PANDAS: Peer-to-peer, Adaptive Networking Allowing Data Availability Sampling within Ethereum Consensus Timebounds

Pigaglio, Matthieu;Ascigil, Onur;Król, Michał;Rene, Sergi;Riviere, Etienne;et.al.
(2025) 26th ACM/IFIP International Middleware Conference — Location: Nashville, USA (15.December.2025)

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Abstract
Layer-2 protocols such as rollups can help address Ethereum’s throughput limits. An efficient data availability layer is key for layer-2 support in Ethereum, but broadcast methods do not scale. A promising approach is the selective distribution of layer-2 data and its verification by data availability sampling (DAS). Integrating DAS with Ethereum consensus is, however, a challenge, as data must be shared and sampled within 4 seconds of each consensus slot. We propose PANDAS, a practical approach to integrating DAS with Ethereum without modifying Ethereum’s core protocols. PANDAS disseminates layer-2 data and samples its availability using lightweight, direct exchanges. Its design accounts for message loss, node failures, and unresponsive participants. Our evaluation in a 1,000-node cluster and simulations for up to 20,000 peers show that PANDAS allows layer-2 data dissemination and sampling under planetary-scale latencies within the 4-second deadline.
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Pigaglio, M., Ascigil, O., Król, M., Rene, S., Lange, F., Peeroo, K., Sadre, R., Stankovic, V., & Riviere, E. (2025). PANDAS: Peer-to-peer, Adaptive Networking Allowing Data Availability Sampling within Ethereum Consensus Timebounds. Proceedings of the 26th ACM/IFIP International Middleware Conference. Published. 26th ACM/IFIP International Middleware Conference, Nashville, USA. https://hdl.handle.net/2078.5/269734