Files
meshtastic-firmware/src/modules/HopScalingModule.cpp
T
de345939af Automatic variable hop limits based on mesh activity and size estimation (#10176)
* asdf

* Implement SphereOfInfluenceModule for traffic management and eviction tracking

* Implement Sphere of Influence module for dynamic hop limit adjustment and role-based floor

* Update SAMPLING_DENOMINATOR to improve mesh size estimation accuracy

* Add debug logging for scale factor estimation and per-hop node counts in SphereOfInfluenceModule

* Enable variable hop limits and role-based hop floors in Sphere of Influence module

* Respond to copilot review

* Disable variable hop limits and role-based hop floors in Sphere of Influence module

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Implement adaptive sampling for unique node ID tracking in Sphere of Influence module

* Add state persistence for Sphere of Influence module

* Enhance Sphere of Influence module with state management and adaptive sampling adjustments

* Refactor hop scaling functionality: remove SphereOfInfluenceModule and introduce HopScalingModule

- Deleted SphereOfInfluenceModule.h, consolidating its responsibilities into the new HopScalingModule.
- Added HopScalingModule.h and HopScalingModule.cpp to manage hop scaling logic, including eviction tracking and sampling-based mesh size estimation.
- Implemented methods for recording evictions and packet senders, estimating scale factors, and computing required hops based on node activity.
- Introduced state persistence for hop scaling parameters to maintain continuity across reboots.
- Enhanced thread safety and modularity by utilizing concurrency features.

* Guard out STM32. Sowwy.

* Refactor HopScalingModule: enhance sampling logic and improve state management

* Add unit tests for HopScalingModule: implement mock database and various test scenarios

* Refactor test output in HopScalingModule tests: replace printf with TEST_MESSAGE for better integration with Unity

* Refactor HopScalingModule logging: replace lastStatusMode with descriptive mode names for improved readability

* Refactor test_main.cpp: change NodeNum variable to static and improve comments for clarity

* Remove unnecessary delay in setup function for improved test performance

* Add missing include for MeshTypes in test_main.cpp

* Refactor HopScalingModule tests: enhance mesh topology scenarios and improve test clarity

* Update HopScalingModule tests: flesh out node scenarios and improve clarity for dense and sparse mesh cases

* Fix politeness factor calculations in HopScalingModule and update related test scenarios for clarity. Remove outdated design doc.

* Enhance HopScalingModule: add sampled estimate for scaling decisions and refactor initial run state management

* Add sample traffic injection for HopScaling tests to enhance sampledEst visibility

* Enhance HopScalingModule: adjust windowFraction calculation for early triggers and improve test output formatting

* Enhance HopScalingModule: add jitter functionality to sampling denominator and update tests for consistent behavior

* Enhance HopScalingModule: implement adaptive sampling denominator adjustment and add reset functionality for tests

* Enhance HopScalingTestShim: add test-only clock and window helpers, update injectSampleTraffic for adaptive sampling, and improve scenario summary output

* Enhance HopScalingModule: add detailed documentation for functions, improve clarity of jitter and sampling logic, and reset functionality in tests

* Enhance HopScalingModule: add evictionEstimate parameter to estimateScaleFactor and update related logging for improved mesh size estimation

* Enhance HopScalingModule: adjust effective rolls calculation for improved accuracy, add eviction estimate logic, responding to all copilot review points

* Implement CompactHistogram for parallel hop scaling sampling

- Added CompactHistogram class to track node hop distances with bitwise sampling.
- Integrated CompactHistogram into HopScalingModule for independent packet sampling.
- Updated NodeDB to feed both the hop scaling module and the new histogram sampler.
- Enhanced HopScalingModule with methods to sample packets for the histogram and retrieve hop distribution statistics.
- Implemented tests for CompactHistogram functionality, including sampling, window rolling, and adaptive denominator scaling.
- Updated existing tests to validate the integration of the new histogram sampling mechanism.

