Adaptive Bitmask Protocols: Sub-10ms Coordination for 1000+ Agent Systems

Multi-agent systems (MAS) scaling beyond N >103 encounter a dual bottleneck: quadratic

coordination complexity and prohibitive bandwidth costs from rich state communication. We

present an architecture enabling O(N) coordination with deterministic sub-10 ms latency through

semantic bitmask encoding.

Our design adapts semantic hashing to dynamic, stateful agent coordination, coupling:

(1) 64-bit feature encoding with frequency-based schema pruning; (2) bicameral con-

trol/data separation using Model Context Protocol (MCP) for asynchronous schema con-

sensus and gRPC for synchronous transport; and (3) hierarchical weighted arbitration for

decision synthesis under uncertainty.

We present two architectural variants: a general-purpose 4-layer design for bandwidth-

constrained distributed systems, and a financial trading 5-layer design incorporating pattern

detection for alpha generation. Comprehensive stress testing across N = 10 to N = 5000 agents

demonstrates 85×payload reduction (24 bytes vs. 2 KB), 8.2 ms p99 decision latency at proto-

type scale, and 100% decision agreement between full-state and compressed encodings across

all four market regimes. Information-theoretic analysis reveals 37.23 bits of feature entropy

against 64-bit capacity (58.2% utilization), with 10.97 bits of joint pattern entropy exploitable

for extreme compression. Scale testing identifies coordinator saturation at N ≈ 600 under

single-threaded aggregation (ρ > 1.0), motivating sharded coordination as a required produc-

tion optimization.

Resources:

Open-Source Implementation (TypeScript SDK): https://github.com/jverene/adaptive-bitmask

Status: Technical Research Draft (Preprint) v3.3.5