Add more fine-grained traffic control

.gitignore

@@ -2,3 +2,4 @@ files
 Band_data
 id_*
 logs
+__pycache__/

datasets5G.py

@@ -0,0 +1,85 @@
+datasets5G = [
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.01_12.11.21.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.01_13.05.00.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.02_07.26.15.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.02_09.39.35.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.02_12.41.17.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.03_07.29.22.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.03_10.42.14.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.03_13.58.03.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.04_07.26.30.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.04_11.58.01.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.04_14.24.21.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.06_07.31.16.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.06_09.32.38.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/Season3-TheExpanse/B_2019.12.06_11.49.24.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.28_07.27.57.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.28_10.14.25.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.28_12.05.29.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.28_14.53.29.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.28_17.18.56.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.29_09.37.23.csv",
+    "5G-production-dataset/Amazon_Prime/Driving/animated-AdventureTime/B_2019.11.29_13.05.25.csv",
+    "5G-production-dataset/Amazon_Prime/Static/Season3-TheExpanse/B_2019.12.19_15.00.47.csv",
+    "5G-production-dataset/Amazon_Prime/Static/Season3-TheExpanse/B_2019.12.23_10.30.35.csv",
+    "5G-production-dataset/Amazon_Prime/Static/Season3-TheExpanse/B_2020.01.03_08.59.40.csv",
+    "5G-production-dataset/Amazon_Prime/Static/Season3-TheExpanse/B_2020.01.03_10.54.39.csv",
+    "5G-production-dataset/Amazon_Prime/Static/Season3-TheExpanse/B_2020.01.05_14.55.57.csv",
+    "5G-production-dataset/Amazon_Prime/Static/animated-Ninjago/B_2020.01.06_09.55.13.csv",
+    "5G-production-dataset/Amazon_Prime/Static/animated-Ninjago/B_2020.01.06_11.08.12.csv",
+    "5G-production-dataset/Amazon_Prime/Static/animated-Ninjago/B_2020.01.06_11.40.29.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.14_10.16.30.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.16_07.22.43.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.16_11.49.59.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.16_12.27.05.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.16_14.23.32.csv",
+    "5G-production-dataset/Download/Driving/B_2019.12.17_07.32.39.csv",
+    "5G-production-dataset/Download/Driving/B_2020.01.16_07.26.43.csv",
+    "5G-production-dataset/Download/Driving/B_2020.01.16_09.56.56.csv",
+    "5G-production-dataset/Download/Driving/B_2020.01.16_12.10.03.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.13_13.03.24.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.13_15.02.01.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.14_07.29.00.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.14_09.38.22.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.14_12.58.17.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.27_17.30.15.csv",
+    "5G-production-dataset/Download/Driving/B_2020.02.27_20.35.57.csv",
+    "5G-production-dataset/Download/Static/B_2019.12.16_13.40.04.csv",
+    "5G-production-dataset/Download/Static/B_2020.01.16_10.43.34.csv",
+    "5G-production-dataset/Download/Static/B_2020.02.13_13.57.29.csv",
+    "5G-production-dataset/Download/Static/B_2020.02.14_13.21.26.csv",
+    "5G-production-dataset/Download/Static/B_2020.02.27_18.39.27.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.23_12.27.34.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.23_13.28.26.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.23_16.08.19.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.24_12.19.13.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.24_13.06.36.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.25_07.25.43.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.25_15.34.34.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.26_07.29.24.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.26_09.53.40.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.26_13.00.56.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.26_13.20.42.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.26_15.02.50.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.27_07.29.47.csv",
+    "5G-production-dataset/Netflix/Driving/Season3-StrangerThings/B_2019.11.27_16.33.16.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.20_16.55.16.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_07.59.06.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_09.03.55.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_09.44.52.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_10.20.17.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_14.33.25.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_15.38.35.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.21_16.15.17.csv",
+    "5G-production-dataset/Netflix/Driving/animated-RickandMorty/B_2019.11.22_07.30.04.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.11.26_13.50.48.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.11.28_09.21.45.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.12.03_08.02.05.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.12.04_12.46.14.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.12.06_09.55.13.csv",
+    "5G-production-dataset/Netflix/Static/Season3-StrangerThings/B_2019.12.16_13.03.47.csv",
+    "5G-production-dataset/Netflix/Static/animated-RickandMorty/B_2019.11.23_14.30.10.csv",
+    "5G-production-dataset/Netflix/Static/animated-RickandMorty/B_2019.11.26_08.02.38.csv",
+    "5G-production-dataset/Netflix/Static/animated-RickandMorty/B_2019.11.26_09.27.10.csv",
+    "5G-production-dataset/Netflix/Static/animated-RickandMorty/B_2019.11.28_08.02.19.csv",
+]