* Enhance CompactHistogram and HopScalingModule: add per-hop distribution functionality, improve time handling for unit tests, and refine test setup for deterministic behavior

* CompactHistogram: add mesh size estimation, improve entry replacement logic, and update logging for per-hop distribution

* Refactor HopScalingModule and CompactHistogram integration

- Removed the suggestedHopFromCompactHistogram function to streamline hop suggestion logic.
- Updated HopScalingModule to directly utilize CompactHistogram's internal methods for hop suggestions and sampling.
- Enhanced logging in HopScalingModule to provide detailed histogram statistics.
- Modified test cases to ensure comprehensive coverage of new histogram behaviors and sampling logic.
- Improved node ID distribution in tests to better exercise sampling mechanisms.
- Ensured that filtering denominators are held for 12 hours before dropping, enhancing stability in sampling.

* Refactor CompactHistogram to support 13-hour activity tracking and introduce politeness regimes

- Updated the bitfield structure to accommodate 13-hour seen tracking.
- Changed the logic in rollHour() to analyze activity over the last 0-2 hours vs. 1-3 hours for politeness factor calculation.
- Introduced three politeness levels: GENEROUS, DEFAULT, and STRICT based on recent activity ratios.
- Adjusted filtering and sampling logic to reflect the new 13-hour tracking period.
- Updated unit tests to validate new behavior and ensure proper functionality of politeness regimes.

* Enhance CompactHistogram and HopScalingModule for improved sampling and decision-making

- Introduced a session-specific hash seed in CompactHistogram to reduce bias in node ID sampling.
- Updated sampling logic to use hashed node IDs instead of raw IDs for filtering and entry management.
- Added histogram rollover tracking in HopScalingModule to ensure proper decision-making after initial data collection.
- Adjusted logging to reflect the active state of the histogram and its comparison with NodeDB advisory hops.
- Enhanced unit tests to validate new sampling logic and memory layout changes.

* Expose hashNodeId for testing in CompactHistogram

* Add mesh trend statistics to CompactHistogram for enhanced activity tracking

* Implement histogram state persistence in CompactHistogram with save and load functions

* Refactor CompactHistogram to improve entry management and enhance rollHour logging

* feat: add HopScalingModule for adaptive hop limit recommendations

Introduces HopScalingModule, a sampled hop-distance histogram that
recommends the minimum hop limit needed to reach ~40 nodes, and
automatically reducing the hops as the mesh grows.

Key design:
- 512-byte packed histogram (128 × 4-byte Record entries) embedded
   in a new HopScalingModule.
- Each Record: 16-bit node hash, 3-bit hop distance, 13-bit seen bitmap
- Sampling filter: only nodes where (hash & (denom-1)) == 0 are kept;
  denominator doubles on overflow and halves when utilisation is low
- Hourly rollHour(): tallies per-hop counts, walks scaled buckets to
  find the minimum hop satisfying TARGET_AFFECTED_NODES (40), applies a
  politeness extension based on recent/older activity ratio, shifts all
  seen bitmaps, and persists state to /prefs/hopScalingState.bin
- Hop recommendation gated by bootstrap (requires >=1 rollHour before
  overriding HOP_MAX)
- NodeDB calls samplePacketForHistogram() on every non-MQTT rx packet
- Module also estimates total mesh size and logs useful information about
  mesh characteristics.

Changes:
- src/modules/HopScalingModule.h/.cpp: new module
- src/mesh/NodeDB.cpp: wire up samplePacketForHistogram
- src/mesh/Router.cpp: consume getLastRequiredHop()
- test/test_hop_scaling/: 12-test suite covering all mesh topologies and
  anticipated operational requirements

* test: increase run iterations in sparse to dense transition test

* feat: refactor HopScalingModule to use RUNS_PER_HOUR constant and improve logging

* feat: enhance HopScalingModule with filtering denominator management and add tests for state transitions

* refactor: remove CompactHistogram module and related files

* address copilot review comments

* Tweak: packet sampling only lora

* ove role-based hop floor logic and related definitions into the module - keep it in one place.

