{ "cells": [ { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Sujet 4 : Estimation de la latence et de la capacité d’une connexion à partir de mesures asymétriques" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On commence par déclarer les bibliothèques utilisés :\n", "\n", "Note : `urllib.request` n'y est pas car elle n'est utilisée que dans le cas où on doit télécharger les données." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "%matplotlib inline\n", "import re\n", "import gzip\n", "import time\n", "import pandas\n", "import io\n", "import os\n", "import datetime\n", "import matplotlib.pyplot as plt\n", "import statsmodels.api" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "## Connexion courte à l'intérieur d'un campus" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On commence par récupérer les données à étudier :" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Les données sont déjà présentes en local.\n" ] } ], "source": [ "def telecharger_fichier_si_necessaire(data_url):\n", "\n", " # Extrait le nom du fichier à partir de l'URL\n", " data_file = data_url[(data_url.rindex(\"/\")+1):]\n", "\n", " # Vérification de l'extention\n", " if data_file[-7:] != \".log.gz\":\n", " raise Exception(\"Le fichier nom de fichier \"+data_file+\" ne finit pas par \\\".log.gz\\\" !\")\n", "\n", " if not os.access(data_file, os.R_OK):\n", " import urllib.request\n", " print(\"Les données n'existent pas en local, on les télécharges.\")\n", " urllib.request.urlretrieve(data_url, data_file)\n", " if os.access(data_file, os.R_OK):\n", " print(\"Fichier récupéré.\")\n", " else:\n", " raise Exception(\"Le fichier n'a pas pu être récupéré !\")\n", " else:\n", " print(\"Les données sont déjà présentes en local.\")\n", "\n", "telecharger_fichier_si_necessaire(\"http://mescal.imag.fr/membres/arnaud.legrand/teaching/2014/RICM4_EP_ping/liglab2.log.gz\")" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On définit la fonction qui va lire chaque ligne pour en extraire les données. La ligne retournée sera formatée en CSV.\n", "\n", "Comme ce qui nous intéresse est le temps mis pour un aller-retour (ou \"ping\") il faut impérativement que celle ci soit présente pour que la ligne soit reconnue, pour les lignes dans ce cas on retournera `Ǹone`.\n", "\n", "Si la ligne est totalement illisible on soulèvera une exception afin d'avertir l'utilisateur qu'il y a des lignes dont le format est illisible par le programme. Ceci est préférable au fait de retourner `Ǹone` car si c'était le cas on risquerait de masquer des données utiles, par exemple si `ping` avait retourné des données en secondes plutôt qu'en millisecondes." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1421761682.052172,665,22.5\n", "\n", "None\n", "\n", "Exception (attendue) : La ligne \"[1421761682.052172] 665 bytes from lig-publig.imag.fr (129.88.11.7): icmp_seq=1 ttl=60 time=22.5 s\" n'est pas dans le format attendu.\n" ] } ], "source": [ "extractDataFromLineRegExp = re.compile(\"^\\[([0-9\\.]+)\\] ([0-9]+) bytes[^:]*: icmp_seq=[0-9]+ ttl=[0-9]+( time=([0-9\\.]+) ms)?$\")\n", "def extractDataFromLine(line):\n", " match = extractDataFromLineRegExp.match(line)\n", " if match and match[4]:\n", " return match[1]+\",\"+match[2]+\",\"+match[4]+\"\\n\"\n", " elif match:\n", " return None\n", " else:\n", " raise Exception(\"La ligne \\\"\"+line+\"\\\" n'est pas dans le format attendu.\")\n", "\n", "# Quelques essais\n", "print(extractDataFromLine(\"[1421761682.052172] 665 bytes from lig-publig.imag.fr (129.88.11.7): icmp_seq=1 ttl=60 time=22.5 ms\")) # Le retour à la ligne est inclus dans ce qui est retourné\n", "print(extractDataFromLine(\"[1421773281.582445] 13 bytes from stackoverflow.com (198.252.206.140): icmp_seq=1 ttl=50\"))\n", "print()\n", "try:\n", " print(extractDataFromLine(\"[1421761682.052172] 665 bytes from lig-publig.imag.fr (129.88.11.7): icmp_seq=1 ttl=60 time=22.5 s\"))\n", " print(\"On devrait avoir une exception ici.\")\n", "except Exception as e:\n", " print(\"Exception (attendue) : \"+e.args[0])" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Lit les données du fichier, utilise la fonction `extractDataFromLine` définit précédemment pour extraire les données et les placer dans une variables `csv_data` qui contiendra les données au format CSV.\n", "\n", "J'ai dans un premier temps essayé de ne pas passer par une variable intermédiaire et ajouter les données directement dans le DataFrame mais c'était extrêmement lent. Il aurait aussi été possible de passer par un fichier intermédiaire. En cas de données plus imposantes cela aurait été nécessaire." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Lu 44413 lignes en 0.190 sec\n" ] } ], "source": [ "def convertit_fichier_en_csv(data_file):\n", " nb = 0\n", " start_time = time.time()\n", " data = '\"date\",\"size\",\"time\"\\n' # La première ligne du CSV à les noms de champs\n", " with gzip.open(data_file, 'rb') as file:\n", " for line in file:\n", " line_data = extractDataFromLine(line.decode('utf-8').strip())\n", " if line_data:\n", " data += line_data\n", " nb += 1\n", "\n", " print (\"Lu %d lignes en %.3f sec\" % (nb, time.time() - start_time))\n", " return data\n", "\n", "csv_data = convertit_fichier_en_csv(\"liglab2.log.gz\")" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Traduit le tableau du format CSV en temps que DataFrame pandas. Comme on lit depuis le contenu d'une variable on utilise `io.StringIO` qui permet de lire une variable comme on lit un fichier." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/html": [ "
