Data Availability Sampling

Definition ∞ Data availability sampling is a technique used in blockchain scalability solutions, particularly rollups, to ensure that transaction data is accessible without requiring every node to download the entire dataset. It allows nodes to probabilistically verify that data has been published, significantly reducing the resource burden on validators. This mechanism is vital for the security and decentralization of layer-2 networks.
Context ∞ The current discussion around data availability sampling is primarily centered on its implementation in optimistic and zero-knowledge rollups, aiming to enhance their security guarantees and decentralization. Key debates involve optimizing the sampling process to minimize overhead while maintaining robust assurances of data availability for all participants.

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→Recursive Folding

→Constant Time Verification

→Rollup Data Integrity

HyperCommit Achieves Constant-Time Verifiable Data Availability Sampling

A novel polynomial commitment scheme enables light clients to verify massive data availability with constant-time cryptographic proofs, securing modular scaling.

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→Decentralized Data Integrity

→Cryptographic Primitive

→Non-Interactive Proofs

Universal Vector Commitments Achieve Constant-Time Data Availability Sampling

A novel Universal Vector Commitment scheme achieves constant-time data availability sampling, fundamentally solving the verifier's dilemma and enabling infinite L2 scalability.

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→Polynomial Commitment

→Cryptoeconomic Security

→Constant Verification Time

Sublinear Vector Commitments Enable Constant-Time Verification for Scalable Systems

A new vector commitment scheme achieves constant verification time with logarithmic proof size, fundamentally enabling efficient stateless clients and scalable data availability.

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→Verifiable Computation

→Scalable Verification

→Subspace Codes

Subspace Codes Enable Logarithmic Proof Size Constant Verification Time Commitment

A novel polynomial commitment scheme using subspace codes achieves logarithmic proof size and constant verification, enhancing rollup efficiency.

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→Polynomial Commitments

→Scalability Solution

→Modular Blockchain

FRIDA: FRI-based Data Availability Sampling without Trusted Setup

Leverages a novel property of the FRI proof system to construct a trustless, efficient data availability sampling scheme for modular blockchains.

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→Modular Blockchain Architecture

→Data Availability Sampling

→Light Client Security

Probabilistic Sampling Verifies Data Availability Securing Modular Blockchain Scaling

Data Availability Sampling leverages erasure coding to enable light nodes to probabilistically verify block data, fundamentally solving the L2 scaling data bottleneck.

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→Reduced Storage Requirements

→Erasure Coding Efficiency

→Random Linear Network Coding

Decoupling Coding and Commitment for Superior Data Availability Sampling

This new modular paradigm uses Random Linear Network Coding on uncoded data, yielding dramatically stronger data availability assurances for light nodes.

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→Distributed Systems

→Sharding

→Scalable Verification

Vector Commitments Enable Modular Blockchain Scalability and Asynchronous Security

A new Probabilistically Verifiable Vector Commitment scheme secures Data Availability Sampling, decoupling execution from data and enabling massive asynchronous scalability.