📊Fee Market Dynamics

Dynamic Pricing Model

The cost of executing web transactions on the network is designed to be dynamic, reflecting the current supply and demand for resources at the point of execution. This ensures that the pricing is responsive to the network's operational conditions and resource availability.

Gas Fee Calculation

The gas fees, denoted as 𝐺G, are influenced by multiple factors, each contributing to the final cost:

• Geography (g): The location of the target node affects fees due to data transit distances.

• Reputation (r): The historical performance and reliability of the node adjust fees.

• Traffic Type (t): The nature of the data (e.g. sensitivity, volume) affects the cost.

• Bandwidth (b): The amount of data processed influences the fees.

• Congestion (c): Network traffic at the time of the transaction adjusts the cost based on activity levels.

The formula used is:

$G=\left(k_{g} \cdot g+k_{r} \cdot r+k_{t} \cdot t+k_{b} \cdot b\right) \cdot\left(1+k_{c} \cdot c\right)$

Here, $k_{g}$, $k_{r}$, $k_{t}$, $k_{b}$, $k_{r}$, $k_{t}$, $k_{b}$ and $k_{c}$ are coefficients that scale the impact of each parameter on the gas fees, allowing for adjustments based on real-time network data.

Node Reputation Scoring

Purpose and Implementation Nodes are scored based on their reliability in handling web transactions. This scoring system is critical for network trust and operational efficiency.

Criteria for Scoring

• Completeness (C): Measures whether the node provides complete datasets.

• Consistency (N): Assesses the uniformity of data across transactions.

• Timeliness (T): Checks how promptly data is provided.

• Availability (A): Evaluates the reliability of the node in providing data when needed.

Scoring Formula

$R=w_{C} \cdot C+w_{N} \cdot N+w_{T} \cdot T+w_{A} \cdot A$

• $w_{C}$, $w_{N}$, $w_{T}$, $w_{A}$​ are weights assigned to each scoring criterion, ensuring each aspect of performance is appropriately valued. The sum of these weights equals 1.

Dynamic Allocation of Weights

The allocation of weights is adjusted based on performance analytics:

• Weights are dynamically adjusted according to the variability observed in each criterion across the network.

• This allows the network to prioritize areas needing improvement and align incentives for node operators accordingly.

This system ensures that node operators are fairly compensated for their contributions to the network while encouraging continuous improvement in data handling and reliability.