* Refactor MockNodeDB to use nodeInfoLiteSetBit for MQTT flag setting

* Refactor hop scaling parameters and logic to integer maths and put default values in defaults.h. Small flash size reduction, no functional impact.

* Update unit test preprocessor directives to PIO_UNIT_TESTING for consistency

* refactor: improve test output organization and clarity in hop scaling tests

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2026-06-04 05:59:49 -05:00

494 lines
21 KiB
C++

#include "HopScalingModule.h"
#include "SafeFile.h"
#include "meshUtils.h"
#if HAS_VARIABLE_HOPS
#include "FSCommon.h"
#include "NodeDB.h"
#include "SPILock.h"
#include "concurrency/LockGuard.h"
#include "mesh-pb-constants.h"
#include <algorithm>
#include <cmath>
#include <cstring>
namespace
{
// Module scheduling
constexpr uint32_t INITIAL_DELAY_MS = 30 * 1000UL; // Startup grace period before first run
constexpr uint32_t RUN_INTERVAL_MS = 5 * 60 * 1000UL; // Emit micro-summary every 5 minutes
// RUNS_PER_HOUR is a public class constant in HopScalingModule.h
// Persistence
// Note: this only needs incrementing if the published arrangement changes. For testing purposes, or prior to widespread release,
// it can stay the same even if the internal layout changes.
constexpr uint32_t HISTOGRAM_STATE_MAGIC = 0x48535432; // 'HST2' — layout v2
constexpr uint8_t HISTOGRAM_STATE_VERSION = 1;
constexpr const char *HISTOGRAM_STATE_FILE = "/prefs/hopScalingState.bin";
#pragma pack(push, 1)
struct PersistedHistogram {
uint32_t magic;
uint8_t version;
uint8_t samplingDenominator;
uint8_t filteringDenominator;
uint8_t filterDenomHoldRollsRemaining; // rollHour() calls remaining in the hold; 0 when expired/not active
uint16_t hashSeed;
Record entries[HopScalingModule::CAPACITY]; // full 512-byte array; count derived on load
};
#pragma pack(pop)
} // namespace
HopScalingModule *hopScalingModule;
// ---------------------------------------------------------------------------
// Lifecycle
// ---------------------------------------------------------------------------
HopScalingModule::HopScalingModule() : concurrency::OSThread("HopScaling")
{
clear();
loadFromDisk();
setIntervalFromNow(INITIAL_DELAY_MS);
}
void HopScalingModule::clear()
{
memset(entries, 0, sizeof(entries));
count = 0;
samplingDenominator = DENOM_MIN;
filteringDenominator = DENOM_MIN;
filteringDenomHoldRollsRemaining = 0;
lastPerHopCounts = {};
lastSuggestedHop = MAX_HOP;
lastPoliteNumer = POLITENESS_DEFAULT;
lastTrendStats = {};
memset(denominatorHistory, DENOM_MIN, sizeof(denominatorHistory));
#ifndef PIO_UNIT_TESTING
hashSeed = static_cast<uint16_t>(random());
#else
hashSeed = 0; // deterministic in unit tests
#endif
}
// ---------------------------------------------------------------------------
// Persistence
// ---------------------------------------------------------------------------
void HopScalingModule::saveToDisk() const
{
#ifdef FSCom
FSCom.mkdir("/prefs");
PersistedHistogram state{};
state.magic = HISTOGRAM_STATE_MAGIC;
state.version = HISTOGRAM_STATE_VERSION;
state.samplingDenominator = samplingDenominator;
state.filteringDenominator = filteringDenominator;
state.filterDenomHoldRollsRemaining = filteringDenomHoldRollsRemaining;
state.hashSeed = hashSeed;
