研究去中心化系统中多代理发现的稳定与效率平衡。
Usable Agent Discovery for Decentralized AI Systems
- 构建双层容错机制，应对节点与代理的动态变化。
- 结构化覆盖在节点故障时更高效，而泛洪式覆盖在就绪性优先时更快。
- 适用于大规模分布式智能体系统的部署与优化设计。
大规模智能体系统运行在分布式基础设施上，多个软件代理共享物理主机，并通过点对点机制发现彼此。发现机制需应对节点级扰动（如故障或主机退出）和代理级扰动（如按需激活、停用及状态切换）。这种交互重塑了传统结构化与非结构化覆盖之间的权衡。本文研究在双层扰动下去中心化代理发现问题，假设节点可承载多个代理，覆盖方式为结构化（如Kademlia）或基于泛洪（如Cyclon+Vicinity），且代理可在热/冷状态间切换。通过对比稳定、仅节点扰动、仅代理冷却、以及混合扰动场景，分析路由效率、系统韧性与服务就绪性的匹配关系：结构化覆盖在稳定与节点扰动下更鲁棒高效；而泛洪式覆盖在就绪性主导时仍具竞争力，甚至可能更快。
原文摘要 · Abstract (English)
Large-scale agentic systems run on distributed infrastructures where many software agents share physical hosts and are discovered via peer-to-peer mechanisms. Discovery must handle node-level churn from failures and host departures and agent-level churn from demand-driven activation, deactivation, and state changes. Their interaction reshapes classic trade-offs between structured and unstructured overlays. We study decentralized agent discovery under this two-level churn, assuming nodes host multiple agents, overlays are structured or gossip-based, and agents switch between warm and cold states. Using Kademlia as a structured and Cyclon+Vicinity as a gossip baseline, we compare stable, node-churn-only, agent-cooling-only, and combined regimes to see when routing efficiency, resilience, and service readiness align or favor different designs. Structured overlays are more robust and efficient in stable and node-churn regimes, while gossip-based overlays remain competitive and can be faster when readiness dominates.
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