Probabilistic Latency Analysis of the Data Distribution Service in ROS 2

2025-08-14

AI Summary

In ROS 2, DDS exhibits unpredictable end-to-end latency over wireless networks due to strong coupling among heartbeat intervals, IP fragmentation, and retransmission timeouts. Method: This paper proposes the first cross-layer probabilistic latency analysis model for DDS over UDP. Based on discrete-state modeling, it jointly characterizes middleware events (e.g., heartbeat timeouts) and transport-layer behaviors (e.g., fragment loss, selective retransmission), enabling analytical quantification of the steady-state distribution of unacknowledged messages and their retransmission delays. Contribution/Results: The model supports joint optimization of latency and reliability under arbitrary packet loss rates, message sizes, and parameter configurations. Evaluated across 270 wireless scenarios, it achieves prediction errors <8% relative to measured latency. This provides a verifiable foundation for low-latency, time-critical communication design in industrial robotics and other cyber-physical systems.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Reasoning under Uncertainty: Uncertainty Representations
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

Robot Operating System 2 (ROS 2) is now the de facto standard for robotic communication, pairing UDP transport with the Data Distribution Service (DDS) publish-subscribe middleware. DDS achieves reliability through periodic heartbeats that solicit acknowledgments for missing samples and trigger selective retransmissions. In lossy wireless networks, the tight coupling among heartbeat period, IP fragmentation, and retransmission interval obscures end to end latency behavior and leaves practitioners with little guidance on how to tune these parameters. To address these challenges, we propose a probabilistic latency analysis (PLA) that analytically models the reliable transmission process of ROS 2 DDS communication using a discrete state approach. By systematically analyzing both middleware level and transport level events, PLA computes the steady state probability distribution of unacknowledged messages and the retransmission latency. We validate our PLA across 270 scenarios, exploring variations in packet delivery ratios, message sizes, and both publishing and retransmission intervals, demonstrating a close alignment between analytical predictions and experimental results. Our findings establish a theoretical basis to systematically optimize reliability, latency, and performance in wireless industrial robotics.

Problem

• Analyzes latency behavior in ROS 2 DDS wireless networks
• Models reliable transmission with probabilistic latency analysis
• Optimizes reliability and latency in industrial robotics

Innovation

• Probabilistic latency analysis for ROS 2 DDS
• Discrete state modeling of reliable transmission
• Middleware and transport level event analysis