How to Implement Custom Flow Control in UDP

Implementing custom flow control in a User Datagram Protocol (UDP) application allows developers to prevent a fast sender from overwhelming a slower receiver’s buffer while retaining the low-latency benefits of UDP. Unlike TCP, which provides built-in reliable delivery and flow control via the transport layer, UDP requires developers to manage transmission rates, packet tracking, and buffer availability directly within the application layer. This guide covers the essential components, protocols, and architectural steps necessary to build a robust custom UDP flow control mechanism.


1. Packet Structure and Header Design

To manage flow at the application layer, you must wrap payloads in custom application-level headers. At a minimum, your custom header must include:


2. The Sliding Window Mechanism

The core of flow control is the sliding window algorithm, which limits the number of unacknowledged packets that can be in flight simultaneously.

Receiver Side

  1. Maintain a fixed-size ring buffer for incoming packets.
  2. Calculate available capacity: \(\text{Available Window} = \text{Total Buffer Size} - \text{Buffered Unread Bytes}\).
  3. Include this dynamic window value in every outgoing ACK packet.
  4. Process packets in sequential order, holding out-of-order packets in the staging buffer until missing packets arrive.

Sender Side

  1. Maintain a pointer for the last packet sent and the last packet acknowledged.
  2. Restrict new transmissions so that: \[\text{Packets in Flight} \le \text{Last Received Advertised Window Size}\]
  3. Stop sending immediately if the advertised window reaches zero (Window Probe state), and periodically send single-byte keep-alive probes until the receiver advertises available space again.

3. Acknowledgment Strategies

Select an acknowledgment strategy based on latency and network overhead requirements:


4. Rate Pacing and Token Buckets

Flow control regulates volume based on receiver capacity, but sending large bursts of packets instantly can still cause packet loss at intermediate network switches. Implement a Token Bucket or Leaky Bucket algorithm to smooth out transmission:

  1. Define a maximum transmission rate (\(R\) packets/sec).
  2. Add tokens to the bucket at a fixed frequency.
  3. Transmit a packet only if a token is available and the sliding window has open capacity.
  4. If tokens are exhausted, queue the packet for the next tick rather than dropping it.

5. RTT Estimation and Dynamic Timeouts

To detect deadlocks or lost window updates without degrading performance, implement dynamic Retransmission Timeouts (RTO):

  1. Compute Smoothed Round Trip Time (SRTT) using an Exponentially Weighted Moving Average (EWMA): \[\text{SRTT} = (1 - \alpha) \cdot \text{SRTT} + \alpha \cdot \text{SampleRTT}\] (Typically, \(\alpha = 0.125\))
  2. Track RTT variation (RTTVAR): \[\text{RTTVAR} = (1 - \beta) \cdot \text{RTTVAR} + \beta \cdot |\text{SRTT} - \text{SampleRTT}|\] (Typically, \(\beta = 0.25\))
  3. Calculate the RTO: \[\text{RTO} = \text{SRTT} + \max(G, 4 \cdot \text{RTTVAR})\] (Where \(G\) is the clock granularity)

If an ACK is not received within the computed RTO, back off transmission, reduce the flight size, and resend the unacknowledged data.


6. Architectural Checklist for Implementation