Imagine this scenario: You have a router, switch, or wireless gateway that goes into a sort of “sleep mode” after a period of inactivity. When you send the first batch of real data, there’s a small delay because the network is “waking up.” Or your VPN tunnel loses its “steam” over time, and the next connection suffers unnecessary lag.
In this article, we’ll explore a punk-style solution called “dynamic throttle.” The idea is simple:
- Monitor the network state (latency, and optionally other indicators).
- When the network starts slowing down (latency rising, low real traffic), inject a bit of “artificial” traffic: **dummy (empty) packets.
- Once the network picks back up with real traffic, we reduce dummy traffic to minimize overhead.
The goal is to keep the network active* and avoid “sleepy” states in routers, NAT tables, VPN tunnels, and other elements that tend to idle when there’s no data flowing.
Where Can This Help?
Modern Wi-Fi* (e.g., Wi-Fi 6, 6E): These devices can cleverly save power, but occasional traffic might cause extra latency when the radio module reactivates from dozing. Sending a few dummy packets could reduce that wake-up delay.
Mobile and 5G Networks: The same phenomenon can happen — a device may transition to a lower power state (RRC_IDLE) and needs reactivation time. A dynamic throttle might help keep the connection in a more active state if latency starts spiking.
VPN Tunnels (OpenVPN, WireGuard, etc.): If you have prolonged inactivity, the router, NAT, or even the VPN daemon may consider the link dormant. Then the first real packet gets delayed while everything re-initializes.
Edge Computing: Many gateways gather sensor data and send it to the cloud in bursts. A dynamic throttle can maintain the upstream link in a ready state, preventing brief dropouts or delays when establishing a connection.
How It Works: A Simple Outline
- Measure latency (and optionally throughput, packet loss, etc.)
- For example, run a small ping every few seconds to a target (DNS server, cloud endpoint, VPN gateway).
- Decision Logic
- If latency is low, keep dummy traffic to a minimum.
- If latency/jitter increases and there’s little real traffic, crank up dummy packets to “revive” the link.
- Send Dummy Packets
- Usually small UDP packets (50–200 bytes). Send them at some rate (e.g., 2–10 per second), dynamically adjusted according to network conditions.
- Check and Repeat
- Once real traffic flows again, reduce the dummy packets so you’re not wasting bandwidth or power.
- Periodically re-evaluate.
A Functional Python Example (Less Theoretical)
Below is a working (though not production-ready) example of how you can implement a “dynamic throttle” on Linux (or any OS with ping
and socket support). This script:
- Periodically pings (
PING_TARGET
) to measure latency. - Optionally monitors real traffic via
tc
command (Traffic Control) — this is a simplified demonstration of how you might read outgoing traffic on an interface. - Dynamically adjusts the amount of dummy packets (UDP) sent to a given target.
Note: The
tc
part is optional and might require elevated privileges (sudo). If you don’t need it, you can remove that logic.
``python
import subprocess
import re
import socket
import time
import math
-----------------------------
CONFIG
-----------------------------
PING_TARGET = "8.8.8.8" # Where we ping to measure latency
DUMMY_TARGET = ("8.8.8.8", 9999) # Where we send dummy packets
NETWORK_INTERFACE = "eth0" # (Optional) Interface to measure real traffic
PACKET_SIZE = 64 # Size of dummy packets in bytes
PING_INTERVAL = 2.0 # Interval between pings (s)
REGULATION_INTERVAL = 2.0 # Interval for adjusting dummy traffic (s)
LOW_LATENCY_THRESHOLD = 50.0 # (ms)
HIGH_LATENCY_THRESHOLD = 120.0 # (ms)
MAX_DUMMY_PACKETS_PER_SEC = 10 # Max number of dummy packets per second
If ping fails, we assume a default (high) latency
DEFAULT_LATENCY = 999.0
Global variable for the number of dummy packets per second
dummy_packets_per_sec = 0
-----------------------------
FUNCTIONS
-----------------------------
def measure_latency(target: str) -> float:
"""
Measure latency to the target using one ping.
Returns the average RTT in milliseconds (float).
If measurement fails, returns DEFAULT_LATENCY.
"""
try:
output = subprocess.check_output(
["ping", "-c", "1", "-W", "1", target],
stderr=subprocess.STDOUT,
text=True
)
match = re.search(r"rtt min/avg/max/mdev = [\d.]+/([\d.]+)/", output)
if match:
return float(match.group(1))
except subprocess.CalledProcessError:
pass
return DEFAULT_LATENCY
def measure_real_traffic(iface: str) -> float:
"""
(Optional) function to measure outgoing real traffic (in Mb/s).
In reality, you might parse /proc/net/dev, bmon, or ifstat, etc.
Here, we do a simplified example with tc -s qdisc show dev ...
.
NOTE: This requires sudo and is very naive for demonstration.
"""
try:
output = subprocess.check_output(
["tc", "-s", "qdisc", "show", "dev", iface],
stderr=subprocess.STDOUT,
text=True
)
# Super simplified parsing - we look for 'Sent x bytes ...'
match = re.search(r"Sent\s+(\d+)\s+bytes", output)
if match:
sent_bytes = float(match.group(1))
# Real measurement would store the previous value, compare time deltas, etc.
# We'll just return a "fake" value
return sent_bytes / 1e6 # pseudo MB => not exactly Mb/s
except subprocess.CalledProcessError:
pass
return 0.0
def regulation_logic(latency: float, real_traffic_mbps: float) -> int:
"""
Decide how many dummy packets to send:
- If latency < LOW_LATENCY_THRESHOLD, we minimize dummy packets.