lab.py

@@ -3,31 +3,21 @@
 import pathlib
 from collections import OrderedDict
 from multiprocessing import Process
+from time import sleep
 from typing import List, Literal, TypedDict, Union
 
 from mininet.clean import cleanup
 from mininet.log import info, setLogLevel
 from mininet.net import Mininet
 from mininet.node import Host, Switch
 
-MobilityType = Union[
-    Literal["Driving-1"],
-    Literal["Driving-10"],
-    Literal["Driving-2"],
-    Literal["Driving-6"],
-    Literal["Driving-7"],
-    Literal["Driving-8"],
-    Literal["Driving-9"],
-    Literal["Static-1"],
-    Literal["Static-2"],
-    Literal["Static-3"],
-]
+from normalize_datasets import NormalizedDataset, get_normalized_datasets
 
 
 class Experiment(TypedDict):
     id: int
     mode: Literal["5g"]
-    mobility: MobilityType
+    mobility: NormalizedDataset
     clients: int
     server_type: Union[Literal["asgi"], Literal["wsgi"]]
     adaptation_algorithm: Union[
@@ -136,7 +126,7 @@ def print_experiment(experiment: Experiment):
     print(f"Network Trace Type : {experiment['server_type']}\n")
 
     print("-------------------------------")
-    print(f"Network Trace Mobility : {experiment['mobility']}\n")
+    print(f"Network Trace Mobility : {experiment['mobility']['name']}\n")
 
     print("-------------------------------")
     print(f"Number of clients: {experiment['clients']}\n")
@@ -151,7 +141,7 @@ def print_experiment(experiment: Experiment):
 def get_experiment_folder_name(experiment: Experiment) -> str:
     experiment_folder = (
         f"id_{experiment['id']}_mode_{experiment['mode']}_trace_"
-        + f"{experiment['mobility']}_host_{experiment['clients']}_algo_"
+        + f"{experiment['mobility']['name']}_host_{experiment['clients']}_algo_"
         + f"{experiment['adaptation_algorithm']}_protocol_"
         + f"{experiment['server_protocol']}_server_{experiment['server_type']}"
     )
@@ -212,17 +202,47 @@ def pcap(experiment: Experiment):
 
 
 def tc(experiment: Experiment, client: Host):
-    proc = client.popen(
-        f"./topo.sh {client.intf()} {experiment['mobility']}",
-        shell=True,
-        stdout=None,
-        stderr=None,
+    intf = client.intf()
+    initial_download_speed = experiment["mobility"]["data"][0].download_kbps
+    initial_upload_speed = experiment["mobility"]["data"][0].upload_kbps
+    initial_interval = experiment["mobility"]["data"][0].change_interval_seconds
+
+    filter_command_base = "tc filter add dev {intf} protocol ip parent 1: prio 1 u32"
+
+    # create root interface
+    client.cmd(f"tc qdisc add dev {intf} root handle 1: htb default 30")
+
+    # create initial download class
+    client.cmd(
+        f"tc class add dev {intf} parent 1:1 classid 1:10 htb rate {initial_download_speed}kbps burst 15k"
     )
+    # create initial upload class
+    client.cmd(
+        f"tc class add dev {intf} parent 1:1 classid 1:20 htb rate {initial_upload_speed}kbps burst 15k"
+    )
+
+    # add filters for download and upload traffic to redirect to proper classes
+    client.cmd(f"{filter_command_base} match ip dst 0.0.0.0/0 flowid 1:10")
+    client.cmd(f"{filter_command_base} match ip src 0.0.0.0/0 flowid 1:20")
 