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28.80\n", "44007 1.421771e+09 41 1.14\n", "44008 1.421771e+09 1944 2.32\n", "44009 1.421771e+09 400 1.98\n", "44010 1.421771e+09 226 3.01\n", "44011 1.421771e+09 466 7.45\n", "44012 1.421771e+09 350 13.50\n", "44013 1.421771e+09 1829 45.90\n", "44014 1.421771e+09 1954 58.50\n", "44015 1.421771e+09 1074 1.45\n", "44016 1.421771e+09 46 1.11\n", "44017 1.421771e+09 1844 2.26\n", "44018 1.421771e+09 645 1.24\n", "44019 1.421771e+09 444 1.25\n", "44020 1.421771e+09 1940 2.46\n", "44021 1.421771e+09 1411 1.47\n", "44022 1.421771e+09 49 1.21\n", "44023 1.421771e+09 420 1.55\n", "44024 1.421771e+09 227 1.22\n", "44025 1.421771e+09 947 1.34\n", "44026 1.421771e+09 1960 2.43\n", "44027 1.421771e+09 531 1.19\n", "44028 1.421771e+09 374 1.14\n", "44029 1.421771e+09 1503 2.19\n", "44030 1.421771e+09 572 1.29\n", "44031 1.421771e+09 1338 1.47\n", "44032 1.421771e+09 1515 7.02\n", "44033 1.421771e+09 1875 2.33\n", "44034 1.421771e+09 1006 1.61\n", "44035 1.421771e+09 1273 1.35\n", "\n", "[44036 rows x 3 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pandas.read_csv(io.StringIO(csv_data))\n", "# csv_data = None # Libère la mémoire\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "### Premiers constats sur les données" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data['time'].plot(style='.')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On remarque quelques points avec un délai nettement plus importante que d'habitude.\n", "\n", "Sinon en histogramme (attention l'échelle est logarithmique) :" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data['time'].hist(log=True, bins=50)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On remarque bien que la majorité des requêtes ont une réponse quasi immédiate. Beaucoup ont une réponse dans les 30 ms. Les durées de 70~80 ms semble être surprenamment courantes. Il n'y a que très peu de réponses dont la durée est supérieure à 90ms." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "### Y a t'il une variabilité par heure ou par jour de la semaine ?\n", "\n", "Comme il s'agit d'un campus on peut s'attendre à une variabilité des performances due aux activités. On peut supposer que le réseau soit plus chargé durant les jours ouvrées et aux heures de travail." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "hideCode": false, "hideOutput": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def timestamp_vers_heure(timestamp):\n", " str_time = datetime.datetime.fromtimestamp(timestamp).strftime('%H:%M:%S')\n", " parts = str_time.split(':')\n", " return float(parts[0]) + (float(parts[1]) / 60.0) + (float(parts[0]) / 3600.0)\n", "\n", "raw_data['heure'] = [timestamp_vers_heure(ts) for ts in raw_data['date']]\n", "raw_data.plot(x='heure', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Il semblerait que seuls quelques heures dans l'après midi soit présentes. Les données ont été prises juste sur quelques heures ou plusieurs jours aux mêmes heures ? Il aurait fallu vérifier la durée des observations." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20/01/2015 13:48:02\n", "20/01/2015 16:26:26\n" ] } ], "source": [ "print(datetime.datetime.fromtimestamp(raw_data['date'].min()).strftime('%d/%m/%Y %H:%M:%S'))\n", "print(datetime.datetime.fromtimestamp(raw_data['date'].max()).strftime('%d/%m/%Y %H:%M:%S'))" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Les données ne sont présentes que pour une petite tranche horaire durant une seule journée. Il s'agit d'un mardi donc jour ouvré mais je ne penses pas que l'on puisse faire des statistiques liés à la variation de charge réseau. Les données ne montrent pas de fortes variations qui pourrait être expliquée par un usage très différent du réseau à un moment donné." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "### Temps de transmission en fonction de la taille des messages et effet de la segmentation.\n", "\n", "On va commencer par une petite visualisation graphique du phénomène :" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data.plot(x='size', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On voit bien les effets de la segmentation du paquet qui commence un peu avant 1500. C'est visiblement ce qui à été à l'origine de la bizarrerie que j'avais constaté et qui fait qu'il y a une augmentation du nombre de requêtes autour de 70~80 ms par rapport à des durées légèrement plus brèves.\n", "\n", "Il faut donc savoir si on veut tester la transmission avec ou sans la capacité des routeurs à segmenter les paquets.\n", "\n", "Le fait que la limite soit proche de 1500 laisse penser que le réseau est basé sur de l'Ethernet sans jumbo frames ce qui est cohérent avec ce que l'on trouve habituellement dans les universités. Le MTU de l'Ethernet est de 1500 auquel il faut soustraire la taille de l'entête IPv4 qui est de 20 octets (sauf options mais peu probable). L'entête du paquet ICMP (8 octets) est normalement inclus dans le retour de la commande `ping` donc on ne le retranchera pas.\n", "\n", "Il aurait été intéressant de tester le MTU grâce aux commandes suivantes :\n", "```\n", "ping -4 -M do -s 1472 lig-publig.imag.fr\n", "ping -4 -M do -s 1473 lig-publig.imag.fr\n", "```\n", "Si le MTU est bien de 1500 (incluant l'entête IPv4) la première commande devrait réussir mais la seconde échouer. Je précise que contrairement à la sortie de la commande, le paramètre \"-s\" n'inclus pas les 8 octets de l'entête ICMP.\n", "\n", "### Cas sans segmentation (size <= 1480) \n", "\n", "On sélectionne donc les entrées de 1480 octets ou moins :" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/html": [ "
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51.421762e+0948921.9013.803611
71.421762e+09114625.1013.803611
81.421762e+0988424.0013.803611
91.421762e+09142219.5013.803611
101.421762e+09118018.0013.803611
111.421762e+0999918.8013.803611
121.421762e+09102024.3013.803611
131.421762e+09713.4513.803611
141.421762e+09345.8513.803611
161.421762e+094071.1413.803611
171.421762e+093561.1013.803611
191.421762e+095871.2713.803611
201.421762e+098091.3313.803611
211.421762e+0913641.5113.803611
221.421762e+0911531.4413.803611
231.421762e+098531.3013.803611
251.421762e+091231.2113.803611
271.421762e+099331.3413.803611
281.421762e+099221.4213.803611
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331.421762e+0913481.4613.803611
341.421762e+097601.3013.803611
351.421762e+0910761.4113.803611
...............
