Mesure-preliminaire
Leopold Clement 2 years ago
parent e329ee656b
commit 5002bba5a2

@ -0,0 +1,102 @@
import datetime
import random
import socket
import time
import yaml
from coapthon.client.helperclient import HelperClient
from coapthon.client.superviseur import SuperviseurGlobal, SuperviseurLocal
from coapthon.utils import parse_uri
from utils_learning import RequettePeriodique
n_capteur = 25
n_superviseur = 8
n_tirage_RTO = 8
tempdir = "dataset/"
host, port, path = parse_uri("coap://raspberrypi.local/basic")
try:
tmp = socket.gethostbyname(host)
host = tmp
except socket.gaierror:
pass
def produit_cartesien(l1, l2):
inter = [[elem1+elem2 for elem1 in l1] for elem2 in l2]
sum = []
for elem in inter:
sum += elem
return sum
def puissance_cartesienne(l1, n):
if n <= 1:
return l1
return produit_cartesien(puissance_cartesienne(l1, n-1), l1)
def tirage_charge():
return [random.choice([2, 3, 4, 5, 7, 10, 11, 9]) for _ in range(n_capteur)]
def tirage_RTO():
return [random.uniform(0.01, 2) for _ in range(n_capteur)]
super_gs = [SuperviseurGlobal([HelperClient(server=(host, port)) for _ in range(
n_capteur)], SuperviseurLocal) for _ in range(n_superviseur)]
requettes = [[RequettePeriodique(super_gs[idx_super].clients[idx_client], 5, path)
for idx_client in range(n_capteur)] for idx_super in range(n_superviseur)]
[[requette.start() for requette in line] for line in requettes]
file = open(tempdir+'data.yaml', 'a')
file.write("# run du {}-{}-{}\n".format(datetime.datetime.now().date(),
datetime.datetime.now().hour, datetime.datetime.now().minute))
file.close()
while True:
etat = tirage_charge()
print(etat)
for line in requettes:
for n, requette in enumerate(line):
requette.period = etat[n]
data = []
for n_iter in range(n_tirage_RTO):
print(n_iter)
rto_tests = [tirage_RTO() for _ in range(n_superviseur)]
for rto, super_g in zip(rto_tests, super_gs):
super_g.set_rto(rto)
for super_g in super_gs:
super_g.reset()
time.sleep(30)
for rto, super_g in zip(rto_tests, super_gs):
rtt_local = []
n_tokkens = []
n_envoies = []
n_echec = []
for client in super_g.clients:
rtt_local.append(client.superviseur.RTTs)
n_tokkens.append(client.superviseur._n_token)
n_envoies.append(client.superviseur._n_envoie)
n_echec.append(client.superviseur._n_echec)
data.append({
'rtos': rto,
'rtts': rtt_local,
'n_tokens': n_tokkens,
'n_envoies': n_envoies,
'n_echec': n_echec
})
file = open(tempdir+'data.yaml', 'a')
file.write(yaml.dump([{
'charge': etat,
'mesures': data
}]))
file.close()

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import yaml
import numpy as np
from matplotlib import pyplot as plt
file = open('dataset/data.yaml', 'r')
# file = open('dataset/data_restr.yaml', 'r')
data = yaml.safe_load(file)
file.close()
charge_tot_rtt = []
charge_tot_retrans = []
rtts = []
taux_retrans = []
for experience_charge in data:
charge_local = np.sum(30/np.array(experience_charge['charge'])/25)
for experience_capt in experience_charge['mesures']:
for capt in experience_capt['rtts']:
rtts += capt
charge_tot_rtt += len(capt) * [charge_local]
for n_t, n_e in zip(experience_capt['n_tokens'], experience_capt['n_envoies']):
if n_e != 0:
taux_retrans.append(1 - n_t/n_e)
charge_tot_retrans += [charge_local]
plt.figure(dpi=1)
fig, axs = plt.subplots(2, 1, sharex=True, figsize=(6, 6), dpi=1000)
hex0 = axs[0].hexbin(charge_tot_rtt, rtts) # , gridsize=20)
hex1 = axs[1].hexbin(charge_tot_retrans, taux_retrans) # , gridsize=20)
axs[0].set_ylabel('$RTT (s)$')
axs[1].set_ylabel("taux de retransmition")
axs[-1].set_xlabel('charge du réseau')
fig.tight_layout()
fig.savefig('charge-rtts.png')
fig.savefig('charge-rtts.svg')
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