Optimizing Asynchronous Consensus Protocols for Decentralized Multi‑Agent Decision Engines in High‑Frequency Trading
Introduction High‑frequency trading (HFT) thrives on microseconds. In a market where a single millisecond can represent thousands of dollars, the latency of every software component matters. Modern HFT firms are moving away from monolithic order‑routing engines toward decentralized multi‑agent decision engines (DMAD‑E). In such architectures, dozens or hundreds of autonomous agents—each responsible for a specific market‑view, risk model, or strategy—collaborate to decide which orders to send, modify, or cancel. The collaboration point is a consensus layer that guarantees all agents agree on a shared decision (e.g., “execute 10,000 shares of X at price Y”). Traditional consensus protocols (e.g., classic Paxos or Raft) were designed for durability and fault tolerance in data‑center environments, not for the sub‑millisecond response times required by HFT. Consequently, asynchronous consensus—which tolerates variable message delays and does not rely on synchronized clocks—has become the focus of research and production engineering. ...