Delay Analysis of EIP-4844

TL;DR

This paper addresses the delay dynamics of blob-carrying transactions under Proto-Danksharding (EIP-4844) and models BTX service as an $\mathrm{M/D}^B/1$ queue. It derives the steady-state distribution using an embedded Markov chain at departure instants and supplementary variables, leveraging the PASTA property to relate time-averages to arrival views. Empirical data show current blob usage yields near-zero queueing delays, while the analysis indicates that reaching the sustainable data-target may require up to about $2\times$ the current demand, with larger, less frequent BTXs incurring higher delays. The work informs capacity planning and pricing for rollup data markets and points to future extensions, such as multi-class BTX traffic and dynamic base-fee integration.

Abstract

Proto-Danksharding, proposed in Ethereum Improvement Proposal 4844 (EIP-4844), aims to incrementally improve the scalability of the Ethereum blockchain by introducing a new type of transaction known as blob-carrying transactions. These transactions incorporate binary large objects (blobs) of data that are stored off-chain but referenced and verified on-chain to ensure data availability. By decoupling data availability from transaction execution, Proto-Danksharding alleviates network congestion and reduces gas fees, laying the groundwork for future, more advanced sharding solutions. This letter provides an analytical model to derive the delay for these new transactions. We model the system as an $\mathrm{M/D}^B/1$ queue which we then find its steady state distribution through embedding a Markov chain and use of supplementary variable method. We show that transactions with more blobs but less frequent impose higher delays on the system compared to lower blobs but more frequent.

Figures (2)

• Figure 1: Average delay of BTXs in a shard for different loads.
• Figure 2: Average delay of BTXs in a shard with different blob capacities.