Sampling efficiency measures how effectively a system can verify the integrity of a large dataset by examining only a small, representative portion of it. In blockchain contexts, this relates to the ability of light clients to confirm block validity without downloading all block data. High sampling efficiency reduces resource requirements for network participants.
Context
Sampling efficiency is a critical consideration for scaling solutions like sharding and data availability layers, where nodes may only process a subset of the total chain data. The current focus involves designing cryptographic schemes that guarantee data availability and integrity with minimal sampling requirements. Improved sampling efficiency is essential for reducing the computational burden on individual nodes, thus promoting greater decentralization and accessibility for digital asset users.
A new k-dimensional polynomial commitment scheme drastically reduces data availability overhead, unlocking massive throughput for decentralized rollups.
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