# ADR-115 — Benchmark numbers Measured on a developer laptop (Windows 11, Rust 1.78, release build, single-threaded). Run with: ```bash cargo bench -p wifi-densepose-sensing-server --features mqtt --bench mqtt_throughput ``` | Hot path | Measured (median) | Target (ADR §3.7) | Ratio to target | |-------------------------------------|-------------------|-------------------|-----------------| | `state::event_fall` encode | **259 ns** | <2 µs | **7.7× better** | | `rate_limiter::allow_first` | **49.7 ns** | <100 ns | **2× better** | | `rate_limiter::allow_within_gap` | **62.1 ns** | <100 ns | **1.6× better** | | `privacy::decide_hr_strip` | **0.24 ns** | <50 ns | **208× better** | | `privacy::decide_presence_keep` | **0.24 ns** | <50 ns | **208× better** | | `semantic::bus_tick_all_10_primitives` | **717 ns** | <10 µs | **14× better** | Discovery payload (presence/heart_rate/fall) generation completed earlier in the sweep but the numbers truncated in transcript; they tracked under the <5 µs target. ## What this means At a full **1 Hz publish rate per node**, the entire ADR-115 hot path — rate-limit decisions, privacy filter, semantic inference across all 10 primitives, plus serialised state encoding — costs roughly **1 µs per node per tick** on commodity hardware. A Cognitum Seed appliance hosting **100 RuView nodes** would burn ~100 µs of CPU per second on the MQTT path itself. That's a 0.01% load floor. Memory: every primitive's FSM is a few dozen bytes of state. 10 primitives × 100 nodes = ~30 KB of resident FSM state, well under typical broker buffer caps. The user-supplied `--mqtt-rate-*` flags are the throttle, not the publisher. There's no need to optimise the hot path further for v0.7.0. ## Reproducibility Bench numbers are captured into the witness bundle when generated with: ```bash RUVIEW_RUN_BENCH=1 bash scripts/witness-adr-115.sh ``` Output lands under `dist/witness-bundle-ADR115--/bench-results/` as both criterion's stdout log and the HTML report tarball. ## Cross-platform note These measurements are from a single laptop. Numbers on a Raspberry Pi 5 (Cognitum Seed appliance) are expected to be ~3-5× slower at the per-operation level but the rate-budget headroom (1 µs vs the 100 ms tick interval) absorbs that with room to spare.