If real traffic is flowing, we hardly need any dummy packets.
- If latency > LOW_LATENCY_THRESHOLD and real traffic is low,
we increase dummy packets to "wake the link up."
- Above HIGH_LATENCY_THRESHOLD, we cut dummy packets so we don't make congestion worse.
"""
# Rough heuristic:
# latency < 50 ms => 0 to 2 p/s
# latency 50-120 ms => 2 to 7 p/s, depending on real traffic
# latency > 120 ms => 0 p/s (network is overloaded)
if latency >= HIGH_LATENCY_THRESHOLD:
return 0 # Network is congested, don't add dummy traffic
if latency <= LOW_LATENCY_THRESHOLD:
# Network is OK
if real_traffic_mbps > 0.5:
# Enough real traffic is flowing
return 0
else:
return 2
else:
# Medium latency
if real_traffic_mbps > 0.5:
# Some real load, don't overdo dummy
return 2
else:
# Very little real traffic, but latency is rising => add more dummy
return 5
def send_dummy_packet(sock: socket.socket, size=64):
"""
Send one dummy UDP packet of given size.
"""
data = b"x" * size
sock.sendto(data, DUMMY_TARGET)
-----------------------------
MAIN LOOP
-----------------------------
def main():
global dummy_packets_per_sec
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.setblocking(False)
last_ping_time = time.time()
last_regulation_time = time.time()
last_dummy_send_time = time.time()
interval_between_dummy = 1.0
while True:
now = time.time()
# Ping every PING_INTERVAL seconds
if now - last_ping_time >= PING_INTERVAL:
last_ping_time = now
latency = measure_latency(PING_TARGET)
print(f"[PING] Latency = {latency:.1f} ms")
# Adjust dummy traffic every REGULATION_INTERVAL seconds
if now - last_regulation_time >= REGULATION_INTERVAL:
last_regulation_time = now
real_traffic_mbps = measure_real_traffic(NETWORK_INTERFACE)
current_latency = measure_latency(PING_TARGET)
dummy_packets_per_sec = regulation_logic(current_latency, real_traffic_mbps)
dummy_packets_per_sec = min(dummy_packets_per_sec, MAX_DUMMY_PACKETS_PER_SEC)
if dummy_packets_per_sec > 0:
interval_between_dummy = 1.0 / dummy_packets_per_sec
else:
interval_between_dummy = 9999.0 # effectively off
print(f"[REGULATION] Setting dummy p/s to: {dummy_packets_per_sec}, "
f"real traffic ~ {real_traffic_mbps:.2f} Mb/s")
# Send dummy packets spaced out in time
if dummy_packets_per_sec > 0:
if now - last_dummy_send_time >= interval_between_dummy:
last_dummy_send_time = now
send_dummy_packet(sock, PACKET_SIZE)
time.sleep(0.01)
if name == "main":
main()
``
Implementation Notes
- measure_latency: Classic ping. If it fails, we set the latency to
DEFAULT_LATENCY
. - measure_real_traffic: A demonstration of how you might detect whether real traffic is flowing. In a real implementation, you’d parse byte counters (e.g., from
/proc/net/dev
), track deltas over time, and calculate actual Mbps. - regulation_logic: A simple heuristic. If latency is good, we minimize dummy. If latency goes up and real traffic is low, we add more dummy. Above a high latency threshold, we stop sending dummy to avoid making congestion worse.
- Main Loop:
- Periodically pings at
PING_INTERVAL
. - Periodically recalculates (every
REGULATION_INTERVAL
) and adjusts dummy packets. - Sends dummy packets at the computed interval, so we don’t create big bursts.
- Periodically pings at
Note: This is still a proof-of-concept, but it’s already functional. If you run this on Linux (with
tc
installed), you’ll see it react to latency and (roughly) to real network traffic.
Use cases for modern devices
- Edge AI / IoT Gateways
- Running on a Raspberry Pi or NUC, sending data to the cloud sporadically. A dynamic throttle helps keep your ISP router or local switch from dropping into idle.
- Mobile Hotspots
- If your device is operating as a hotspot with LTE/5G, a dynamic throttle might reduce response time. But beware of extra battery drain.
- VPN (OpenVPN/WireGuard)
- Point
DUMMY_TARGET
to the other end of the tunnel, generating keep-alive traffic that keeps NAT/firewalls from dropping the VPN session.
- Point
- Modern Wi-Fi Mesh
- Small dummy keep-alive packets can help ensure mesh nodes don’t discard routing information during low-traffic periods.
Conclusion
Dynamic throttle is an unconventional (some might say “punk”) technique that uses adaptive dummy packets to keep network traffic slightly active. In modern devices (with various power-saving and QoS features), it may help in scenarios where you dislike “startup delays,” and you’re okay with a slight overhead in bandwidth or power.
Key is dynamism: you only increase dummy traffic when latency is rising and real traffic is idle. Otherwise, you scale dummy down to minimize waste.
In practice, always measure carefully — sometimes it helps; sometimes it’s negligible.
The code above is a real example of how you might start on Linux. You could adapt it, add more refined metrics, or integrate a more sophisticated control algorithm (e.g., PID or eBPF-based solutions).
If you try this, have fun experimenting! Let us know if it actually improves anything in your setup — or if you hit constraints that make it purely theoretical. Even negative results can be valuable, as they push our engineering understanding further.
Tip: Want to take it further? Check out PID controllers or eBPF. You can dynamically respond to latency in even more precise ways in rea
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