add bulk_run_cover

mixnet/v2/sim/bulk_run_cover.py

@@ -0,0 +1,82 @@
+import argparse
+from datetime import datetime
+
+import pandas as pd
+from matplotlib import pyplot as plt
+
+from config import P2PConfig, Config
+from simulation import Simulation
+
+
+def bulk_run_cover():
+    parser = argparse.ArgumentParser(description="Run simulation",
+                                     formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+    parser.add_argument("--config", type=str, required=True, help="Configuration file path")
+    args = parser.parse_args()
+    config = Config.load(args.config)
+
+    results = []
+
+    config.simulation.running_time = 30
+    config.mixnet.num_nodes = 1000
+    config.mixnet.num_mix_layers = 4
+    config.mixnet.payload_size = 320
+    config.mixnet.message_interval = 1
+    config.mixnet.real_message_prob = 0.01
+    config.mixnet.real_message_prob_weights = []
+    config.mixnet.max_message_prep_time = 0
+    config.mixnet.max_mix_delay = 0
+    config.p2p.type = P2PConfig.TYPE_GOSSIP
+    config.p2p.connection_density = 6
+    config.p2p.max_network_latency = 0.20
+    config.measurement.sim_time_per_second = 1
+
+    base = config.mixnet.real_message_prob * 2
+    for cover_message_prob in [base, base * 2, base * 3, base * 4, base * 5]:
+        config.mixnet.cover_message_prob = cover_message_prob
+
+        sim = Simulation(config)
+        sim.run()
+
+        egress, ingress = sim.p2p.measurement.bandwidth()
+        results.append({
+            "num_nodes": config.mixnet.num_nodes,
+            "num_mix_layers": config.mixnet.num_mix_layers,
+            "p2p_type": config.p2p.type,
+            "real_message_prob": config.mixnet.real_message_prob,
+            "cover_message_prob": cover_message_prob,
+            "egress_mean": egress.mean(),
+            "egress_max": egress.max(),
+            "ingress_mean": ingress.mean(),
+            "ingress_max": ingress.max(),
+        })
+
+    df = pd.DataFrame(results)
+    df.to_csv(f"{datetime.now().replace(microsecond=0).isoformat()}.csv", index=False)
+    draw_plot(df)
+
+
+def load_and_plot():
+    # with skipping the header
+    df = pd.read_csv("2024-05-27T14:14:58.csv")
+    print(df)
+    draw_plot(df)
+
+
+def draw_plot(df: pd.DataFrame):
+    plt.plot(df["cover_message_prob"], df["egress_mean"], label="Egress Mean", marker="o")
+    plt.plot(df["cover_message_prob"], df["egress_max"], label="Egress Max", marker="x")
+    plt.plot(df["cover_message_prob"], df["ingress_mean"], label="Ingress Mean", marker="v")
+    plt.plot(df["cover_message_prob"], df["ingress_max"], label="Ingress Max", marker="^")
+
+    plt.xlabel("Cover Emission Rate")
+    plt.ylabel("Bandwidth (KiB/s)")
+    plt.title("Bandwidth vs Cover Emission Rate")
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+
+
+if __name__ == "__main__":
+    bulk_run_cover()
+    # load_and_plot()