Comparison of Middlewares in Edge-to-Edge and Edge-to-Cloud Communication for Distributed ROS2 Systems

TL;DR

This study provides a quantitative analysis for the communication performance of utilized networking middlewares including MQTT and Zenoh alongside DDS in ROS 2 among a multiple host system and assesses the drift error over time caused by these networking middlewares with the robot moving in an identical square-shaped path.

Abstract

The increased data transmission and number of devices involved in communications among distributed systems make it challenging yet significantly necessary to have an efficient and reliable networking middleware. In robotics and autonomous systems, the wide application of ROS\,2 brings the possibility of utilizing various networking middlewares together with DDS in ROS\,2 for better communication among edge devices or between edge devices and the cloud. However, there is a lack of comprehensive communication performance comparison of integrating these networking middlewares with ROS\,2. In this study, we provide a quantitative analysis for the communication performance of utilized networking middlewares including MQTT and Zenoh alongside DDS in ROS\,2 among a multiple host system. For a complete and reliable comparison, we calculate the latency and throughput of these middlewares by sending distinct amounts and types of data through different network setups including Ethernet, Wi-Fi, and 4G. To further extend the evaluation to real-world application scenarios, we assess the drift error (the position changes) over time caused by these networking middlewares with the robot moving in an identical square-shaped path. Our results show that CycloneDDS performs better under Ethernet while Zenoh performs better under Wi-Fi and 4G. In the actual robot test, the robot moving trajectory drift error over time (96\,s) via Zenoh is the smallest. It is worth noting we have a discussion of the CPU utilization of these networking middlewares and the performance impact caused by enabling the security feature in ROS\,2 at the end of the paper.

Figures (8)

• Figure 1: Proposed evaluation scheme to test DDS, Zenoh, and Mosquitto in different network setups
• Figure 2: DDS architecture in the ROS 2 system
• Figure 3: The Turtlebot 4 robot used in the experiment with OptiTrack markers on top
• Figure 4: Actual robot setup. The TurtleBot 4 receives the "/cmd_vel" velocity command from the HOST to run a square trajectory. The linear velocity is set to 0.33 m/s forwarding, and the turning velocity is set to 30 degree/s. The OptiTrack MOCAP System is only used to record the trajectories, which are subsequently employed in calculating the drift errors.
• Figure 5: Network setups. The router or broker is for Zenoh and MQTT; DDS does not need an individual broker.