// Save all CAPACITY slots; count is reconstructed on load by scanning seenHoursAgo.
memcpy(state.entries, entries, sizeof(state.entries));
auto file = SafeFile(HISTOGRAM_STATE_FILE, true);
const size_t written = file.write(reinterpret_cast<const uint8_t *>(&state), sizeof(state));
if (file.close() && written == sizeof(state)) {
LOG_DEBUG("[HOPSCALE] Saved: count=%u samp=1/%u filt=1/%u holdRollsRemaining=%u", count, samplingDenominator,
filteringDenominator, state.filterDenomHoldRollsRemaining);
} else {
LOG_WARN("[HOPSCALE] Failed to write %s (%u of %u bytes)", HISTOGRAM_STATE_FILE, static_cast<unsigned>(written),
static_cast<unsigned>(sizeof(state)));
}
#endif
}
void HopScalingModule::loadFromDisk()
{
#ifdef FSCom
concurrency::LockGuard g(spiLock);
auto file = FSCom.open(HISTOGRAM_STATE_FILE, FILE_O_READ);
if (!file)
return;
PersistedHistogram state{};
const bool readOk = (file.read(reinterpret_cast<uint8_t *>(&state), sizeof(state)) == sizeof(state));
file.close();
// Validate magic, version, denom range, denom power-of-two invariant, and hold counter.
if (!readOk || state.magic != HISTOGRAM_STATE_MAGIC || state.version != HISTOGRAM_STATE_VERSION ||
state.samplingDenominator < DENOM_MIN || state.samplingDenominator > DENOM_MAX ||
state.filteringDenominator < state.samplingDenominator || state.filteringDenominator > DENOM_MAX ||
!is_pow_of_2(state.samplingDenominator) || !is_pow_of_2(state.filteringDenominator) ||
state.filterDenomHoldRollsRemaining > FILTER_DENOM_HOLD_ROLLS) {
LOG_DEBUG("[HOPSCALE] No valid persisted state (magic=%08x ver=%u samp=%u filt=%u hold=%u), starting fresh", state.magic,
state.version, state.samplingDenominator, state.filteringDenominator, state.filterDenomHoldRollsRemaining);
return;
}
// Derive count by scanning: active entries have seenHoursAgo != 0; pack them to the front.
uint8_t restored = 0;
for (uint8_t i = 0; i < CAPACITY && restored < CAPACITY; i++) {
if (state.entries[i].seenHoursAgo != 0u) {
entries[restored++] = state.entries[i];
}
}
count = restored;
samplingDenominator = state.samplingDenominator;
filteringDenominator = state.filteringDenominator;
filteringDenomHoldRollsRemaining = state.filterDenomHoldRollsRemaining;
// denominatorHistory can't be recovered; initialise all slots to filteringDenominator so
// the first few post-reboot scaledPerHour values use a safe (slightly conservative) multiplier.
memset(denominatorHistory, filteringDenominator, sizeof(denominatorHistory));
hashSeed = state.hashSeed;
LOG_INFO("[HOPSCALE] Restored: count=%u samp=1/%u filt=1/%u holdRollsRemaining=%u", count, samplingDenominator,
filteringDenominator, state.filterDenomHoldRollsRemaining);
#endif
}
// ---------------------------------------------------------------------------
// Core API
// ---------------------------------------------------------------------------
void HopScalingModule::samplePacketForHistogram(uint32_t nodeId, uint8_t hopCount)
{
const uint16_t hash = hashNodeId(nodeId);
if (!passesFilter(hash, samplingDenominator))
return;
hopCount = std::min(hopCount, MAX_HOP);
// Update an existing entry
Record *entry = nullptr;
for (uint8_t i = 0; i < count; i++) {
if (entries[i].nodeHash == hash) {
entry = &entries[i];
break;
}
}
if (entry) {
entry->hops_away = hopCount;
