Rollup Compression

Overview

Rollup compression encodes batches more compactly before their data or state differences are posted to a data-availability layer. It targets repeated addresses, signatures, field values, and other structures that need not be represented in full each time. Methods include field omission, dictionaries, delta encoding, signature aggregation, specialized transaction formats, and publishing state differences instead of complete states. The decoder and execution rules must reconstruct the information required to verify the batch unambiguously.

Compression lowers posting cost, often the dominant rollup expense, but increases implementation complexity. Operators must version formats carefully and preserve compatibility across upgrades. Analysts should compare effective bytes per transaction under realistic workloads because headline ratios depend on transaction mix, batching fullness, and the availability system used. Fulfillment and withdrawal policies should use the stage that matches the business risk. Payment applications using Rollup Compression should maintain separate states for local acceptance, batch publication, proof verification or challenge completion, bridge execution, and base-layer finality. Operational support needs monitoring for sequencer outages, delayed batches, proof failures, forced-inclusion paths, contract pauses, and upgrade events. Users should have a documented route to recover or exit when the preferred sequencer, prover, or interface is unavailable.

A transaction accepted by a sequencer has not necessarily been published, proven, finalized on the base layer, or made withdrawable. Rollup Compression should be described through its execution, sequencing, data-publication, proof or challenge, bridge, and settlement stages.

The security model for Rollup Compression includes sequencer control, proof or fault-resolution rules, data availability, bridge contracts, upgrade keys, and the base-layer verifier. A cryptographic proof can reduce execution trust while leaving censorship, data, governance, and contract risks.