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

Fuente: arXiv
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Hauptverfasser: Pigaglio, Matthieu, Ascigil, Onur, Król, Michał, Rene, Sergi, Lange, Felix, Peeroo, Kaleem, Sadre, Ramin, Stankovic, Vladimir, Rivière, Etienne
Format: Preprint
Veröffentlicht: 2025
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author Pigaglio, Matthieu
Ascigil, Onur
Król, Michał
Rene, Sergi
Lange, Felix
Peeroo, Kaleem
Sadre, Ramin
Stankovic, Vladimir
Rivière, Etienne
author_facet Pigaglio, Matthieu
Ascigil, Onur
Król, Michał
Rene, Sergi
Lange, Felix
Peeroo, Kaleem
Sadre, Ramin
Stankovic, Vladimir
Rivière, Etienne
contents Layer-2 protocols can assist Ethereum's limited throughput, but globally broadcasting layer-2 data limits their scalability. The Danksharding evolution of Ethereum aims to support the selective distribution of layer-2 data, whose availability in the network is verified using randomized data availability sampling (DAS). Integrating DAS into Ethereum's consensus process is challenging, as pieces of layer-2 data must be disseminated and sampled within four seconds of the beginning of each consensus slot. No existing solution can support dissemination and sampling under such strict time bounds. We propose PANDAS, a practical approach to integrate DAS with Ethereum under Danksharding's requirements without modifying its protocols for consensus and node discovery. PANDAS disseminates layer-2 data and samples its availability using lightweight, direct exchanges. Its design accounts for message loss, node failures, and unresponsive participants while anticipating the need to scale out the Ethereum network. Our evaluation of PANDAS's prototype in a 1,000-node cluster and simulations for up to 20,000 peers shows that it allows layer-2 data dissemination and sampling under planetary-scale latencies within the 4-second deadline.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00824
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PANDAS: Peer-to-peer, Adaptive Networking for Data Availability Sampling within Ethereum Consensus Timebounds
Pigaglio, Matthieu
Ascigil, Onur
Król, Michał
Rene, Sergi
Lange, Felix
Peeroo, Kaleem
Sadre, Ramin
Stankovic, Vladimir
Rivière, Etienne
Distributed, Parallel, and Cluster Computing
Networking and Internet Architecture
Performance
Layer-2 protocols can assist Ethereum's limited throughput, but globally broadcasting layer-2 data limits their scalability. The Danksharding evolution of Ethereum aims to support the selective distribution of layer-2 data, whose availability in the network is verified using randomized data availability sampling (DAS). Integrating DAS into Ethereum's consensus process is challenging, as pieces of layer-2 data must be disseminated and sampled within four seconds of the beginning of each consensus slot. No existing solution can support dissemination and sampling under such strict time bounds. We propose PANDAS, a practical approach to integrate DAS with Ethereum under Danksharding's requirements without modifying its protocols for consensus and node discovery. PANDAS disseminates layer-2 data and samples its availability using lightweight, direct exchanges. Its design accounts for message loss, node failures, and unresponsive participants while anticipating the need to scale out the Ethereum network. Our evaluation of PANDAS's prototype in a 1,000-node cluster and simulations for up to 20,000 peers shows that it allows layer-2 data dissemination and sampling under planetary-scale latencies within the 4-second deadline.
title PANDAS: Peer-to-peer, Adaptive Networking for Data Availability Sampling within Ethereum Consensus Timebounds
topic Distributed, Parallel, and Cluster Computing
Networking and Internet Architecture
Performance
url https://arxiv.org/abs/2507.00824