439881.421771e+09671.0416.437778
439911.421771e+092671.2516.437778
439921.421771e+0911691.3016.437778
439931.421771e+0911651.3316.437778
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439971.421771e+098321.3316.437778
439981.421771e+0914391.4116.437778
440011.421771e+099781.4416.437778
440021.421771e+0910971.3316.437778
440031.421771e+098551.4616.437778
440071.421771e+09411.1416.437778
440091.421771e+094001.9816.437778
440101.421771e+092263.0116.437778
440111.421771e+094667.4516.437778
440121.421771e+0935013.5016.437778
440151.421771e+0910741.4516.437778
440161.421771e+09461.1116.437778
440181.421771e+096451.2416.437778
440191.421771e+094441.2516.437778
440211.421771e+0914111.4716.437778
440221.421771e+09491.2116.437778
440231.421771e+094201.5516.437778
440241.421771e+092271.2216.437778
440251.421771e+099471.3416.437778
440271.421771e+095311.1916.437778
440281.421771e+093741.1416.437778
440301.421771e+095721.2916.437778
440311.421771e+0913381.4716.437778
440341.421771e+0910061.6116.437778
440351.421771e+0912731.3516.437778
\n", "

32667 rows × 4 columns

\n", "
" ], "text/plain": [ " date size time heure\n", "0 1.421762e+09 665 22.50 13.803611\n", "1 1.421762e+09 1373 21.20 13.803611\n", "2 1.421762e+09 262 21.20 13.803611\n", "3 1.421762e+09 1107 23.30 13.803611\n", "4 1.421762e+09 1128 1.41 13.803611\n", "5 1.421762e+09 489 21.90 13.803611\n", "7 1.421762e+09 1146 25.10 13.803611\n", "8 1.421762e+09 884 24.00 13.803611\n", "9 1.421762e+09 1422 19.50 13.803611\n", "10 1.421762e+09 1180 18.00 13.803611\n", "11 1.421762e+09 999 18.80 13.803611\n", "12 1.421762e+09 1020 24.30 13.803611\n", "13 1.421762e+09 71 3.45 13.803611\n", "14 1.421762e+09 34 5.85 13.803611\n", "16 1.421762e+09 407 1.14 13.803611\n", "17 1.421762e+09 356 1.10 13.803611\n", "19 1.421762e+09 587 1.27 13.803611\n", "20 1.421762e+09 809 1.33 13.803611\n", "21 1.421762e+09 1364 1.51 13.803611\n", "22 1.421762e+09 1153 1.44 13.803611\n", "23 1.421762e+09 853 1.30 13.803611\n", "25 1.421762e+09 123 1.21 13.803611\n", "27 1.421762e+09 933 1.34 13.803611\n", "28 1.421762e+09 922 1.42 13.803611\n", "29 1.421762e+09 24 1.12 13.803611\n", "31 1.421762e+09 1122 1.61 13.803611\n", "32 1.421762e+09 995 1.44 13.803611\n", "33 1.421762e+09 1348 1.46 13.803611\n", "34 1.421762e+09 760 1.30 13.803611\n", "35 1.421762e+09 1076 1.41 13.803611\n", "... ... ... ... ...\n", "43988 1.421771e+09 67 1.04 16.437778\n", "43991 1.421771e+09 267 1.25 16.437778\n", "43992 1.421771e+09 1169 1.30 16.437778\n", "43993 1.421771e+09 1165 1.33 16.437778\n", "43994 1.421771e+09 1272 1.36 16.437778\n", "43997 1.421771e+09 832 1.33 16.437778\n", "43998 1.421771e+09 1439 1.41 16.437778\n", "44001 1.421771e+09 978 1.44 16.437778\n", "44002 1.421771e+09 1097 1.33 16.437778\n", "44003 1.421771e+09 855 1.46 16.437778\n", "44007 1.421771e+09 41 1.14 16.437778\n", "44009 1.421771e+09 400 1.98 16.437778\n", "44010 1.421771e+09 226 3.01 16.437778\n", "44011 1.421771e+09 466 7.45 16.437778\n", "44012 1.421771e+09 350 13.50 16.437778\n", "44015 1.421771e+09 1074 1.45 16.437778\n", "44016 1.421771e+09 46 1.11 16.437778\n", "44018 1.421771e+09 645 1.24 16.437778\n", "44019 1.421771e+09 444 1.25 16.437778\n", "44021 1.421771e+09 1411 1.47 16.437778\n", "44022 1.421771e+09 49 1.21 16.437778\n", "44023 1.421771e+09 420 1.55 16.437778\n", "44024 1.421771e+09 227 1.22 16.437778\n", "44025 1.421771e+09 947 1.34 16.437778\n", "44027 1.421771e+09 531 1.19 16.437778\n", "44028 1.421771e+09 374 1.14 16.437778\n", "44030 1.421771e+09 572 1.29 16.437778\n", "44031 1.421771e+09 1338 1.47 16.437778\n", "44034 1.421771e+09 1006 1.61 16.437778\n", "44035 1.421771e+09 1273 1.35 16.437778\n", "\n", "[32667 rows x 4 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "non_frag = raw_data[raw_data['size'] <= 1480]\n", "non_frag" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On regarde les données sélectionnées sous forme de graphique :" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "non_frag.plot(x='size', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Et l'histogramme de répartition des durées (attention échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "non_frag['time'].hist(log=True, bins=50)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On remarque bien l'absence du pic vers 70~80 ms que l'on avait avant.\n", "\n", "On tente une régression linéaire :" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
OLS Regression Results
Dep. Variable: time R-squared: 0.000
Model: OLS Adj. R-squared: 0.000
Method: Least Squares F-statistic: 14.75
Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.000123
Time: 17:48:17 Log-Likelihood: -1.0715e+05
No. Observations: 32667 AIC: 2.143e+05
Df Residuals: 32665 BIC: 2.143e+05
Df Model: 1
Covariance Type: nonrobust
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
coef std err t P>|t| [0.025 0.975]
const 3.2757 0.072 45.301 0.000 3.134 3.417
size 0.0003 8.5e-05 3.841 0.000 0.000 0.000
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Omnibus: 41906.256 Durbin-Watson: 0.637
Prob(Omnibus): 0.000 Jarque-Bera (JB): 31002700.511
Skew: 6.581 Prob(JB): 0.00
Kurtosis: 153.346 Cond. No. 1.73e+03


Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 1.73e+03. This might indicate that there are
