PeerDAS bandwidth requirements confuse solo stakers

PeerDAS divides 128kB blobs into 128 columns of 2KB each to reduce node load. This mechanism allows validators to verify data availability by sampling small portions instead of downloading entire blobs. The Fusaka upgrade, which developers scheduled for December 3, implements this through EIP-7594. This change changes how different node types handle network traffic.

The network defines three distinct node types with different resource needs. Supernodes, or backbone nodes, hold a combined balance of at least 4,096 ETH. These nodes must subscribe to all 128 column subnets and custody data for 4,096 epochs, roughly 18 days. Supernodes face high processing and p2p loads. In devnet testing for BPO2 with 14 blobs, supernodes saw receive spikes at 400 Mb/s and transmit peaks at 300 Mb/s. Validating nodes with a single validator subscribe to 8 or more random column subnets. These stakers process 1/8th or more of the data a supernode handles. Devnet data for 10 blobs shows validating nodes using 15-20 Mb/s for both receiving and transmitting data. Full nodes participate in 4 column subnets and process 1/32nd of the data a supernode handles. Full nodes used 4-8 Mb/s for both receive and transmit at 10 blobs.

The distinction between these roles causes confusion regarding block reconstruction. A validator providing blobs over the Beacon API must function as a supernode because they require all columns to reconstruct the blob. Regular validating nodes do not need this capacity. This technical requirement creates a gap between the simple task of sampling and the heavy task of full data custody.

Misunderstanding validator duties and bandwidth

Solo stakers often mistake their sampling duties for the heavy lifting of full data reconstruction. PeerDAS allows a validator to be confident blobs exist by only fetching small random chunks. This sampling does not require the node to download every byte of data availability. However, the bandwidth required to build and publish blocks increases because of erasure coding. Post-Fusaka blobs are 256kB, combining 128kB for the blob and 128kB for erasure coding.

The increase in upload bandwidth requirements for local block building is significant. For a block with 10 blobs, theoretical calculations show the upload bandwidth for a local block builder exceeds the 50 MB limit set by EIP-7870. This problem persists even though the network uses distributed blob building and MEV relays to help. When a proposer builds a block locally, they publish the block and the 128 columns. Other nodes check their mempool for the blobs referenced in the block to skip downloads. If they find the blobs, they avoid downloading them via gossipsub.

The 68% supernode bandwidth requirement refers to the massive load these backbone nodes carry to maintain the network. Developers designed the system so that if you stake more ETH, you handle more blobs. This maintains decentralization by preventing the exclusion of home stakers. Even so, the massive discrepancy between a supernode’s 300-400 Mb/s peaks and a solo staker’s 15-25 Mb/s usage shows that the network relies on sophisticated entities for heavy data handling. If a solo staker assumes they must perform the same duties as a supernode to remain secure, they will over-provision hardware unnecessarily.

Solo staker profitability and market shifts

Changes to the consensus issuance schedule impact solo stakers more than users of liquid staking or centralized exchanges. Solo stakers show higher sensitivity to variations in staking rewards. This sensitivity stems from fixed costs and competitive pressures. Other staking methods access superior MEV and DeFi yields, which lessens their reaction to issuance changes.

A reduction in issuance can crowd out solo stakers. This happens because solo staking has fixed costs that do not scale like the costs for centralized entities. If rewards drop, the profitability of solo staking falls disproportionately. This may drive stakers toward decentralized liquidity staking providers (dSSPs) that provide additional DeFi returns.

The market is segmented by user preference. Institutional stakers focus on security and regulatory compliance. Retail investors often prefer the convenience and brand trust of platforms like Coinbase. Large ETH holders focus on price appreciation and use liquid staking. Because solo stakers represent a small segment, any policy that reduces issuance or changes the reward structure can accelerate centralization. If solo stakers exit the market due to lower profitability, centralized entities increase their market share. This creates a cycle where validator power concentrates in fewer hands.

Scaling via blob parameter only forks

The network will increase blob capacity in stages using Blob Parameter Only (BPO) forks. These forks allow developers to change the number of blobs per block without a full hard fork. This flexibility uses EIP-7892 to adjust knobs in client configurations. The three knobs are the blob target, the blob max, and the base fee update fraction.

The first BPO1 fork aims to raise the maximum blob count from 9 to 15. The second BPO2 fork targets a ceiling of 21 blobs. These changes follow the logic that core developers will monitor production environments before making more aggressive expansions.

The implementation of EIP-7918 adds a floor to blob fees. This floor ties the blob fee to execution gas to prevent fees from falling to zero when demand is low. This policy aims to stabilize fee dynamics and keep L2 costs predictable. A backtest suggests that these rules would have kept blob prices higher on approximately 93% of days since the Dencun upgrade. This redirecting of value helps stakers by keeping fees from collapsing.

The rollout of BPO forks is a cautious process. Core developers plan to watch the effects of BPO1 and BPO2 before proceeding to BPO3 or BPO4. This graduated approach reflects the experimental nature of PeerDAS. The developers recognize that PeerDAS introduces new blockchain architecture territory. If the network experiences instability, developers can use these targeted forks to adjust parameters without the coordination overhead of a major upgrade.

Will the increased bandwidth load for supernodes eventually force a redefinition of the validator role?