-    try:
-        proc.communicate()
-    finally:
-        proc.kill()
+    # sleep before changing values
+    sleep(initial_interval)
+
+    for current_data in experiment["mobility"]["data"][1:]:
+        curr_download_speed = current_data.download_kbps
+        curr_upload_speed = current_data.upload_kbps
+        curr_interval = current_data.change_interval_seconds
+
+        # change download class rate
+        client.cmd(
+            f"tc class change dev {intf} parent 1:1 classid 1:10 htb rate {curr_download_speed}kbps burst 15k"
+        )
+        # change upload class rate
+        client.cmd(
+            f"tc class change dev {intf} parent 1:1 classid 1:20 htb rate {curr_upload_speed}kbps burst 15k"
+        )
+        # sleep before changing rate again
+        sleep(curr_interval)
 
 
 def player(experiment: Experiment, client: Host):
@@ -238,8 +258,10 @@ def player(experiment: Experiment, client: Host):
 if __name__ == "__main__":
     setLogLevel("info")
 
+    normalized_datasets = get_normalized_datasets()
+
     experiment: Experiment = {
-        "mobility": "Driving-8",
+        "mobility": normalized_datasets[0],
         "server_type": "wsgi",
         "server_protocol": "tcp",
         "clients": 1,

normalize_datasets.py

@@ -0,0 +1,79 @@
+import pathlib
+from dataclasses import dataclass
+from typing import List, TypedDict
+
+import pandas as pd
+from pandas.core.frame import DataFrame
+
+from datasets5G import datasets5G
+
+
+@dataclass
+class Limits:
+    upload_kbps: float
+    download_kbps: float
+    change_interval_seconds: int
+
+
+class NormalizedDataset(TypedDict):
+    name: str
+    data: List[Limits]
+    total_duration: int
+    platform: str
+    mobility: str
+    case: str
+    dataset: str
+
+
+def get_normalized_datasets() -> List[NormalizedDataset]:
+    normalized_datasets = []
+
+    for filename in datasets5G:
+        # Normalize dataset using pandas
+        csv_data: DataFrame = pd.read_csv(filename)  # type: ignore
+
+        filtered_data: DataFrame = csv_data[["Timestamp", "DL_bitrate", "UL_bitrate"]]
+        filtered_data = filtered_data.groupby("Timestamp").mean().reset_index()
+
+        filtered_data["Timestamp"] = pd.to_datetime(
+            filtered_data["Timestamp"], format="%Y.%m.%d_%H.%M.%S"
+        )
+        filtered_data["Timestamp"] = (
+            ((filtered_data["Timestamp"] - filtered_data["Timestamp"].shift()))
+            .shift(-1)
+            .fillna(pd.Timedelta(seconds=1))
+            .dt.seconds
+        )
+
+        total_duration = filtered_data["Timestamp"].sum()
+
+        filtered_data.rename(
+            columns={
+                "Timestamp": "change_interval_seconds",
+                "DL_bitrate": "download_kbps",
+                "UL_bitrate": "upload_kbps",
+            },
+            inplace=True,
+        )
+
+        # Normalize name removing first path
+        parts = pathlib.Path(filename).parts
+        normalized_name = "-".join(parts[1:]).strip(".csv")
+        platform = parts[1]
+        mobility = parts[2]
+        case = parts[3] if len(parts) > 4 else parts[1]
+        dataset = parts[4] if len(parts) > 4 else parts[3]
+
+        normalized_datasets.append(
+            {
+                "name": normalized_name,
+                "data": filtered_data.to_dict("records"),
+                "total_duration": total_duration,
+                "platform": platform,
+                "mobility": mobility,
+                "case": case,
+                "dataset": dataset,
+            }
+        )
+
+    return normalized_datasets