当发现成为风暴：面向无线机器人网络的ROS 2发现模型
When Discovery Becomes a Storm: A ROS 2 Discovery Model for Wireless Robotic Networks
AI总结：
针对无线机器人网络中ROS 2的发现风暴问题，提出闭环分析模型并验证，设计响应感知策略将平均发现完成时间降低25.3%至39.7%。
AI中文摘要：
在机器人操作系统2（ROS 2）中，数据分发服务（DDS）参与者必须在交换数据前相互发现。在无线环境中，延迟或丢失的发现消息会导致可靠性计时器超时，触发重传，加剧信道争用并进一步延迟发现消息的传递，这种自我强化的反馈会升级为发现风暴。现有模型在固定传输条件下表征发现需求，但未捕捉共享信道延迟如何改变协议状态并产生更多流量。为解决此问题，我们提出首个ROS 2发现的闭环分析模型，其表征延迟诱导反馈如何放大重传开销并引发严重发现风暴。该模型将信道争用表示为共享服务过程，耦合消息传输延迟与接收者状态及可靠性计时器，可预测发现完成时间和各类消息数量。我们通过90种拓扑配置下的1350次实验运行验证该模型，开环空时基线仅能捕获高负载完成时间的一部分，闭环模型再现了该增长并保守地对观测到的高负载范围进行上界估计。基于模型的见解，我们进一步设计了响应感知发现策略，可将平均发现完成时间降低25.3%至39.7%。
英文摘要：
In Robot Operating System 2 (ROS 2), Data Distribution Service (DDS) participants must discover one another before exchanging data. In wireless environments, delayed or lost discovery messages cause reliability timers to expire, triggering retransmissions that intensify channel contention and further delay the delivery of discovery messages. This self-reinforcing feedback can escalate into a discovery storm. Existing models characterize discovery demand under fixed delivery conditions, but do not capture how shared-channel delay changes protocol state and generates further traffic. To address this issue, we present the first closed-loop analytical model of ROS 2 discovery that characterizes how delay-induced feedback amplifies retransmission overhead and leads to severe discovery storms. Our model represents channel contention as a shared service process, coupling message-delivery latency with receiver states and reliability timers. The model predicts both discovery completion time and per-class message counts. We validate the model through 1,350 experimental runs across 90 topology configurations. An open-loop airtime baseline captures only a fraction of the high-load completion time. The closed-loop model reproduces this rise and conservatively upper-bounds the observed high-load range. Guided by insights from the model, we further design a response-aware discovery policy that reduces mean discovery completion time by 25.3% to 39.7%.
