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Propagation Rules Specification

Version: 0.1.0-draft

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Overview

This document specifies how signals route through the NTL network topology.

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Core Rules

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Rule 1: TTL Enforcement

A node MUST NOT propagate a signal with TTL = 0. Before propagating, the node MUST decrement the TTL by 1.

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Rule 2: Loop Prevention

A node MUST NOT propagate a signal if its own Node ID appears in the signal’s trace. This prevents infinite loops in cyclic topologies.

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Rule 3: Weight Floor

A node MUST NOT propagate a signal with weight below min_propagation_weight (default: 0.01). Signals that attenuate below this floor are effectively absorbed.

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Rule 4: Deduplication

A node MUST maintain a deduplication cache of recently seen signal IDs. If a signal ID is already in the cache, the signal MUST be silently dropped. The cache MUST retain entries for at least max_ttl * avg_propagation_time duration.

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Rule 5: Signature Verification

A node MUST verify the signal’s cryptographic signature before processing or propagating. Invalid signatures MUST result in the signal being dropped and the originating synapse’s weight being reduced.

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Propagation Scopes

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Flood (scope = 0)

The signal MUST be propagated to ALL active synapses (excluding the synapse it arrived on). Used for discovery and emergency signals. Constraints:
  • Flood signals SHOULD have low TTL (≤ 3) to prevent network saturation
  • Nodes MAY rate-limit flood propagation

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Weighted (scope = 1) — Default

The signal is propagated to synapses selected by the path scoring function, ordered by score descending. The number of synapses selected is bounded by max_propagation_fanout (default: 5).

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Targeted (scope = 2)

The signal is directed toward a specific destination node. The propagation engine selects the synapse most likely to reach the destination, based on topology knowledge and signal trace history. If the destination is a direct synapse, the signal MUST be sent directly. If not, the signal is forwarded to the synapse with the highest affinity for the destination’s region of the topology.

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Gradient (scope = 3)

The signal follows the gradient of type affinity — propagating toward nodes that have historically processed similar signal types. This creates emergent specialization pathways.

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Path Scoring Function

For Weighted and Gradient propagation, synapses are scored: 
score = (synapse.weight * W_weight)
      + (latency_score * W_latency)
      + (type_affinity * W_affinity)
      + (recency_score * W_recency)
Where:
  • latency_score = 1.0 / (1.0 + normalized_latency)
  • type_affinity = historical_success_rate_for_signal_type
  • recency_score = 1.0 / (1.0 + hours_since_last_active)
Default weights: W_weight = 0.4, W_latency = 0.2, W_affinity = 0.3, W_recency = 0.1

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Attenuation

When propagating a signal, the node MUST attenuate the signal’s weight: 
signal.weight *= synapse.attenuation_factor
The default attenuation factor is 0.9. Synapses MAY configure different attenuation factors.

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Trace Management

When a node propagates a signal:
  1. The node MUST append its Node ID to the signal’s trace
  2. The trace MUST NOT exceed 64 entries
  3. Nodes MAY truncate the oldest entries if the trace exceeds 64
For privacy-sensitive deployments, trace recording MAY be disabled. In this case, loop prevention relies solely on the deduplication cache.