markCurrentHour(*entry);
return;
}
// New node: trim if necessary before allocating a slot
if (getFillPercentage() >= FILL_HIGH_PCT) {
trimIfNeeded();
}
if (count < CAPACITY) {
entries[count].nodeHash = hash;
entries[count].hops_away = hopCount;
entries[count].seenHoursAgo = 1u; // mark current hour
count++;
} else {
LOG_WARN("[HOPSCALE] Histogram full at samp=1/%u (DENOM_MAX=%u); dropping node hash=0x%04x; hop recommendation may be "
"skewed!!!",
samplingDenominator, DENOM_MAX, hash);
}
}
void HopScalingModule::rollHour()
{
// Advance denominatorHistory before the tally so each slot h holds the filteringDenominator
// that was active when seenHoursAgo bit h was set. hourlyRaw[h] is then gated per-slot by
// denominatorHistory[h], giving a correct population estimate for each historical hour even
// when filteringDenominator changes between rolls. Scale-up backfills the entire array so
// the invariant holds retroactively (see trimIfNeeded()).
for (uint8_t h = 12; h > 0; h--)
denominatorHistory[h] = denominatorHistory[h - 1];
denominatorHistory[0] = filteringDenominator;
// 1. Tally per-hop counts and per-slot hourly activity in one pass.
// hourlyRaw[h]: gated per-slot by denominatorHistory[h] so the raw count and its
// multiplier are always consistent, even across filteringDenominator transitions.
// counts.*: gated uniformly by the current filteringDenominator for a consistent
// population estimate used by the hop-walk recommendation (step 2).
PerHopCounts counts{};
uint16_t hourlyRaw[13] = {};
uint16_t trendNewThisHour = 0;
uint16_t trendReturning = 0;
uint16_t trendLapsed = 0;
uint16_t trendOlderThan4h = 0;
uint16_t trendAgingOut = 0;
for (uint8_t i = 0; i < count; i++) {
const uint16_t hash = entries[i].nodeHash;
const uint32_t seen = entries[i].seenHoursAgo;
// Per-slot hourly activity: gate each slot by its own denominator.
for (uint8_t h = 0; h < 13; h++) {
if ((seen & (1u << h)) && passesFilter(hash, denominatorHistory[h]))
hourlyRaw[h]++;
}
// Hop counts and trend stats: uniform current-denominator gate.
if (!passesFilter(hash, filteringDenominator))
continue;
if (seenInLast13h(entries[i])) {
counts.perHop[entries[i].hops_away]++;
counts.total++;
}
const bool heardThisHour = (seen & 1u) != 0u;
const bool heardLastHour = (seen & 2u) != 0u;
const bool hasOlderHistory = (seen >> 1u) != 0u;
const bool recentlySilent = (seen & 0xFu) == 0u;
if (heardThisHour && !hasOlderHistory)
trendNewThisHour++;
else if (heardThisHour && hasOlderHistory)
trendReturning++;
if (!heardThisHour && heardLastHour)
trendLapsed++;
if (recentlySilent && (seen & 0x1FF0u) != 0u)
trendOlderThan4h++;
if (seen == (1u << 12u))
trendAgingOut++;
}
lastPerHopCounts = counts;
// 1b. Compute politeness factor from the 0-2 h vs 1-3 h activity ratio.
{
const uint32_t recent = static_cast<uint32_t>(hourlyRaw[0]) + hourlyRaw[1];
const uint32_t older = static_cast<uint32_t>(hourlyRaw[1]) + hourlyRaw[2];
if (older > 1 && recent > 1) {
const uint32_t r = static_cast<uint32_t>(recent) * ACTIVITY_WEIGHT_SCALE;
const uint32_t o = static_cast<uint32_t>(older);
if (r < o * ACTIVITY_WEIGHT_GENEROUS_MAX_NUMER)
lastPoliteNumer = POLITENESS_GENEROUS;
else if (r > o * ACTIVITY_WEIGHT_STRICT_MIN_NUMER)
lastPoliteNumer = POLITENESS_STRICT;
