jhelovuo / RustDDS

Rust implementation of Data Distribution Service
Apache License 2.0
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RustDDS

continuous-integration codecov

RustDDS is a pure Rust implementation of Data Distribution Service. The latest released version is available on crates.io and API documentation on docs.rs. The GitHub repository tracks development.

RustDDS is developed by Atostek Oy. Atostek provides support and software development services related to DDS, ROS2, and robotics software in general. As a part of our work, we have open-sourced the RustDDS implementation.

We have tried to translate the key ideas of the DDS application interface to Rust concepts, but also follow Rust conventions. Consequently, the API is not exactly as written in the DDS specification, but a functionally equivalent approximation using Rust concepts and conventions.

Data Distribution Service

The Data Distribution Service for real-time systems (DDS) is an Object Management Group (OMG) machine-to-machine connectivity framework that aims to enable scalable, real-time, dependable, high-performance and interoperable data exchanges using a publish–subscribe pattern. DDS addresses the needs of applications like air-traffic control, smart grid management, autonomous vehicles, robotics, transportation systems, power generation, medical devices, simulation and testing, aerospace and defense, and other applications that require real-time data exchange [Wiki].

Current implementation status

Currently, the implementation is complete enough to do data exchange with ROS2 software.

The ros2-client is recommended for talking to ROS components. The ros2 module within RustDDS should not be used anymore.

Version 0.10.0

The DeserializerAdpter interface for attaching serialization formats to RTPS was extended to support deserialization with a "seed" value. This allows the deserialization process to input other run-time data besides the incoming byte stream.

0.10.1

0.10.2

0.10.3

Version 0.9.2

Version 0.9.1

Version 0.9

Version 0.8.6

Version 0.8.5

Version 0.8

New features:

This release breaks compatibility:

Version 0.6

This release breaks compatibility with 0.5.x. There are some minor differences in public API names. Changes were made to follow Rust naming conventions. Version 0.6.0 fixes a regression, where communication with eProsima FastRTPS was only possible for a short time.

Version 0.5

This release breaks compatibility with 0.4.0. Differences are

Features Status

Interoperability

Using "Shapes" demo programs available. Data exchange worked in both directions:

Usage

Please see the examples included within the crate and also Interoperability test .

Data serialization and keying

Some existing DDS implementations use code generation to implement DataReader and DataWriter classes for each payload type.

We do not rely on code generation, but Rust generic programming instead: There is a generic DataReader and DataWriter, parameterized with the payload type D and a serializer adapter type SA. The Serde library is used for payload data serialization/deserialization.

The payload type D is required to implement serde::Serialize when used with a DataWriter, and serde::DeserializeOwned when used with a DataReader. Many existing Rust types and libraries already support Serde, so they are good to go as-is.

In DDS, a WITH_KEY topic contains multiple different instances, that are distinguished by a key. The key must be somehow embedded into the data samples. In our implementation, if the payload type D is communicated in a WITH_KEY topic, then D is additionally required to implement trait Keyed.

The trait Keyed requires one method: key(&self) -> Self::K , which is used to extract a key of an associated type K from D. They key type K must implement trait Key, which is a combination of pre-existing traits Eq + PartialEq + PartialOrd + Ord + Hash + Clone + Serialize + DeserializeOwned and no additional methods.

A serializer adapter type SA (wrapper for a Serde data format) is provided for OMG Common Data Representation (CDR), as this is the default serialization format used by DDS/RTPS. It is possible to use another serialization format for the objects communicated over DDS by providing a Serde data format implementation.

Intentional deviations from DDS specification

Rationale

The DDS 1.4 specification specifies an object model and a set of APIs for those objects that constitute the DDS specification. The design of these APIs in, e.g., naming conventions and memory management semantics, does not quite fit the Rust world. We have tried to create a design where important DDS ideas are preserved and implemented, but in a manner suitable to Rust. These design compromises should be apparent only on the application-facing API of DDS. The network side is still aiming to be fully interoperable with existing DDS implementations.

Class Hierarchy

The DDS specifies a class hierarchy, which is part of the API. That hierarchy is not necessarily followed, because Rust does not use inheritance and derived classes in the same sense as e.g. C++.

Naming Conventions

We have tried to follow Rust naming conventions.

Data listeners and WaitSets

DDS provides two alternative methods for waiting arriving data, namely WaitSets and Listeners. We have chosen to replace these by using the non-blocking IO API from mio crate. The DDS DataReader objects can be directly used with the mio Poll interface. It should be possible to implement other APIs, such as an async API on top of that.

Instance Handles

DDS uses "instance handles", which behave like pointers to objects managed by the DDS implementation. This does not seem to mix well with Rust memory handling, so we have chosen to not implement those.

An instance handle can be used to refer to refer to data values (samples) with a specific key. We have written the API to use directly the key instead, as that seems semantically equivalent.

Return codes

The list of standard method return codes specified by DDS (section 2.2.1.1) is modified, in particular:

DataReader and DataWriter interfaces

The DDS specification specifies multiple functions to read received data samples out of a DataReader:

We have decided to not implement all 12 of these. Instead, we implement smaller collection of methods:

All of the methods above require a ReadCondition to specify which samples to access, but it is very easy to specify "any" condition, i.e. access unconditionally.

There are also methods read_next_sample, take_next_sample , but these are essentially simplification wrappers for read/take.

In addition to these, we also provide a Rust Iterator interface for reading data.

Memory management

The DDS specification specifies manual memory management in the sense that many object types are created with a create_ method call and destroyed with a matching delete_ method call. We have opted to rely on Rust memory management wherever possible, including handling of payload data.

Based on rtps-rs

The RTPS implementation used here is derived from rtps-rs.