimated_results_t[3])
# PROGRESS BAR
if t == (x * int(len(throughput) / 100)):
print("EXECUTION PROGRESS IS @ {}%: {}".format(x, x * '=' + '>'))
x += 1
# *** PLOT RESULTS PHASE ***
## THROUGHPUT
fig = plt.figure(1, figsize=(10, 10))
fig.suptitle('Big Data Network Analyzer (BDNA)', fontsize=16)
plt.xlabel('Time [s]')
plt.ylabel('Throughput [bit/s]')
plt.title(
'TOTAL THROUGHPUT ESTIMATION - MEMORY = {}% OF INTERFACE CAPACITY'.
format(PERCENTAGE))
xdata = np.arange(SECONDS_OF_TRAFFIC)
plt.plot(xdata, estimated_tot_throughput, 'rx')
plt.plot(xdata, throughput, 'b--', linewidth=2)
plt.show()
## COS DISTRIBUTION
fig = plt.figure(2, figsize=(10, 10))
fig.suptitle('Big Data Network Analyzer (BDNA)', fontsize=16)
plt.xlabel('Time [s]')
plt.ylabel('COS PERCENTAGE [%]')
plt.title(
'COS DISTRIBUTION ESTIMATION - MEMORY = {}% OF INTERFACE CAPACITY'.
format(PERCENTAGE))
xdata = np.arange(SECONDS_OF_TRAFFIC)
# COS0
plt.plot(xdata, estimated_cos0_percent, 'bx')
real_cos0_percent = np.array(SECONDS_OF_TRAFFIC * [COS0])
plt.plot(xdata, real_cos0_percent, 'r--', linewidth=2)
# COS1
plt.plot(xdata, estimated_cos1_percent, 'yx')
real_cos1_percent = np.array(SECONDS_OF_TRAFFIC * [COS1])
plt.plot(xdata, real_cos1_percent, 'r--', linewidth=2)
# COS2
plt.plot(xdata, estimated_cos2_percent, 'gx')
real_cos2_percent = np.array(SECONDS_OF_TRAFFIC * [COS2])
plt.plot(xdata, real_cos2_percent, 'r--', linewidth=2)
plt.show()