else
lastPoliteNumer = POLITENESS_DEFAULT;
} else {
lastPoliteNumer = POLITENESS_DEFAULT;
}
}
// 1c. Scale and cache trend stats (denominatorHistory already advanced above).
{
MeshTrendStats t{};
for (uint8_t h = 0; h < 13; h++) {
const uint32_t s = static_cast<uint32_t>(hourlyRaw[h]) * denominatorHistory[h];
t.scaledPerHour[h] = static_cast<uint16_t>(std::min<uint32_t>(s, UINT16_MAX));
}
auto scale = [&](uint16_t raw) -> uint16_t {
return static_cast<uint16_t>(std::min<uint32_t>(static_cast<uint32_t>(raw) * filteringDenominator, UINT16_MAX));
};
t.newThisHour = scale(trendNewThisHour);
t.returningThisHour = scale(trendReturning);
t.lapsedSinceLastHour = scale(trendLapsed);
t.olderThan4h = scale(trendOlderThan4h);
t.agingOut = scale(trendAgingOut);
lastTrendStats = t;
}
// 2. Walk scaled hop buckets to produce a hop-limit recommendation.
// effectiveMin: walk threshold — first hop whose cumulative count reaches this.
// effectiveMax: ceiling on the one-hop extension check with GENEROUS politeness.
const uint16_t effectiveMin = TARGET_AFFECTED_NODES;
const uint16_t effectiveMax = MAX_TARGET_NODES;
uint8_t suggested = MAX_HOP;
if (counts.total > 0) {
uint32_t cumulative = 0;
for (uint8_t hop = 0; hop <= MAX_HOP; hop++) {
cumulative += static_cast<uint32_t>(counts.perHop[hop]) * filteringDenominator;
if (cumulative >= effectiveMin) {
suggested = hop;
break;
}
}
if (suggested < MAX_HOP) {
const uint32_t atNext = static_cast<uint32_t>(counts.perHop[suggested + 1]) * filteringDenominator;
// politeLimit = effectiveMin + gap * politeNumer / POLITENESS_DENOM
// Multiply both sides by POLITENESS_DENOM to stay in integers.
const uint32_t gap = static_cast<uint32_t>(effectiveMax) - static_cast<uint32_t>(effectiveMin);
if ((cumulative + atNext) * POLITENESS_DENOM <=
static_cast<uint32_t>(effectiveMin) * POLITENESS_DENOM + gap * lastPoliteNumer) {
suggested++;
}
}
}
lastSuggestedHop = suggested;
// 3. Log scaled per-hop counts and recommendation.
{
uint16_t scaled[MAX_HOP + 1];
for (uint8_t h = 0; h <= MAX_HOP; h++) {
const uint32_t s = static_cast<uint32_t>(counts.perHop[h]) * filteringDenominator;
scaled[h] = static_cast<uint16_t>(std::min<uint32_t>(s, UINT16_MAX));
}
const uint32_t scaledTotal = static_cast<uint32_t>(counts.total) * filteringDenominator;
memcpy(lastScaledPerHop, scaled, sizeof(lastScaledPerHop));
LOG_INFO("[HOPSCALE] rollHour: entries=%u/128 samp=1/%u filt=1/%u counted=%u est=%u suggestedHop=%u polite=%u/4", count,
samplingDenominator, filteringDenominator, counts.total, static_cast<unsigned>(scaledTotal), suggested,
lastPoliteNumer);
const auto &ts = lastTrendStats;
LOG_INFO("[HOPSCALE] scaledSeenPerHour (h0=now): [%u %u %u %u %u %u %u %u %u %u %u %u %u]", ts.scaledPerHour[0],
ts.scaledPerHour[1], ts.scaledPerHour[2], ts.scaledPerHour[3], ts.scaledPerHour[4], ts.scaledPerHour[5],
ts.scaledPerHour[6], ts.scaledPerHour[7], ts.scaledPerHour[8], ts.scaledPerHour[9], ts.scaledPerHour[10],
ts.scaledPerHour[11], ts.scaledPerHour[12]);
LOG_INFO("[HOPSCALE] trend: new=%u returning=%u lapsed=%u olderThan4h=%u agingOut=%u", ts.newThisHour,
ts.returningThisHour, ts.lapsedSinceLastHour, ts.olderThan4h, ts.agingOut);
}
// 4. Scale-down check: if fewer than FILL_LOW_PCT% of capacity pass the filteringDenominator
