elara-time

Time convergence engine for the ELARA Protocol - featuring dual clock system, reality windows, and temporal prediction algorithms.

Features

Dual Clock System: Perceptual time (smooth UX) + State time (network consensus)
Reality Windows: Temporal boundaries for event processing
Horizon Adaptation: Dynamic adjustment based on network conditions
Non-Destructive Correction: Time bending without timeline breaks
Peer Time Modeling: Distributed time synchronization

Quick Start

use elara_time::{TimeEngine, PerceptualClock, StateClock};

// Create time engine
let mut engine = TimeEngine::new(node_id);

// Get current times
let perceptual = engine.perceptual_time();
let state = engine.state_time();

// Process network time update
engine.update_peer_time(peer_id, network_time, rtt_estimate)?;

// Adapt horizons based on network quality
engine.adapt_horizons(network_quality);

Dual Clock System

Perceptual Clock (τp)

Purpose: User experience smoothness
Properties: Monotonic, local, smooth interpolation
Use Case: Media playback, UI updates

State Clock (τs)

Purpose: Network consensus
Properties: Correctable, distributed, eventual consistency
Use Case: Event ordering, state reconciliation

Reality Window

Past ←──────────────────────────────────────────→ Future
      │                    │                    │
      τs - Hc              τs                   τs + Hp
      │                    │                    │
      └── Correction ──────┴──── Prediction ────┘
          Horizon                 Horizon

Correction Horizon (Hc): How far back we can correct
Prediction Horizon (Hp): How far forward we can predict
Dynamic Adjustment: Based on network jitter and stability

Network Time Model

pub struct PeerTimeModel {
    pub offset: Duration,        // Clock offset from peer
    pub round_trip_time: Duration,
    pub confidence: f64,         // 0.0 to 1.0
    pub stability_score: f64,    // Network stability metric
}

Horizon Adaptation

The engine automatically adjusts horizons based on network conditions:

Good Network → Tight Horizons → Sharp Reality
Bad Network  → Wide Horizons  → Flexible Reality

License

Licensed under either of:

Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

elara-time 0.1.0