strong multicollinearity or other numerical problems." ], "text/plain": [ "\n", "\"\"\"\n", " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: time R-squared: 0.000\n", "Model: OLS Adj. R-squared: 0.000\n", "Method: Least Squares F-statistic: 14.75\n", "Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.000123\n", "Time: 17:48:17 Log-Likelihood: -1.0715e+05\n", "No. Observations: 32667 AIC: 2.143e+05\n", "Df Residuals: 32665 BIC: 2.143e+05\n", "Df Model: 1 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "const 3.2757 0.072 45.301 0.000 3.134 3.417\n", "size 0.0003 8.5e-05 3.841 0.000 0.000 0.000\n", "==============================================================================\n", "Omnibus: 41906.256 Durbin-Watson: 0.637\n", "Prob(Omnibus): 0.000 Jarque-Bera (JB): 31002700.511\n", "Skew: 6.581 Prob(JB): 0.00\n", "Kurtosis: 153.346 Cond. No. 1.73e+03\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", "[2] The condition number is large, 1.73e+03. This might indicate that there are\n", "strong multicollinearity or other numerical problems.\n", "\"\"\"" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "size_stat = non_frag['size']\n", "size_stat = statsmodels.api.add_constant(size_stat)\n", "model = statsmodels.api.OLS(non_frag['time'], size_stat).fit()\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "On regarde l'évolution de la durée en fonction de la taille du paquet (attention, échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def affiche_points_et_regression(points, model):\n", " plt.scatter(points['size'], points['time'], marker=\".\")\n", " plt.plot(points['size'], model.predict(), color='black')\n", " plt.yscale('log')\n", " plt.show()\n", "\n", "affiche_points_et_regression(non_frag, model)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Cela semble être cohérent, calcule les paramètres L et C de la connexion :" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "La latence est de L=0.003276s (soit 3.276ms)\n", "La capacité est de C=3064515 octets/s (soit 3.06 Mo/s ou 24.52 Mbps)\n" ] } ], "source": [ "def print_details_connexion(model):\n", " print(\"La latence est de L=%fs (soit %.3fms)\" % (model.params.const / 1000, model.params.const))\n", "\n", " temps_en_ms_pour_1octet = model.params.tolist()[1]\n", " temps_en_s_pour_1octet = temps_en_ms_pour_1octet / 1000.0\n", " nombre_octets_dans_1s = 1.0 / temps_en_s_pour_1octet\n", " print(\"La capacité est de C=%.0f octets/s (soit %.2f Mo/s ou %.2f Mbps)\" % (nombre_octets_dans_1s, nombre_octets_dans_1s / 1000000, nombre_octets_dans_1s / 1000000 * 8))\n", "\n", "print_details_connexion(model)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "### Cas avec segmentation (size > 1480) \n", "\n", "On sélectionne les entrées de plus de 1480 octets et affiche l'histogramme de répartition des durées (attention échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "avec_frag = raw_data[raw_data['size'] > 1480]\n", "avec_frag['time'].hist(log=True, bins=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le fameux pic vers 70~80 ms réapparaît bien.\n", "\n", "Calcule la régression :" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
OLS Regression Results
Dep. Variable: time R-squared: 0.000
Model: OLS Adj. R-squared: 0.000
Method: Least Squares F-statistic: 4.050
Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.0442
Time: 17:48:18 Log-Likelihood: -50605.
No. Observations: 11369 AIC: 1.012e+05
Df Residuals: 11367 BIC: 1.012e+05
Df Model: 1
Covariance Type: nonrobust
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
coef std err t P>|t| [0.025 0.975]
const 5.2898 2.244 2.357 0.018 0.891 9.689
size 0.0026 0.001 2.012 0.044 6.7e-05 0.005
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Omnibus: 6230.343 Durbin-Watson: 0.677
Prob(Omnibus): 0.000 Jarque-Bera (JB): 33724.913
Skew: 2.764 Prob(JB): 0.00
Kurtosis: 9.374 Cond. No. 2.02e+04


Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 2.02e+04. This might indicate that there are
strong multicollinearity or other numerical problems." ], "text/plain": [ "\n", "\"\"\"\n", " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: time R-squared: 0.000\n", "Model: OLS Adj. R-squared: 0.000\n", "Method: Least Squares F-statistic: 4.050\n", "Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.0442\n", "Time: 17:48:18 Log-Likelihood: -50605.\n", "No. Observations: 11369 AIC: 1.012e+05\n", "Df Residuals: 11367 BIC: 1.012e+05\n", "Df Model: 1 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "const 5.2898 2.244 2.357 0.018 0.891 9.689\n", "size 0.0026 0.001 2.012 0.044 6.7e-05 0.005\n", "==============================================================================\n", "Omnibus: 6230.343 Durbin-Watson: 0.677\n", "Prob(Omnibus): 0.000 Jarque-Bera (JB): 33724.913\n", "Skew: 2.764 Prob(JB): 0.00\n", "Kurtosis: 9.374 Cond. No. 2.02e+04\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", "[2] The condition number is large, 2.02e+04. This might indicate that there are\n", "strong multicollinearity or other numerical problems.\n", "\"\"\"" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "size_stat = avec_frag['size']\n", "size_stat = statsmodels.api.add_constant(size_stat)\n", "model = statsmodels.api.OLS(avec_frag['time'], size_stat).fit()\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On regarde l'évolution de la durée en fonction de la taille du paquet (attention, échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "affiche_points_et_regression(avec_frag, model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Cela semble être cohérent, calcule les paramètres L et C de la connexion :" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "La latence est de L=0.005290s (soit 5.290ms)\n", "La capacité est de C=387760 octets/s (soit 0.39 Mo/s ou 3.10 Mbps)\n" ] } ], "source": [ "print_details_connexion(model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "C'est nettement moins performant !" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Connexion vers un site Web éloigné assez populaire\n", "\n", "Tout d'abord, récupération des données. Le fichier est au même format donc on peut utiliser les mêmes fonctions que précédemment :" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Les données sont déjà présentes en local.