Link to presenationons: Intro and Sampling Horizons - Leo FullDAS Ingredients - Csaba Full DAS, as we discuss here (after PeerDAS session) next logical step after PeerDAS aiming for maximum scalability targeting 32 MB blob space using 2D erasure code (improved diffusion, repair, and sampling)

Part 1 (November) Armiarma Improvements (Mikel & Leon) Improvements/refactor of the crawler to:[x] Hosting typeCloud Residential Business College Cellular Government [x] OS of the Beacon Nodes

Dissemination of rows and columns to validators Baseline assumptions (this is how the current model works, but almost none of these are cast in stone): Block data is encoded using 2D RS coding from 256x256 to 512x512 Dissemination is done using GossipSub channels per rows and per column Validators instruct their beacons nodes to subscribe to the channels corresponding to selected rows and columns Beacon nodes subscribe to the union of channels of all their validators Reconstruction is done at the beacon node (not validator) level Reconstruction is done by beacon nodes on-the-fly, injecting missing and reconstructed blocks in their respective channels when possible Attestations are done based on the information received this way, no further sampling is performed