比较三种分布式索引结构在边缘到云端的智能体发现性能
Trade-offs in Decentralized Agentic AI Discovery Across the Compute Continuum
- 对比 Chord、Pastry、Kademlia 三种结构在代理发现中的表现
- 在4096节点静态与动态环境中验证可靠性与开销差异
- 为边缘到云场景下的智能体发现提供选型参考
部署于计算连续体上的智能体系统需要在云、边缘及间歇连接环境中仍具备有效的发现机制。当前一些新兴智能体架构已将去中心化发现作为设计重点，将基于DHT的查找置于代理目录路径中。本文研究了主要结构化覆盖网络家族在代理发现中的权衡，以Chord、Pastry和Kademlia作为共享控制平面框架内的候选索引底层，在4096节点静态与代表性动态变化基准下，分析发现可靠性、启动行为及控制平面开销的差异。目标是明确这些覆盖网络在边缘到云环境中的适用工作点。
原文摘要 · Abstract (English)
Agentic systems deployed across the compute continuum need discovery mechanisms that remain effective across cloud, edge, and intermittently connected domains. In some emerging agentic architectures, decentralized discovery is already an active design direction, placing DHT-based lookup on the path toward agent directories. This paper studies the trade-offs among major structured-overlay families for agent discovery, comparing Chord, Pastry, and Kademlia as candidate indexing substrates within a shared control-plane framework. Using a benchmark subset centered on a 4096-node stationary comparison and a representative 4096-node churn benchmark, the paper characterizes how discovery reliability, startup behavior, and control-plane overhead vary across these overlays. The goal is to clarify the operating points they expose for agent discovery across edge-to-cloud environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。