// gate and are active, halve samplingDenominator to admit more nodes.
// Note: during a filteringDenominator hold period, lowering samplingDenominator does not
// immediately improve counts.total (new admissions don't pass the elevated
// filteringDenominator). On a genuinely quieting mesh this check can therefore fire on
// consecutive hours, cascading samplingDenominator toward DENOM_MIN. This is intentional:
// rapid re-admission allows quick recovery if the mesh returns. The hop recommendation
// stays conservative (MAX_HOP) throughout because filteringDenominator remains elevated;
// step 5 below re-synchronises the denominators once the hold expires.
if (counts.total * 100u < static_cast<uint32_t>(CAPACITY) * FILL_LOW_PCT) {
if (samplingDenominator > DENOM_MIN) {
samplingDenominator = static_cast<uint8_t>(samplingDenominator / 2u);
LOG_INFO("[HOPSCALE] Scale-down: sampling denom halved to %u (filter denom=%u)", samplingDenominator,
filteringDenominator);
}
}
// 5. Tick down the hold counter; once it reaches zero, halve filteringDenominator toward
// samplingDenominator once per rollHour() (= once per hour) rather than a single jump:
// avoids a sudden large change in the hop-walk count when samplingDenominator cascaded
// down significantly during the hold period. No new hold is placed on each step — the
// 13-roll hold already guaranteed that re-admitted nodes have full seenHoursAgo history;
// further pacing is provided naturally by the 1-step-per-hour rate. denominatorHistory
// is updated automatically by the shift at the top of rollHour(), so no backfill here.
if (filteringDenominator > samplingDenominator) {
if (filteringDenomHoldRollsRemaining > 0)
filteringDenomHoldRollsRemaining--;
if (filteringDenomHoldRollsRemaining == 0) {
const uint8_t stepped = static_cast<uint8_t>(filteringDenominator / 2u);
filteringDenominator = (stepped > samplingDenominator) ? stepped : samplingDenominator;
LOG_INFO("[HOPSCALE] Filter denom stepped to %u (samp=1/%u)", filteringDenominator, samplingDenominator);
}
}
// 6. Shift all seen bitmaps left by one slot (opens a fresh slot for the new hour).
for (uint8_t i = 0; i < count; i++) {
rollSeenBits(entries[i]);
}
if (histogramRollCount < 255)
histogramRollCount++;
saveToDisk();
}
// ---------------------------------------------------------------------------
// Internal helpers
// ---------------------------------------------------------------------------
void HopScalingModule::trimIfNeeded()
{
// Step 1: evict stale entries (not seen in any of the past 13 hours).
uint8_t newCount = 0;
for (uint8_t i = 0; i < count; i++) {
if (seenInLast13h(entries[i])) {
if (i != newCount) {
entries[newCount] = entries[i];
}
newCount++;
}
}
count = newCount;
// Step 2: if still too full, double the sampling denominator and remove non-matching entries.
if (getFillPercentage() >= FILL_HIGH_PCT && samplingDenominator < DENOM_MAX) {
samplingDenominator = static_cast<uint8_t>(
std::min<uint16_t>(static_cast<uint16_t>(samplingDenominator) * 2u, static_cast<uint16_t>(DENOM_MAX)));
filteringDenominator = std::max(filteringDenominator, samplingDenominator);
filteringDenomHoldRollsRemaining = FILTER_DENOM_HOLD_ROLLS;
// Raise any denominatorHistory slot that is below the new filteringDenominator.