\n", "Lu 6887 lignes en 0.044 sec\n" ] } ], "source": [ "telecharger_fichier_si_necessaire(\"http://mescal.imag.fr/membres/arnaud.legrand/teaching/2014/RICM4_EP_ping/stackoverflow.log.gz\")\n", "csv_data = convertit_fichier_en_csv(\"stackoverflow.log.gz\")\n", "raw_data = pandas.read_csv(io.StringIO(csv_data))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Regarde si, comme le site proche, les données ont été récupérées sur une courte période :" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20/01/2015 16:26:43\n", "20/01/2015 17:04:20\n" ] } ], "source": [ "print(datetime.datetime.fromtimestamp(raw_data['date'].min()).strftime('%d/%m/%Y %H:%M:%S'))\n", "print(datetime.datetime.fromtimestamp(raw_data['date'].max()).strftime('%d/%m/%Y %H:%M:%S'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "C'est le cas, on regarde tout de même si il semble y avoir une variation notable des performances :" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data['time'].plot(style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On voit que le temps d'attente est parfois plus long. C'est attendu dans le cas d'un site distant et/ou plus chargé. C'est assez curieux mais il semble que le délai minimum diminue très légèrement avec le temps. Peut être un réseau moins chargé ? La commande `ping` ne donne que 3 chiffres significatifs. C'est peut être la cause d'un effet d'arrondi.\n", "\n", "Pourrait t'il y avoir un lien entre l'heure et la taille des paquets envoyés (ils sont sensés être aléatoire) ?" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data.plot(x='date', y='size', style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visuellement il n'y a rien qui indique qu'il y ait un biais à ce sujet.\n", "\n", "On va donc voir le temps de transmission en fonction de la taille :" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "raw_data.plot(x='size', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cas sans segmentation (size <= 1480) \n", "\n", "On sélectionne donc les entrées de 1480 octets ou moins :" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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31j+nKBvq3s2WEsCMSsB4iEsSUTVo4kBQu9ZuP4Drl6/W8ideX1Tlsf1niq6jb/hlioOEkTBxZlXfbgyP/OoLThVUbIotaWe62sK0ThPBdlXf7rrPlRE2FqQbRQBLW1AP63OTZxJVT1Ab1GfJGPucomxQyx8OGQ9xSSKqBk0cCGrXmq2D+v7E44uAsf2XFg3v6IOy5eqOtxBay/X7b7a20GgZqqBiMwMv7UxXW5jW6Qq2LmGC7RXdM+s+l1sosB6t51lgASxNO6P63OSZRNUT1Ab1WRLGPqcoG9TyW0PGQ1x0noPJWAtr1+L5U/X9ieOLSs7lJZ/r06DhQzeAxOhtITF6O0iMXmL0EqP3IS1HH3V+xQs78MiLO9BeLuHMUzpCX4ywOtRzaQ1idbbIlIlt6Nt1MPGXle5smKQOWKfMJH1py8HG+cJLavPho8NYvXUQ0ydNwLJLzgjtX53yXac0cHgI0zra0T1rsrZTcd+LIFsee6kfbx4eAgOY3tEeOva8zsxr679v2INnNuzBkq4ZuPnKsyP72CZpzvYJesZhXwJJGDeOPm62qSoqAcHiVVgd6jnvPrM2hSZvPVWfRxZXUNbNWPU7ZiKS6tSj7tFr0pe2RNA4onTc5+/ee2y4WldmuQQ88qnf8O1fnfJVQdRFJwt4jHCu2OIVHV3Cxp4rOLa2/EqEJCKMeAbxsovnZ+bsbYvlOv4nTKhNyrgXY6POq6ISECxehdWhnlP3mbUlNHnr8SOuoBwkPOlmsdqsR+07k760JYLGEaWT2qxSqSKwf3XKV4VDF502jRHOFVuGR8YOwLCxBziCo0eEHFEG8TMb9gTaYxvbYrmO/wkTarOi4R19lOgSdF4VlYBg8SqsDvXcFd0zUxGa3HpcEYeU83EF5SDhSXf5YJv1qH1n0pe2RNA4onRSm9VnWS4hsH91yleFQxedLOAxwrlii1d0dAkae3WCo2dCREupvowlXTMC7bGNbbFcx/+ECbVZ0fChG0Bi9BKjN7MjConRS4zeZnkSo3ewsQSCd1bHf/0vcwJfhqC/dR1HkPIe58vGxMnp1qNTr8k1Wc108Wt7ktkjWc100pkFo/sl6DrQaR3tWrNVbHzZBY25oBkhScaD7XGmvvNRdbvOtsvzpQeY/RCzPU6TMq4cvSogLbt4Ph5YvW2MYOXNSotayjRIPPTLjgPCl9tNKkTGXdZXR3gyEZqz2hv1tqu6cMdTG2JneMaxO+49UZmqukK1KnJGZZTaEKSDhN6gJZyTjAfb40x95//mmnMDnb1f/6oCcdz+SjJObTBuxFhgrID0zIY9/oKVN0M2YinTIPHQLzsujiBsKkTq1KOic72J0JyWiOTXF0kyPOPYHfeeqExVXaFaFTl1MkqTCtJBYzBoCeck48H2OFPfeb/JFd7y1f5VBeK4/WUjEzkLIh09Ed1PRPuIqM9z7K+J6BUiWk9EPySiWZ5ztxDRZiLaRESXp2W4F1VAWtI1w1+w8mbIKtmyOuKeKnK54m0cQdhUiNSpR0XnehOhOS0Rya8vkmR4xrE77j1Rmaq6QrUqcupklCYVpIPGoNsiVbxNMh5sjzP1nfebXOEtX+1fVSCO2182MpGzIDJ0Q0QXAzgC4EF3X1gimsTMh5y//xzAOcy8jIjOAbASwIUAZgH4EYCzmHkkrA6J0UuMXmL0EqOXGL05VmP0EZuD3wJgDjN/2vkbzPy3zrkfALiDmVeHlZ/GevRxB7zNNcpN7DGZ0WLypRE068HE6Yd9icZNStK9P6it3lkMm/YcrkvJnzKxDRt2HRydceK+gN6XMmgWSpjzsPGlZ+IYdL+kv/7sFuw9dAwfe8+cUZuTfCH4zRIJG59+DjSszrTeMVNM+yhvp+5HqpuDOxXcCeCPABwEcJlz+FQAazyX9TvHMiWJKGVj6VBTe4LO64i4YcKuV1TT2UfTr75New6Pil7Pv/Ymdgy+PSp0xxFoTZ5NoCDuEdYefnHnaALO86+9CQKg/nR5tHcn7ri6u044A8Y+Z6/A9/xrbwJAneNMKkyr4m3SvXjXbj+A65avHo0/v9xfs33hjI7Yoq0qXH5nbT/u+ODYiQHu+PQTOf3eHbdOm3v1JsH0nVSF17BnV0Rii7HMfCsznwbgIQCfcQ6PzaYY+97VLiRaSkS9RNQ7MDAQ1wxfkohSrsFZLpkadF5HxA0TdutENQ3hya/sKKHbtI9Mnk2gIO5xLGqWpd9gGx7hMcKZe21YtrT3sw1hOkq8Va/VEdJVkXFV3+5Eoq1aZtDEgKD6g94dt84goTdrTPuokYRXP2zMulkB4CPO3/0ATvOcmw1gl99NzLycmXuYuaezs9OCGb8iriiV1tKhcUU0HRE3TNitE9U0hCe/sqOEbtM+Mnk2gYK4R1hTsyz9fmm0ttAY4QwY+5zDBD4bwnSUeKteqyOkqyLjFd0zE4m2aplBEwOC6g96d0bfMfe6lAX+KEz7qJGEVz9ixeiJaAEzv+b8/d8AXMLM1xJRF2qO3xVjfwxgQRZirIrE6CVGLzF6idGHMZ5i9DqzblYCuBTANAB7AdwO4EoACwFUAWwHsIyZ33CuvxXAJwBUANzEzKuijMhzc3Bd1Fk8SdeyDxr0foPJvfbw0WH8aONegAifeO+80HXd73p6Y2CKuY7DM2mLzvU2Z+94+2PD7kOBX0AmM17SmEmStOygMvwccVRduna641Ht2yj71GURwma2eOvasOugtuOM+oED+L+XNmazBT2DsFlSWcxmG1eZsWnjFWbKLSVUq1W44bqwJVqjRE9VmPLLtLvj6u46YdVLuVSLdar13PX0Rtz73NbR67zLwKqCIBAsjCURtW1lVAbVoS7t682GDsosjit6mrbXRtlBZQTtdwwEZ02b2Om3Oqpp1qkLoRb28C6lrE4UcInKKo2amBD0Xqr9EifjPOoZ+NkfJXjbeh/GVWZs2qjCjFfTi5PlFyRM+Qk+qrDqpVL1F7XUZV+9n1VB0Fu/iWjnh4moHBe3LBVVJA4SEHVtNrElzaWTfUVBn2VvowRWXTv9MM06dXGFWe9SykHjOUrc1JmE4PdeBk1UMMk4j3oGfvYneR5pII5eA1WY8Wp6cbL8goQpP8HHFcL8RMZyCb71qMu+ej+rgqC3fhPRzg8TUTkubllqf6gicZCAqGuziS1pLp3sKwr6LHsbJbDq2FnyG2Qwzzp1cYVZ71LK6kSB0XZEiJs6kxD83sugiQomGedRz8DP/iTPIw0kdKOJxOglRh/nXonRS4xeYvQOWc26SdsJxZmZkLWTiTPIo9oWNdsnapDHddBx+sT03rhOycSuKKcRp01pfLEW6cveBuqXRJhtpssthG0ibrMPUs+MLTJRwk0aQmGYEKmKVV7xVUcwNKnPtA+C+kW3bSbL3PqVpbM8s60+Mb3X7RtVODTNiowS5tTx4S0/TpvSEL+LJMjbQJ1gEba3b1jGtF+5QdnPefZBU8bodYQb20JhWPmqcGMqGJrUZ9oHJuJxVN9FLXMbdk8WfWJ6ryqau9hcNtlvfHjLj9OmNMTvIgnyNlDtCdvb13hJ5Ip/Bm2efdCUjl5HuLEtFIaVPyZ70FAwNKnPtA9MxOOovota5jbsHlMRNU6fmN6riuYuNpdN9hsf3vLjtCkN8btIgrwNVHvC9vY1XhK57J9Bm2cfSIw+5LiNOt3jEqMPLkti9BKjz4PxFKNvSkcfx9l48T5Uv5ktYQ8yzJ6gARX2Ynhnx6gbgXvbabJJeBozQXT7TWcWgreP/PrL1K6out3zOhs4J/2SMnEuOsR9ljrviG75uuMwT9Lsp7jP1OTLI4hx6+i9gkfQksNhooi6F2VZyT4F/PeNDXsJRkUfn6WCgWCRWM1gdWkrl+qWjvUmukRl6iYRO/3a5JbhXc4YAMothKpH3ApqZ1gfRYlkOnbpiGCqIKr2YVD5pkJy1Fiw8Rx0vwx1luXWKV8tyyWoD/MgzX6K+0xN9rwNY9xmxnoFD8B/2dQwUUQVWipK9mmY2BJlj99SwaEiro+TB8aKluo5E/EzjiDkZ/OYflPErShBMqiPwkQyHbvCjnvv88s2jSrfVEiOGgumxBX3dN4R3fLVslyKILi6pNlPcZ+picBrg6Zz9KMCWsiSw2GiiCq0lJXs0zCxJcyeoH1qQ0Xcsv/jqRM+aew5E/EzjiDkZ/OYflPErShBMqiPwkQyHbvCjnvv88s2jSrfVEiOGgumxBX3dN4R3fLVslyKILi6pNlPcZ+picBrg6YL3QASo5cYvcTode+TGL3efRKjt0BWSyDE7ViTB2n6Yuiuy53mjAVdB6w7qyZpnTrnda9Jo0yTenWvNXkGSW2Kc8+KF3bgkRd3YPqkCVh2yRmxZmfpfJFGEfVjQpc0xo