15.4. Large Data Rates

When the amount of data exchanged between a Publisher and a Subscriber is large, some extra configuration may be required to compensate for side effects on the network and CPU load. This large amount of data can be a result of the data types being large, a high message rate, or a combination of both.

In this scenario, several approaches can be considered depending on the problem:

  • For the cases in which the data samples are large (in the order of MB) such as transmitting raw video frames, point clouds, images, etc. between different hosts, TCP based communications may yield better reception rates with lower message loss, specially in the cases where a best effort transport layer is more susceptible to data loss, such as WiFi. To tackle these cases, Large Data mode and Fast DDS over TCP documents several ways to configure Fast DDS to communicate over TCP.

  • Network packages could be dropped because the transmitted amount of data fills the socket buffer before it can be processed. The solution is to increase the buffers size.

  • It is also possible to limit the rate at which the Publisher sends data using Flow Controllers, in order to limit the effect of message bursts, and avoid to flood the Subscribers faster than they can process the messages.

  • On RELIABLE_RELIABILITY_QOS mode, the overall message rate can be affected due to the retransmission of lost packets. Selecting the Heartbeat period allows to tune between increased meta traffic or faster response to lost packets. See Tuning Heartbeat Period.

  • Also on RELIABLE_RELIABILITY_QOS mode, with high message rates, the history of the DataWriter can be filled up, blocking the publication of new messages. A non-strict reliable mode can be configured to avoid this blocking, at the cost of potentially losing some messages on some of the Subscribers.


eProsima Fast DDS defines a conservative default message size of 64kB, which roughly corresponds to TCP and UDP payload sizes. If the topic data is bigger, it will automatically be fragmented into several transport packets.


The loss of a fragment means the loss of the entire message. This has the most impact on BEST_EFFORT_RELIABILITY_QOS mode, where the message loss probability increases with the number of fragments

15.4.1. Increasing socket buffers size

In high rate scenarios or large data scenarios, network packages can be dropped because the transmitted amount of data fills the socket buffer before it can be processed. Using RELIABLE_RELIABILITY_QOS mode, Fast DDS will try to recover lost samples, but with the penalty of retransmission. With BEST_EFFORT_RELIABILITY_QOS mode, samples will be definitely lost.

By default eProsima Fast DDS creates socket buffers with the system default size. However, these sizes can be modified using the DomainParticipantQos, as shown in the example below.


DomainParticipantQos participant_qos;

// Increase the sending buffer size
participant_qos.transport().send_socket_buffer_size = 1048576;

// Increase the receiving buffer size
participant_qos.transport().listen_socket_buffer_size = 4194304;


<?xml version="1.0" encoding="UTF-8" ?>
<profiles xmlns="http://www.eprosima.com/XMLSchemas/fastRTPS_Profiles">
    <participant profile_name="participant_xml_profile_qos_socketbuffers">
</profiles> Finding out system maximum values

Operating systems set a maximum value for socket buffer sizes. If the buffer sizes are tuned with DomainParticipantQos, the values set cannot exceed the maximum value of the system. Linux

The maximum buffer size values can be retrieved with the command sysctl. For socket buffers used to send data, use the following command:

$> sudo sysctl -a | grep net.core.wmem_max
net.core.wmem_max = 1048576

For socket buffers used to receive data the command is:

$> sudo sysctl -a | grep net.core.rmem_max
net.core.rmem_max = 4194304

However, these maximum values are also configurable and can be increased if needed. The following command increases the maximum buffer size of sending sockets:

$> sudo sysctl -w net.core.wmem_max=12582912

For receiving sockets, the command is:

$> sudo sysctl -w net.core.rmem_max=12582912 Windows

The following command changes the maximum buffer size of sending sockets:

C:\> reg add HKLM\SYSTEM\CurrentControlSet\services\AFD\Parameters /v DefaultSendWindow /t REG_DWORD /d 12582912

For receiving sockets, the command is:

C:\> reg add HKLM\SYSTEM\CurrentControlSet\services\AFD\Parameters /v DefaultReceiveWindow /t REG_DWORD /d 12582912

15.4.2. Increasing the Transmit Queue Length of an interface (Linux only)

The Transmit Queue Length (txqueuelen) is a TCP/UDP/IP stack network interface value. This value sets the number of packets allowed per kernel transmit queue of a network interface device. By default, the txqueuelen value for Ethernet interfaces is set to 1000 in Linux. This value is adequate for most Gigabit network devices. However, in some specific cases, the txqueuelen setting should be increased to avoid overflows that drop packets. Similarly, choosing a value that is too large can cause added overhead resulting in higher network latencies.

Note that this information only applies to the sending side, and not the receiving side. Also increasing the txqueuelen should go together with increasing the buffer sizes of the UDP and/or TCP buffers. (this must be applied for both the sending and receiving sides).

The settings for a specific network adapter can be viewed using the one of the following commands:

ip link show ${interface}

This will display the configuration of the adapter, and among the parameters the txqueuelen. This parameter can be a value between 1000 and 20000.


If the ip command is used, the Transmit Queue Length parameter is called qlen.

The txqueuelen can be modified for the current session using either the ifconfig or ip commands. However, take into account that after rebooting the default values will be configured again.

ip link set txqueuelen ${value} dev ${interface}

15.4.3. Flow Controllers

eProsima Fast DDS provides a mechanism to limit the rate at which the data is sent by a DataWriter. These controllers should be registered on the creation of the DomainParticipant using FlowControllersQos, and then referenced on the creation of the DataWriter using PublishModeQosPolicy.

