Dynamic Blob Targets for Better Blob Pricing

2024-10-21 14:18:50 Primitive Reading

From ethresear.ch by keyneom

Abstract

This proposal introduces a dynamic pricing mechanism for blobs in Ethereum, using a PID (Proportional-Integral-Derivative) controller to adjust the target number of blobs. The goal is to maintain baseline security and assumes Data Availability Sampling (DAS) while optimizing blob usage and burn rates, ensuring economic stability and predictability for network participants.

Key Concepts

PID-Controlled Blob Target: Adjust the target number of blobs based on network usage over time.
Bounded Pricing Mechanism: Implement different pricing behaviors within and outside target bounds.
Existing Pricing Mechanism at Limits: Use existing blob pricing mechanisms at the bounds.
Burn Rate Optimization: Balance per-blob pricing with overall burn amounts.

Detailed Mechanism

Blob Target Adjustment

-A PID controller algorithm adjusts the target number of blobs based on consistent deviations from the current target.
-The target blob count floats between predetermined lower and upper bounds, the upper bound is set based on security considerations and the lower bound is assumed to be 1.

Pricing Mechanism

Within Target Bounds:-Price adjusts linearly as actual blob count varies from the target.-Increases when above target, decreases when below.
-Price adjusts linearly as actual blob count varies from the target.
-Increases when above target, decreases when below.
Outside Target Bounds:-Existing blob pricing mechanisms take over, causing exponential price changes.-This continues until actual blob count returns within the target bounds.
-Existing blob pricing mechanisms take over, causing exponential price changes.
-This continues until actual blob count returns within the target bounds.
Blob Target Adjustment Effects:-When target increases: Price per blob decreases, but overall burn amount increases.-When target decreases: Price per blob increases, but overall burn amount decreases.
-When target increases: Price per blob decreases, but overall burn amount increases.
-When target decreases: Price per blob increases, but overall burn amount decreases.

Security and Economic Considerations

-Upper bound for blob target is determined by validator count and DAS security requirements assuming a given bandwidth per validator (i.e. we know in advance when validators are withdrawing and it is rate limited as well so we should be safe and able to account for those with enough time to start adjusting the upper blob target limit if needed). We can assume 33% or something similar of validators online in determine how many samples can be completed, etc. to determine a conservative upper limit.

Disclaimer: This specification is preliminary and is subject to change at any time without notice. Amazon Finance assumes no responsibility for any errors contained herein.