5J3Tb6AhBHP4a44odJBp2JeGWyd2aaGXVhZYeJj0n21tURR+Nm68atM416da81eQY2+sL0Hr8JCo986je07dAVu6OImihh8gVne+zoYqsvXMatGBtEXPFDFXLCxEET8SosezTKBpsil7ZI6iMAB4l4SerUOa97TRplmtSre63JM7DRF6b3+E1QMLFDV+yOImqihC5pjB2Tum30hSmRjp6I7ieifUTU5zn2ZSL6BRG9QkSPE9FJzvG5RHSUiNY7/92bpvEmxBU/VCEnTBw0Eq+czzp7Z8YVk+K0T0fITbq3ro44GjdbN26dadSre63JM7DRF6b3+E1QMLFDV+yOImqihC5pjB2Tum30hSk6WwleDOAIgAc9e8Z+AMBPmLlCRHcDADP/pbq3rC4So5cYvel53WvSKFNi9BKjT0JhY/RhDpyIrgFwLTPfkKej93sQcZxJmgMgzmwgv8+6gyTpgEoyuG29GLa+EPxmScWZBWQ6trLcCDuNHwNJ2xH1jgGoK99v5k6aP3K86HyJpDVjLS5ZOvqnADzCzN92rtsA4JcADgH4H8z8fFT5SR29n1gCmO0Dqbtkb1S9UcJc0iV8/fYLDXI0SUSfJAKULfHKlmjrl8kMaGbq+gjwYfeq9ycRrW32VZIyTSYORNkEwLdv/bYxVDPAbU9E8KIKva0thBFl0oWNPrb9nDIRY4noVgAVAA85h3YDmMPM7wbwOQAriGhSwL1LiaiXiHoHBgaSmOErlsQR/NIUaXRE2DDxM2y/0KD6kog+SQQoW+KVLdHWL5PZRABVBXgTu4D4orUJaQj2cSYORNkU1Ld+2Mrk1kEVev0mXdjo4zSekw6xHT0RfRzAVQBuYOefBcw8xMyDzt9rAWwBcJbf/cy8nJl7mLmns7MzrhkAzJYlTnKPTr1R1yZdwldXyEkq+iQRoGyJV7ZEW79MZhMBVBXgde1KKlqbkIZgH2fiQJRNfn3r9pOSXGstk1sHVej1m3Rho4/TeE46xArdENESAF8BcAkzD3iu6wSwn5lHiGg+gOcBnMvM+8PKlxh9cHkSo5cYvS4So0/GuI7RE9FKAJcCmAZgL4DbAdwCoB2A+++ONcy8jIg+AuCLqIVzRgDczsxPRRmR1hIIYS9wGi9glJPWsS2uYw6q27vJs+kshbRme9guIytH4FdX2CyTsC+KIrTFBrr9EXR9nDqS2Jd2fTr3F9LRZ0FayxQHiWxxxSWTev2WrAXCBcC44mlQ3epep2WDTEJdoTNvcSoNEVK3rqBlievEXIOla7Nsiw10+yPo+rT3v826Pp37G1KMLSI6IltcccmkXj8RKcq2uOJpUN3qV7hJJqGu0Jm3OJWluKXzjMdcZ7B0bV5CXVx0+yPoep32ZT0pIO3x2HBibFHREdniiksm9fqJSFG2xRVPg+pWxS2TTEJdoTNvcSpLcUvnGY+5zmDp2ryEurjo9kfQ9Trty3pSQNrjsdBibNpIjP5X90uMXmL0EqNPfk9e9encLzH6BOjOoIgzuyYrh5cGedjl94WVpL+DZs2E3Wv7izzPL5Ms6mjkMR5FWFsB8z0BitQPuo6+nIUxaaMjwMbNgM1KlEyDPOxSReXvrO03ym70E/jueGrDaGbro707A/foTSsjNU/BN426TEXUrOxKg7C2xtm3t1H7oSli9DoCbNwM2KxEyTTIwy4/Udkku9FP4NPdo9d7L2AvIzVPwTeNukxF1KzsSoPQtsbYt7dR+6EpHL2OABugutQ1AAAbuUlEQVQ3AzYrUTIN8rDLT1Q2yW70E/h09+gdFdstZ6TmKfimUZepiJqVXWkQ2tYY+/Y2aj9IjF5i9KnUKTH6YtclMfrxFaNvGkfvR1op4WktK5BErY96cYs0OL3ozFpJ8kWc9KXOg6RjzFuOLScWdyZblv1f1DEOpGfbuBJj/UhDNPETGm0t/Zskoy5KXNMR2/IgqE0mz063X6L2+y0KSceYtxxbWaFxs80Bz5LEMYTPtNubFUWwrSli9H6kIZr4CY22MvWSZNRFiWtZLfVqSlCbbInl6rmw/X6LQtIx5i3HVlaoTh/7ZZvX3RdD+Ey7vVlRBNua1tGnIZr4CY22MvWSZNRFiWtZLfVqSlCbbInl6rmw/X6LQtIx5i3HVlaoTh/7ZZvX3RdD+Ey7vVlRBNskRh+jTInR20Ni9GORGH08ijrGgfxj9E3t6JuFJDNJ1AEWd4P0ZsL2sgVx6strNpRu+/KY+RNmY5S9WVOUL5VxL8Y2C2Fil6m49scXzcW9z20FADz/2psAMO6cvY7gaFO4TZqZbQuT9uWRnRsm3hZNSC+CuGpK08bom4UwsUv3XveeZzbsqTuv7pM5HtAVHG0Jt3715SHOmbQvC/si+0URb4skpBdBXDUl0tET0f1EtI+I+jzHvkxEvyCiV4jocSI6yXPuFiLaTESbiOjytAwfL4SJXbr3uiLQkq4ZdefVfTLHA7qCoy3h1q++PMQ5k/ZlYV9kvyjibZGE9CKIq6bobCV4MYAjAB707Bn7AQA/YeYKEd0NAMz8l0R0DoCVAC4EMAvAjwCcxcwjYXUkidEnETd1y8o7xppGjL5r5iR0nNAa2SaTrNQkbbOdmWg6Lla8sAOPvLgD0ydNwGULp2PDroPW2hx3/CQdY2GC/KY9h0O1mixE1LB+mTKxre4ZhNmQ9rsYNV6WXXJGZL1paWNWxVh1c3Dl3DUArmXmG4joFgBg5r91zv0AwB3MvDqs/LiOPkkCkm5ZRYmx2kS3TQBw/TfWjK4c2dZCgStH2rLDxuqBpuWueGEH/urxV0c/lw22XEyLpHFgW+9GHvHoItkX9K6YvBfq+Pqba8615uyz3ErwEwBWOX+fCmCn51y/c2wMRLSUiHqJqHdgYCBWxUkSkHTLKkqM1Sa6bVqzdVB75Uhbdti4x7RcVauoGGy5mBZJx5itd6MIekKe9tl4L9TxlYc2lsjRE9GtACoAHnIP+Vzm+08GZl7OzD3M3NPZ2Rmr/iQJSLplFSXGahPdNi2eP1V75Uhbdti4x7RcVasoG2y5mBZJx5itd6MIekKe9tl4L9TxlYc2Fjt0Q0QfB7AMwPuY+R3nWKahG2B8xOjTQLdNzRij98MbQzXdcjEtbMfo45ad95z/vO2z8V40ZIyeiJYA+AqAS5h5wHNdF4AV+JUY+2MAC9IUY+OiPigg2b6etr5U1GtsZEia1Kl7fZjQByDQ7iJ9QTZK1mySbFW3bTbHelrtsUWaX5BFw5qjJ6KVAC4FMA3AXgC3A7gFQDsANzC1hpmXOdffilrcvgLgJmZepZapkrWjX7v9QJ2YUm4hlACthAwb4qyuoOhdxbCtXIq1iqFJnbrXq+fU7dmqACo+dhcp0aQugSjllRWTYDJJwO/5lEtU22nLeR7lElAqlbTamsbzykM8tSViFxFrYiwzX8/MM5m5lZlnM/N9zHwmM5/GzIuc/5Z5rr+Tmc9g5oU6Tj4PVDGlMsLaCRk2xFldQdHGKoYmdeper55Tt2erBNhdJBE7LDmnSOK6ySQB33ucse1SqUK7rWk8rzzE0yLZlxfjMjNWFVPKLaSdkGFDnNUVFG2sYmhSp+716jl1e7ZygN1FErHDknOKJK6bTBLwvccZ2y7lErTbmsbzykM8LZJ9eTFuFzWTGL3E6CVGLzH6POyzybhdvTKr1RnTyFpUVXxTRx/HIZig9m2S2S9Fe5l07IkaW0naFPbFacsZm5Zp80eGLkn6IaycsGPue9c9azL6dh00brOpz7nr6Y14ZsMeLOmagZuvPFu7TX6My9UrvRloaa7OaFvwue2qLtzx1IZRcfjR3p244+pu3PFkn/aWcnFEOxPUvt0x+DYeWL0tVoZq0QQvHXuixlaSNoWJ27YEU9NsUxvbGZqSpB/CytHN/Pai22ZTn3PX0xtHV5B1/5/U2evQVDH6rDLQbAs+q/p2j8m0W9W320iMjSPamaD25TMb9sTOUC2a4KVjT9TYStKmUHHbkmBqYp/tiQC6JOmHsHKCJkyokzK86NZn6nPUFWTVz2nRVI4+qww024LPFd0zx2TaXdE900iMjSPamaD25ZKuGbEzVIsmeOnYEzW2krQpVNy2JJia2Gd7IoAuSfohrJygCRPqpAwvuvWZ+hx1BVn1c1pIjD4mEqOXGH2cMnTrlxi9xOh1GLdirErSl8Dmyxu3vrQHuw3izuiJs/RyUnuK8CVjOuMnC5tNZvEktSWqPbbbm2b/5TnWxqUYq5JUqLIpsOksE2sj6zas/rhlJWlr1PVVrq2E196ajT1FEIJNs3KzsNkk0zZpFnFUe2y3N83+K/pYc2mqGL1KUqHKpsAWmLkYUV9cG2yWlaStUdcDteVNs7KnCEJwnQ0aWblZ2KzdZxayiKPaY7u9afZf0ceaS1P/oncFmOFKVUuoUq/Tvd+0btP64thgs6wkbQ273n0JSrAr+MXp+yzx2tDi/EIeGQm2JwubdftMx94kdemct11fWmUXYay5SIw+4jqJ0cevS+d6idFLjF5i9PERMbagpO3g4tqT1I4oRxC33Vl8MfnZG7fMJGv3685icmfDdM2anHgP4bDjSWZV2Wir7rVRtgPmzzfpD7yoGUu2xrWIsQXEFWeGhqtgACVq7H1J/copt5QA5rolnwHEandaYlaUvXH7wJtl+WjvTqP9dXXaqmasAmZCtu1JAHGfj2mWrqlw67U9zvNNOgkjKqs4D5G2qcXYouGKM+5rmrdIY0ssUstRl3yO2+6sxGPdJaqjykyyv65OW9dsrc9YBcyEbNuTAGxOFIh7rY7tps836SSMqKziPERa+UWfIaMi5HAVVdR+2RZhX9KkYlGdWOf8ghqp8hgR2LTdaYlZOvbGKbPVEZgB8/11ddq6eH4tY9X7i95EyLY9CSDu8zG5L65wm+T5Jp2E4X1GWYjNOujsMHU/gKsA7PNsJfhRAHcAOBvAhczc6xyfC2AjgE3O7Wu8m5IEITF6idGnbZ+pvXHLlBi9vbbqXisxejtbCV4M4AiABz2O/mwAVQBfB/B5xdHXbSKuQ1EcfZ4zdGzbaFrmd1/qx77DQ5je0V43OLOYHZHHDAs3bb1r5iR0nNCa+xeuDn7Oy/SLM8kyDmk6ft2yijBjKoyoHzS2f2BYE2OZ+TnHgXuPbXQqiWVcEckzi9a2jaZlqku1ugISEC7I2bAnjyxIdWlZ25m5aRAkIJtkFidZallXLLb1LLPM7LZF1GQL2xnGJqQhxs4jonVE9CwR/VbQRUS0lIh6iah3YGAgBTPM0BVITAStvGw0LVNdqlVXkLNhj+026ZSnLiVrOzM3DYIERkDf/iRLLacpzvoRVyDOk6hJB3X2Z7xPsW1HvxvAHGZ+N4DPAVhBRJP8LmTm5czcw8w9nZ2dls0wxxVI4i73qnt/Fjaalqku1aq7F64Ne2y3Sac8dSlZQjGWSw5DbVdrC6Hk/INaV5BNstSyTr/afJZ+ZWXxjiXBtc99m9RJB3X2Z7xPsVbCVFDsnYh+Bk+M3ue+0PMuEqO3b6NpmRKjL2bM14vE6CVGr2I1M1bX0RNRJ4D9zDxCRPMBPA/gXGbeH1Z+UkefdLaDWlZchT7NmTRZzG7wuzftNcmzenFtzvIYD6Q5G0v3PUk628bkR5h6vlHGgDUxlohWArgUwDQi6gdwO4D9AP4JQCeA7xPRema+HMDFAL5IRBUAIwCWRTn5pCTNSFTLMhV7vPekseRuXLuS3Ofem/a+oVllCNrMxBwPpJIx7REfdd6TpBmxJhMl1PNx96otMpExema+nplnMnMrM89m5vuY+XHn73ZmPsVx8mDmx5i5i5nPY+bzmfmptBugiommGYlqWaZij/ceIB1hL64IlXaGX1KyEtdM6im64JcFtvogSHwEot+TOBMB4k6UUM/H3au2yDT8EgiqmGiakaiWZSr2jAowhsJY2nYluc+9N+19Q7MS10zqKbrglwW2+sBPfNR9T+JMBIg7UUI9H3ev2iLTFKtXSoze/n3uvRKjb+x/ssdFYvSNMQZkmWJN0p4lkGX9uuUGKf/