Data Availability Sampling

Why Data Availability Matters

Rollups inherit security from their host chain by posting all their transaction data to that chain. The host chain just stores it; anyone can later download it to reconstruct the rollup's state. But what if the rollup operator publishes a state root claiming a certain outcome — and withholds the data needed to verify it? Without the data, no one can detect fraud. This is the 'data availability problem.' The host chain must guarantee that posted data is actually available to anyone who wants to check.

The Trivial Solution and Why It Doesn't Scale

The trivial solution is: every full node downloads every block, including all rollup data. Done. But this caps how much data the chain can carry — it's bounded by what an ordinary node can download. To 10x or 100x the data capacity, you'd need to make full nodes much more powerful, hurting decentralisation. So a more clever approach is needed.

Data Availability Sampling (the Idea)

Data availability sampling lets light nodes sample tiny random pieces of each block. If the data is fully available, every sample succeeds. If even a small fraction is withheld, with high probability some sample will hit a missing piece and the node will detect it. With erasure coding (a technique borrowed from storage systems), missing a small amount of data means the whole thing is unreconstructable — so a withholder either has to publish almost everything or nothing.

• Problem: how do we know a block's data was actually published?
• Trivial solution: every node downloads everything — limits capacity
• DAS: light nodes sample random pieces and use math (erasure coding) to be sure
• Result: more total data can be posted without making every node bigger