Latency distribution plot for paper

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alrevuelta 2024-02-15 15:08:14 +01:00
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commit ff5c9c885c
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7 changed files with 44185 additions and 4 deletions

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@ -0,0 +1,41 @@
import matplotlib.pyplot as plt
import scienceplots
import numpy as np
import pandas as pd
from analyze import load
latencies = pd.DataFrame({
"2kb": load("raw/paper_latency_2kb_v2.txt", "arrival_diff="),
"25kb": load("raw/paper_latency_25kb_v2.txt", "arrival_diff="),
"100kb": load("raw/paper_latency_100kb_v2.txt", "arrival_diff="),
"500kb": load("raw/paper_latency_500kb_v2.txt", "arrival_diff=")})
num_bins = 50
#fig, ax = plt.subplots(2, 2)
with plt.style.context(['science', 'ieee']):
fig, ax = plt.subplots(2, 2)
possitions = [
("2kb", ax[0][0]),
("25kb", ax[0][1]),
("100kb", ax[1][0]),
("500kb", ax[1][1])
]
for (size, pos) in possitions:
latencies.hist(size, bins=num_bins, ax=pos)
pos.grid(False)
text = r'$ \mu=$' + '{:.0f};'.format(latencies[size].mean(axis=0)) + r' $ p_{95}=$' + '{:.0f};'.format(
np.percentile(latencies[size], 95)) + ' max={:.0f}'.format(latencies[size].max())
pos.set_title(f"msgsize={size}; " + text, fontsize=6)
ax[0][0].set(ylabel='Amount samples')
ax[1][0].set(xlabel='Latency (ms)', ylabel='Amount samples')
ax[1][1].set(xlabel='Latency (ms)')
fig.set_size_inches(4, 3)
fig.savefig('paper_distribution.svg', dpi=600)

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@ -14,13 +14,13 @@ network:
graph [
node [
id 0
host_bandwidth_up "38 Mbit"
host_bandwidth_down "83 Mbit"
host_bandwidth_up "100 Mbit"
host_bandwidth_down "100 Mbit"
]
edge [
source 0
target 0
latency "100 ms"
latency "150 ms"
packet_loss 0.0
]
]
@ -39,8 +39,9 @@ hosts:
--rln-relay-dynamic=false
--rln-relay-membership-index=0
--nat=extip:0.0.0.0
--max-msg-size=600KB
start_time: 5s
environment: {"PEERS": "1000", "CONNECTTO": "50", "NUMPUBLISHERS": "1", "MSGSIZEKBYTES": "10"}
environment: {"PEERS": "1000", "CONNECTTO": "25", "NUMPUBLISHERS": "1", "MSGSIZEKBYTES": "10"}
peer2: *client_host
peer3: *client_host
peer4: *client_host