u33FexE17Do+ZzZFH20yuSXK9zfLSmkmVRd+b/MhJ6kyL4Hzz+MEVhixTrEHamXwmQm5ay/CG7v/pybBMIpaVCHBlEjfjcuGMjtz2pzXt1zyyc9OqO60y/cr1ipZRYyap4FkEkTyPSRG2aPgYfRLSzuTLsn7dcoMyLJOIZUpiLVb17c6lbSbXJLneho1p1Z1WmX7lekVLIHzMJBU8iyCS5zEpwhbj2tGnncmXZf265arnWlsosVimJNbiiu6ZubTN5Jok19uwMa260yrTr1xXtNQZM0kFzyKI5HlMirCFxOglRi8x+hRslRi9/r0So4+PiLEA7np6I57ZsAdLumbg5ivPjpX+barim8xU8XtJANQtR9DRXsbqrYM4ZdIEfOqSM8bUpS5dAMB3vfJNew7jkRd34JRJE3Dpwul1L6Xuy7t2+wHc++wW7Dt0DB97zxzfPgzrmyjc9ry29zCGKlV87D218t1n5v7tLlvg2qf2X9Bz+fqzW7B14AhOPrENZ57SgY94+mvz3sN44+AxHB8eQVu5hFNPOgGTJ7Zhekc7umZNxoZdB/Ha3sPY//ZxzO9815hnMaaeN9/GvGkn4jKnr6NS4tXzNz28Dj/auBenTZmIP7xobl0Z3mvd59pWLmHKxDa89c7xURsvXTgdfbsO1o2Fw0eHsXrrINrLJZx5SgcmtZexYfchXNE9EwtndODrz27B3kPHQAC27X8Hv37qZExobcFezzN336OpJ7Zh8O3jdc/jiXX96Nt1CMMjVbS2lDC9ox3DVcbbxyo4OjyCSrUW5zuh3AIAGGHGwlM6wMDo2Pzppn1Yv+MAhipVTJnYhkq1iqFKFe2tLZg8oYzjlVrZbeUSLpo/FR0ntOK1vYfx/Vd3ozLCOG/2ZPz+e+bU9QtQCy1N72jH20MV/PgX+zBSZXTPmoTz50zBoy/14+A7w2AwRhhoIWBCuQVtrSV0z5qMLQNHMHB4CABw+skTcXiogikT27D30DEcPDqM+dNOxLzOd2HD7kM4MjQMrgJTJrbhneMVvHV0GCNVBgGYfEIrhquMCeUSpr2rHYeODeOEtjI+8d55ge9TGOPe0d/19Ebc+9zW0c8XL5iG5xyhEAD+5ppzI5doBcwy7dRs0rZyKTCb1C3Du6RpuaWEKjMqI/7PpLWF8LCT9atmBLvnmbkuZk4AWlpoTJmucKaKYu5ndanV267qwm3/9mpd2WofBvWj7q81tT1hEABvi9z+89sfdO32A7hu+eox2/CVS3AEaPN3wPssvG342PLVvn0dtWytV8y8cO7JdWM1qKxSKZ7tQZQIo/H2ID68aBaeWL8r0C4hPn7vUxS6jr5pY/TPbNhT9/nn2+pXYtBZotU0027NVv1sUrcMdUnTsBfXm/W7ZqvP8sIjPEYYZcC3TFc4U0Ux97Nq16q+3b6ia1C74ghWanvCUFsUtj+o+lxcKlX/vtHBLwN7zdbBwL722ug3jtzrhivVMWM1qCybTt4tM4qf/dJ/SXFx8snxe59s0bSOfknXjLrPF849ue6zzhKtppl2i+frZ5O6ZahLmpY996t4s34Xz/dZXriFxgijJcC3TFc4U0WxUYFNseuK7pm+omtQu+IIVmp7wiDl/66do+JyyHNxKZf8+0YHvwzsxfOn+pan2qiOI1XMVMeqtwxvWXFtD6KkUdylZ/kvKd48WxDlh9/7ZIumDd0AEqOXGL3E6CVGLzF6oAkc/fybvw/9f/ALgiAUj0WzJ+OJz/ym8X3jIkYvTl4QhGZgff9BfPhr/ze18hva0YuTFwShWejbdSi1siMdPRHdT0T7iKjPc+yjRLSBiKpE1KNcfwsRbSaiTUR0eRpGuzT0t5QgCIKH7lm+22tbQcdXPgBgiXKsD8DvAXjOe5CIzgFwHYAu5557iKgluZn+bL3rd8XZC4LQ8MSN0esSuXolMz/n7BnrPbYRAIjGTKr6EICHmXkIwOtEtBnAhQBW2zDWjy9dcy6+9L0NeGe4irYWwtQT2/DW0WEQEY4dH0HZObb/nWFUqlWcUG7BjMkT8Dtnn4JDQxWs33EAO/e/g4oziXjhKR3oOKEVV3TPxM9fH8T3X92NkRFGSwk4sb0VJ7a34NjxERw8VsGkCWWc/K527D14FEeOj9S+dJzMEQbQ2lLCebMn48Pvno2vP7sFb7x1FLOnnIC///1FAIAbv70W+44MYUJrC5xcH5Bz35GhEbS1ECa0taC9tQWnTp4AANj/9nHsPXQMh4dq9S2c0YE/vGgunljXjx3738FZp3Rgy8ARDB457rSJcdYpHfiDxXPx+Lp+rN/5FoZHajMAzps9Ge/vmjE6e+P+//c6jg6P4OhQBUeGKpjY1oJ3jo/gXe1lnHxiG04+sTZ7YahSxUXzp+LwUAUvbT+AvYeO4ZRJE3DayRNHZ314Z0UcHqpg3+EhHHznOIYqVd8ZHe51DNTNBHFneTzy4o7RmSLubJk1Wwdx+Ohw3bXqLBa/mSphKfrefQ3cOkyWgijy2uXC+MX25uBfA7CGmb/tfL4PwCpmfjSs/Lizbla8sAN/9firxvflTdGyCMs+mbNFwS8Ts9xCKKGWtOS1etnF8/HA6m2jWb1+2bNhSxt7M3PdOtQsW5UiLEErjF/ymnXjlzfh60GIaCkR9RJR78CAf7ZdFGlmkqVJ0VxqUZ084J+JWRnhMU4eqGVDe7N6g7Jng5bR9WbmunVEZfgWYQlaQYjCtqPvB3Ca5/NsAGMXxgDAzMuZuYeZezo7/bPtokgzkyxNipZFaDvD0iZ+mZjlFkJrC43pxyVdM+qyeoOyZ4OW0fVm5rp1RGX4FmEJWkGIwvYOU08CWEFEXwEwC8ACAD+3XMcobiaZxOibO0Z/4byp2jH693fNiBWjv+D0KVj5p4uNY/QXnD4FD31yscTohUITGaMnopUALgUwDcBeALcD2A/gnwB0AngLwHpmvty5/lYAnwBQAXATM6+KMiLP9egFQRAaFWt7xjLz9QGnHg+4/k4Ad0aVKwiCIGSDTEMXBEFocsTRC4IgNDni6AVBEJoccfSCIAhNjjh6QRCEJqcQG48Q0QCA7ZqXTwPgv3NycWgEGwGx0zZipz0awUYgfztPZ+bIjNNCOHoTiKhXZ95onjSCjYDYaRux0x6NYCPQOHZK6EYQBKHJEUcvCILQ5DSio1+etwEaNIKNgNhpG7HTHo1gI9AgdjZcjF4QBEEwoxF/0QuCIAgGNIyjJ6Ilzobjm4no5pxtOY2IfkpEG51N0v+7c/xkIvp3InrN+f8Uzz2ZbZqu2NpCROuI6HsFtvEkInqUiH7h9OlFBbXzs87z7iOilUQ0oQh2EtH9RLSPiPo8x4ztIqILiOhV59w/ks9eoSnY+WXnub9CRI8T0UlFtNNz7vNExEQ0LW87jWDmwv8HoAXAFgDzAbQBeBnAOTnaMxPA+c7fHQB+CeAcAP8LwM3O8ZsB3O38fY5jczuAeU5bWjKy9XMAVqC2FSQKauP/AfBJ5+82ACcVzU4ApwJ4HcAJzud/BfDHRbATwMUAzgfQ5zlmbBdqe0dchNq2CKsAXJGBnR8AUHb+vruodjrHTwPwA9RyfqblbafJf43yi/5CAJuZeSszHwfwMGobkecCM+9m5pecvw8D2IiaI/gQak4Lzv8/7Pw9umk6M78OwN00PVWIaDaA3wXwTc/hotk4CbUX6z4AYObjzPxW0ex0KAM4gYjKACaitnta7nYy83Oo7RHhxcguIpoJYBIzr+aal3rQc09qdjLzD5m54nxcg9qudIWz0+GrAL6A+l0qc7PThEZx9KcC2On53O8cyx2qbZz+bgAvADiFmXcDtS8DANOdy/Ky/x9QG5hVz7Gi2TgfwACA/+2EmL5JRCcWzU5mfgPA3wHYAWA3gIPM/MOi2enB1K5Tnb/V41nyCdR++QIFs5OIrgbwBjO/rJwqlJ1BNIqj1950PEuI6F0AHkNtJ61DYZf6HEvVfiK6CsA+Zl6re4vPsSz6uIzaP5P/hZnfDeBt1EINQeRipxPj/hBq/zyfBeBEIvqDsFt8juU+ZhFsV672Um1nugqAh9xDAfbk8S5NBHArgNv8TgfYU6jn3yiOXnvT8awgolbUnPxDzPxd5/Be559scP6/zzmeh/3vBXA1EW1DLdT120T07YLZ6Nbbz8wvOJ8fRc3xF83O3wHwOjMPMPMwgO8C+I0C2ulialc/fhU28R5PHSL6OICrANzghDmKZucZqH3Bv+y8T7MBvEREMwpmZyCN4uhfBLCAiOYRURuA61DbiDwXHPX8PgAbmfkrnlNPAvi48/fHAfyb5/h1RNRORPOQ8qbpAMDMtzDzbGaei1p//YSZ/6BINjp27gGwk4gWOofeB+A/i2YnaiGbxUQ00Xn+70NNmymanS5GdjnhncNEtNhp3x957kkNIloC4C8BXM3M7yj2F8JOZn6Vmacz81znfepHbTLGniLZGUpeKrDpfwCuRG12yxYAt+Zsy2+i9s+wVwCsd/67EsBUAD8G8Jrz/5M999zq2L4JGavvqG3u7s66KZyNABYB6HX68wkAUwpq5/8E8AsAfQC+hdpMi9ztBLASNd1gGDUn9Cdx7ALQ47RtC4CvwUmoTNnOzajFuN336N4i2qmc3wZn1k2edpr8J5mxgiAITU6jhG4EQRCEmIijFwRBaHLE0QuCIDQ54ugFQRCaHHH0giAITY44ekFQcJZhOCdvOwTBFjK9UhAEocmRX/TCuIaITiSi7xPRy1RbZ/5jRPQzIuohoquJaL3z3yYiet255wIiepaI1hLRD9ylBgShqIijF8Y7SwDsYubzmLkbwDPuCWZ+kpkXMfMi1NYc/ztnjaN/AnAtM18A4H4Ad+ZhuCDoUs7bAEHImVdRc+B3o7ZMxPPqRkBE9AUAR5n5n4moG0A3gH93rmtBLV1eEAqLOHphXMPMvySiC1Bbq+hvieiH3vNE9D4AH0VtcxSgtvzsBma+KFtLBSE+EroRxjVENAvAO8z8bdQ2Fjnfc+50APcA+H1mPuoc3gSgk4gucq5pJaKujM0WBCPkF70w3jkXwJeJqIraaoWfRs3hA7U9YacCeNwJ0+xi5iuJ6FoA/0hEk1F7h/4BwIasDRcEXWR6pSAIQpMjoRtBEIQmRxy9IAhCkyOOXhAEockRRy8IgtDkiKMXBEFocsTRC4IgNDni6AVBEJoccfSCIAhNzv8HaZMhPiDUaNQAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "non_frag = raw_data[raw_data['size'] <= 1480]\n", "non_frag.plot(x='size', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Déjà bonne nouvelle le MTU ne semble pas être différent car vu la variété de réseaux traversé il serait compliqué de donner une valeur sûre.\n", "\n", "On peut donc essayer de faire une régression :" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
OLS Regression Results
Dep. Variable: time R-squared: 0.000
Model: OLS Adj. R-squared: -0.000
Method: Least Squares F-statistic: 0.05442
Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.816
Time: 17:48:20 Log-Likelihood: -15946.
No. Observations: 5015 AIC: 3.190e+04
Df Residuals: 5013 BIC: 3.191e+04
Df Model: 1
Covariance Type: nonrobust
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