// Slots already above it (recorded during a prior scale-up that hasn't fully stepped
// down yet) are left untouched: eviction at samplingDenominator retains exactly those
// entries, so the old higher gate remains accurate for those historical hours.
// Slots below the new value must be raised because the eviction removed entries that
// had been admitted at the looser old gate — the remaining entries represent a 1/N
// subsample where N is the new filteringDenominator, not the old smaller value.
for (uint8_t h = 0; h < 13; h++)
denominatorHistory[h] = std::max(denominatorHistory[h], filteringDenominator);
LOG_INFO("[HOPSCALE] Scale-up: samp denom doubled to %u (filt=%u)", samplingDenominator, filteringDenominator);
newCount = 0;
for (uint8_t i = 0; i < count; i++) {
if (passesFilter(entries[i].nodeHash, samplingDenominator)) {
if (i != newCount) {
entries[newCount] = entries[i];
}
newCount++;
}
}
count = newCount;
}
}
void HopScalingModule::logStatusReport(bool didHourlyUpdate) const
{
const bool histActive = (histogramRollCount > 0 && count > 0);
const auto &histCounts = lastPerHopCounts;
const uint8_t runsRemaining = didHourlyUpdate ? RUNS_PER_HOUR : (RUNS_PER_HOUR - runsSinceLastHourlyUpdate);
const uint8_t minsUntilRollover = runsRemaining * (RUN_INTERVAL_MS / (60 * 1000UL));
LOG_INFO("[HOPSCALE] hop=%u histActive=%u fill=%u%% samp=1/%u filt=1/%u entries=%u lastCounted=%u polite=%u/4 "
"nextRoll=%umin",
lastRequiredHop, histActive ? 1u : 0u, getFillPercentage(), samplingDenominator, filteringDenominator, count,
histCounts.total, lastPoliteNumer, minsUntilRollover);
LOG_INFO("[HOPSCALE] nodes perHop: [%u %u %u %u %u %u %u %u]", histCounts.perHop[0], histCounts.perHop[1],
histCounts.perHop[2], histCounts.perHop[3], histCounts.perHop[4], histCounts.perHop[5], histCounts.perHop[6],
histCounts.perHop[7]);
LOG_INFO("[HOPSCALE] last scaled perHop: [%u %u %u %u %u %u %u %u]", lastScaledPerHop[0], lastScaledPerHop[1],
lastScaledPerHop[2], lastScaledPerHop[3], lastScaledPerHop[4], lastScaledPerHop[5], lastScaledPerHop[6],
lastScaledPerHop[7]);
}
int32_t HopScalingModule::runOnce()
{
const bool isFirstRun = !hasCompletedInitialRun;
bool didHourlyUpdate = false;
if (isFirstRun) {
hasCompletedInitialRun = true;
runsSinceLastHourlyUpdate = 0;
didHourlyUpdate = true;
} else {
runsSinceLastHourlyUpdate++;
if (runsSinceLastHourlyUpdate >= RUNS_PER_HOUR) {
runsSinceLastHourlyUpdate = 0;
didHourlyUpdate = true;
}
}
if (didHourlyUpdate && !isFirstRun) {
rollHour();
}
if (didHourlyUpdate) {
uint8_t suggested = (histogramRollCount > 0 && count > 0) ? lastSuggestedHop : HOP_MAX;
// Role-based hop floor: TRACKER/TAK_TRACKER always reach at least 2 hops,
// SENSOR reaches at least 1, so these reporting roles remain reachable even
// on a dense mesh where the histogram recommends a lower hop count.
uint8_t roleFloor = 0;
switch (config.device.role) {
case meshtastic_Config_DeviceConfig_Role_TRACKER:
case meshtastic_Config_DeviceConfig_Role_TAK_TRACKER:
roleFloor = 2;
break;
case meshtastic_Config_DeviceConfig_Role_SENSOR:
roleFloor = 1;
break;
default:
break;
}
lastRequiredHop = std::max(suggested, roleFloor);
}
logStatusReport(didHourlyUpdate);
return RUN_INTERVAL_MS;
}
#endif