A new thread is spawned the first time a flow controller is referenced by an asynchronous DataWriter. This thread will be responsible for arbitrating the network output of the samples being transmitted by all the DataWriters referencing the same flow controller.

Flow controllers should be given a name so they can later on be referenced by the DataWriters. A default, unlimited, FIFO flow controller is always available with name FASTDDS_FLOW_CONTROLLER_DEFAULT. Scheduling policy

There are different kinds of flow controllers, depending on the scheduling policy used. All of them will limit the number of bytes sent to the network to no more than max_bytes_per_period bytes during period_ms milliseconds. They only differ in the way they decide the order in which the samples are sent.

  • FIFO will output samples on a first come, first served order.

  • ROUND_ROBIN will output one sample from each DataWriter in circular order.

  • HIGH_PRIORITY will output samples from DataWriters with the highest priority first. The priority of a DataWriter is configured using property fastdds.sfc.priority. Allowed values are from -10 (highest priority) to 10 (lowest priority). If the property is not present, it will be set to the lowest priority. Samples for DataWriters with the same priority are handled with FIFO order.

  • PRIORITY_WITH_RESERVATION works as the previous one, but allows the DataWriters to reserve part of the output bandwidth. This is done with the property fastdds.sfc.bandwidth_reservation. Allowed values are from 0 to 100, and express a percentage of the total flow controller limit. If the property is not present, it will be set to 0 (no bandwidth is reserved for the DataWriter). After the reserved bandwidth has been consumed, the rest of the samples will be handled with the rules of HIGH_PRIORITY. Example configuration

// Limit to 300kb per second.
static const char* flow_controller_name = "example_flow_controller";
auto flow_control_300k_per_sec = std::make_shared<eprosima::fastdds::rtps::FlowControllerDescriptor>();
flow_control_300k_per_sec->name = flow_controller_name;
flow_control_300k_per_sec->scheduler = eprosima::fastdds::rtps::FlowControllerSchedulerPolicy::FIFO;
flow_control_300k_per_sec->max_bytes_per_period = 300 * 1000;
flow_control_300k_per_sec->period_ms = 1000;

// [OPTIONAL] Configure sender thread settings
flow_control_300k_per_sec->sender_thread = eprosima::fastdds::rtps::ThreadSettings{-1, 0, 0, -1};

// Register flow controller on participant
DomainParticipantQos participant_qos;

// .... create participant and publisher

// Link writer to the registered flow controller.
// Note that ASYNCHRONOUS_PUBLISH_MODE must be used
DataWriterQos qos;
qos.publish_mode().kind = ASYNCHRONOUS_PUBLISH_MODE;
qos.publish_mode().flow_controller_name = flow_controller_name;


Specifying a flow controller with a size smaller than the transport buffer size can cause the messages to never be sent.

15.4.4. Tuning Heartbeat Period

On RELIABLE_RELIABILITY_QOS (ReliabilityQosPolicy), RTPS protocol can detect which messages have been lost and retransmit them. This mechanism is based on meta-traffic information exchanged between DataWriters and DataReaders, namely, Heartbeat and Ack/Nack messages.

A smaller Heartbeat period increases the CPU and network overhead, but speeds up the system response when a piece of data is lost. Therefore, users can customize the Heartbeat period to match their needs. This can be done with the DataWriterQos.

DataWriterQos qos;
qos.reliable_writer_qos().times.heartbeatPeriod.seconds = 0;
qos.reliable_writer_qos().times.heartbeatPeriod.nanosec = 500000000; //500 ms

15.4.5. Using Non-strict Reliability

When HistoryQosPolicyKind is set as KEEP_ALL_HISTORY_QOS, all samples have to be received (and acknowledged) by all subscribers before they can be overridden by the DataWriter. If the message rate is high and the network is not reliable (i.e., lots of packets get lost), the history of the DataWriter can be filled up, blocking the publication of new messages until any of the old messages is acknowledged by all subscribers.

If this strictness is not needed, HistoryQosPolicyKind can be set as KEEP_LAST_HISTORY_QOS. In this case, when the history of the DataWriter is full, the oldest message that has not been fully acknowledged yet is overridden with the new one. If any subscriber did not receive the discarded message, the publisher will send a GAP message to inform the subscriber that the message is lost forever.

15.4.6. Practical Examples Example: Sending a large file

Consider the following scenario:

  • A Publisher needs to send a file with a size of 9.9 MB.

  • The Publisher and Subscriber are connected through a network with a bandwidth of 100 MB/s

With a fragment size of 64 kB, the Publisher has to send about 1100 fragments to send the whole file. A possible configuration for this scenario could be:

  • Using RELIABLE_RELIABILITY_QOS, since a losing a single fragment would mean the loss of the complete file.

  • Decreasing the heartbeat period, in order to increase the reactivity of the Publisher.

  • Limiting the data rate using a Flow Controller, to avoid this transmission cannibalizing the whole bandwidth. A reasonable rate for this application could be 5 MB/s, which represents only 5% of the total bandwidth.


Using Shared Memory Transport the only limit to the fragment size is the available memory. Therefore, all fragmentation can be avoided in SHM by increasing the size of the shared buffers. Example: Video streaming

In this scenario, the application transmits a video stream between a Publisher and a Subscriber, at 50 fps. In real-time audio or video transmissions, it is usually preferred to have a high stable datarate feed, even at the cost of losing some samples. Losing one or two samples per second at 50 fps is more acceptable than freezing the video waiting for the retransmission of lost samples. Therefore, in this case BEST_EFFORT_RELIABILITY_QOS can be appropriate.