coef std err t P>|t| [0.025 0.975]
const 113.2275 0.165 684.253 0.000 112.903 113.552
size 4.521e-05 0.000 0.233 0.816 -0.000 0.000
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Omnibus: 2447.857 Durbin-Watson: 0.488
Prob(Omnibus): 0.000 Jarque-Bera (JB): 10432.526
Skew: 2.500 Prob(JB): 0.00
Kurtosis: 7.993 Cond. No. 1.72e+03


Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 1.72e+03. This might indicate that there are
strong multicollinearity or other numerical problems." ], "text/plain": [ "\n", "\"\"\"\n", " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: time R-squared: 0.000\n", "Model: OLS Adj. R-squared: -0.000\n", "Method: Least Squares F-statistic: 0.05442\n", "Date: Fri, 12 Jun 2020 Prob (F-statistic): 0.816\n", "Time: 17:48:20 Log-Likelihood: -15946.\n", "No. Observations: 5015 AIC: 3.190e+04\n", "Df Residuals: 5013 BIC: 3.191e+04\n", "Df Model: 1 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "const 113.2275 0.165 684.253 0.000 112.903 113.552\n", "size 4.521e-05 0.000 0.233 0.816 -0.000 0.000\n", "==============================================================================\n", "Omnibus: 2447.857 Durbin-Watson: 0.488\n", "Prob(Omnibus): 0.000 Jarque-Bera (JB): 10432.526\n", "Skew: 2.500 Prob(JB): 0.00\n", "Kurtosis: 7.993 Cond. No. 1.72e+03\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", "[2] The condition number is large, 1.72e+03. This might indicate that there are\n", "strong multicollinearity or other numerical problems.\n", "\"\"\"" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "size_stat = non_frag['size']\n", "size_stat = statsmodels.api.add_constant(size_stat)\n", "model = statsmodels.api.OLS(non_frag['time'], size_stat).fit()\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On regarde l'évolution de la durée en fonction de la taille du paquet (attention, échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "affiche_points_et_regression(non_frag, model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Il y a un problème, les données ne semble pas assez précises car la courbe de régression est trop plate.**\n", "\n", "Au vue du nuage de points il semble que cela soit dû aux valeurs bruités qui sont très nombreuses.\n", "\n", "La mesure ne pourrait toutefois pas être très précise à cause des arrondis fait par la commande `ping`. Dans l'exemple précédent un octet supplémentaire augmentait le temps de transmission en moyenne de 0.0003 ms (coef size visible dans le modèle de régression). Passer de 0 à 1480 octets augmente le délai de moins de 1ms.\n", "\n", "Il faut voir si on ne peut pas retirer les valeurs trop déviantes :" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "med_time = non_frag['time'].median()\n", "decal_permis = 1\n", "data_clean = non_frag[((med_time - decal_permis) <= non_frag['time']) & (non_frag['time'] <= (med_time + decal_permis))]\n", "\n", "size_stat = data_clean['size']\n", "size_stat = statsmodels.api.add_constant(size_stat)\n", "model = statsmodels.api.OLS(data_clean['time'], size_stat).fit()\n", "\n", "affiche_points_et_regression(data_clean, model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On retrouve quelque chose de cohérent :" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def affiche_points_et_regression_data_clean(data_uncleaned, data_cleaned, model):\n", " plt.scatter(data_uncleaned['size'], data_uncleaned['time'], marker=\".\")\n", " plt.plot(data_cleaned['size'], model.predict(), color='black')\n", " plt.yscale('log')\n", " plt.show()\n", "\n", "affiche_points_et_regression_data_clean(non_frag, data_clean, model)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "La latence est de L=0.110821s (soit 110.821ms)\n", "La capacité est de C=4025780 octets/s (soit 4.03 Mo/s ou 32.21 Mbps)\n" ] } ], "source": [ "print_details_connexion(model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cas avec segmentation (size > 1480) \n", "\n", "On sélectionne maintenant les entrées de plus de 1480 octets et affiche l'histogramme de répartition des durées (attention échelle logarithmique) :" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "avec_frag = raw_data[raw_data['size'] > 1480]\n", "avec_frag.plot(x='size', y='time', style='.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Là aussi les données sont bien trop bruités ! On va les nettoyer et faire la régression avec la même méthode que précédemment :" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "med_time = avec_frag['time'].median()\n", "decal_permis = 1\n", "data_clean = avec_frag[((med_time - decal_permis) <= avec_frag['time']) & (avec_frag['time'] <= (med_time + decal_permis))]\n", "\n", "size_stat = data_clean['size']\n", "size_stat = statsmodels.api.add_constant(size_stat)\n", "model = statsmodels.api.OLS(data_clean['time'], size_stat).fit()\n", "\n", "affiche_points_et_regression(data_clean, model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ce qui visualisé avec les autres points donne :" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "affiche_points_et_regression_data_clean(avec_frag, data_clean, model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut estimer les paramètres de la connexion :" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "La latence est de L=0.111333s (soit 111.333ms)\n", "La capacité est de C=2663910 octets/s (soit 2.66 Mo/s ou 21.31 Mbps)\n" ] } ], "source": [ "print_details_connexion(model)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "\n", "Les paramètres de latence et de capacité dans chaque cas sont les suivants :\n", "\n", "| Distance | Segmentation | Latence | Capacité |\n", "|:-:|:-:|:-:|:-:|\n", "| Courte | Non | 3.3 ms| 3.06 Mo/s |\n", "| Courte | Oui | 5.3 ms | 0.39 Mo/s |\n", "| Longue | Non | 110.8 ms | 4.03 Mo/s |\n", "| Longue | Oui | 111.3 ms | 2.66 Mo/s |\n", "\n", "Les valeurs de capacité semble être particulièrement imprécises." ] } ], "metadata": { "celltoolbar": "Aucun(e)", "hide_code_all_hidden": true, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }