  Scalability in blockchain remains a significant challenge, especially when
prioritizing decentralization and security. The Ethereum community has proposed
comprehensive data-sharding techniques to overcome storage, computational, and
network processing limitations. In this context, the propagation and
availability of large blocks become the subject of research to achieve scalable
data-sharding. This paper provides insights after exploring the usage of a
Kademlia-based DHT to enable Data Availability Sampling (DAS) in Ethereum. It
presents a DAS-DHT simulator to study this problem and validates the results of
the simulator with experiments in a real DHT network, IPFS. Our results help us
understand what parts of DAS can be achieved based on existing Kademlia DHT
solutions and which ones cannot. We discuss the limitations of DHT solutions
and discuss other alternatives.
