Ethereum Proposes New Method to Cut Blob Data Processing Loads

Ethereum researchers are looking at a more efficient way to handle blob data. A new prototype suggests that by dividing recovery duties among nodes, the network can significantly lower the computing workload required to manage rollup data. In simulations with 1,000 nodes, this approach showed an 11 to 18 times reduction in the effort needed to reconstruct missing data.

Currently, the network relies on PeerDAS to ensure data availability, where nodes download only portions of data. High custody nodes are tasked with keeping enough information to rebuild missing pieces. The new proposal suggests assigning specific blobs to certain nodes first. This prevents multiple nodes from doing the exact same recovery work at the same time. Other nodes can simply receive the recovered data rather than performing the heavy lifting themselves.

While these results look positive, the design is still in the testing phase. It focuses on reducing CPU strain rather than changing transaction speeds or fees. Researchers note that this is a potential stepping stone toward a more complex system known as RowDAS, which aims for even greater network resilience. For now, the community is looking toward larger simulations and real world testing to see how this holds up outside of a controlled environment.