# Temporal Reward Adjustment Mechanism

### Strategic Temporal Allocation Formula

To balance early adopter incentives with sustainable growth, Aledger implements a strategic temporal allocation formula that dynamically adjusts rewards based on participation timing, network growth, and total supply constraints.

```
User Reward = Base Reward × [α × Temporal Coefficient + β × Staking Ratio + γ × Network Saturation Factor]
```

Where:

* **Base Reward**: Standard reward calculated from asset package APY
* **α, β, γ**: Weight coefficients that sum to 1.0 (initially set to α=0.4, β=0.4, γ=0.2)
* **Temporal Coefficient**: Rewards early adoption (calculated below)
* **Staking Ratio**: Existing staking ratio coefficient from core tokenomics
* **Network Saturation Factor**: Adjusts for network capacity constraints

#### Temporal Coefficient Calculation

```
Temporal Coefficient = 1 + 0.5 × [1 - min(User Entry Position / Adoption Threshold, 1)²]
```

Where:

* **User Entry Position**: Sequential position of user registration (1 = first adopter)
* **Adoption Threshold**: Target number for early adoption phase (initially 1,000 packages)

This creates a non-linear decay curve where:

* First adopters receive up to 1.5× multiplier
* Middle adopters receive gradually decreasing benefits
* Late adopters (beyond threshold) receive the standard 1.0× multiplier

#### Network Saturation Factor

```
Network Saturation Factor = max(0, 1 - (Current Daily Emissions / Maximum Daily Emissions)^1.5)
```

This factor dynamically adjusts rewards as the network approaches maximum emission capacity:

* At low emission levels (<50% of capacity): Minimal impact (\~1.0×)
* At medium emission levels (50-80% of capacity): Moderate reduction
* At high emission levels (>80% of capacity): Significant reduction

### Parameter Governance

The Temporal Reward Adjustment parameters (α, β, γ, Adoption Threshold) are subject to governance voting by node operators, with the following constraints:

* Parameter adjustments limited to ±10% per quarter
* 14-day advance notice required for any parameter changes
* Super-majority (66%) of weighted node votes required for approval


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