Sedna: Sharding transactions in multiple concurrent proposer blockchains

TL;DR

<3-5 sentence high-level summary>

Abstract

Modern blockchains increasingly adopt multi-proposer (MCP) consensus to remove single-leader bottlenecks and improve censorship resistance. However, MCP alone does not resolve how users should disseminate transactions to proposers. Today, users either naively replicate full transactions to many proposers, sacrificing goodput and exposing payloads to MEV, or target few proposers and accept weak censorship and latency guarantees. This yields a practical trilemma among censorship resistance, low latency, and reasonable cost (in fees or system goodput). We present Sedna, a user-facing protocol that replaces naive transaction replication with verifiable, rateless coding. Users privately deliver addressed symbol bundles to subsets of proposers; execution follows a deterministic order once enough symbols are finalized to decode. We prove Sedna guarantees liveness and \emph{until-decode privacy}, significantly reducing MEV exposure. Analytically, the protocol approaches the information-theoretic lower bound for bandwidth overhead, yielding a 2-3x efficiency improvement over naive replication. Sedna requires no consensus modifications, enabling incremental deployment.

Figures (8)

• Figure 1: Bandwidth overhead factor as a function of payload size. The dotted line shows the information-theoretic lower bound $1/(1-c_e/n)$ from Theorem \ref{['thm:it_lower_bound']}, for $n = 256$, $c_e/n = 0.125$, $\delta = 10^{-9}$.
• Figure 2: Single-slot success probability versus fanout $m$ for naive replication, MDS coding, and rateless coding. Parameters: $n = 256$, $c_e/n = 0.125$, $\delta = 10^{-9}$, $S = 4096$ bytes.
• Figure 3: Effect of symbols per lane $s$ on rateless success probability. Increasing $s$ reduces the required number of honest lanes at the cost of larger bundle sizes. Parameters: $n = 256$, $c_e/n = 0.125$, $\delta = 10^{-9}$, $S = 32768$ bytes.
• Figure 4: Rateless coding overhead as a function of payload size for varying censorship ratios $c_e/n \in \{0.05, 0.10, 0.20, 0.30, 0.40\}$. Higher censorship tolerance requires proportionally more redundancy, but overhead decreases with payload size in all cases. Parameters: $n = 256$, $\delta = 10^{-9}$.
• Figure 5: Bandwidth overhead as a function of failure budget $\delta$. Lower failure probability (higher reliability) requires additional redundancy. Coded approaches scale more gracefully than naive replication as reliability requirements tighten. Parameters: $n = 256$, $c_e/n = 0.125$, $S = 4096$ bytes.

Theorems & Definitions (33)

• Definition 1: Verification relation
• Definition 2: Inclusion Height
• Definition 3: Monotone decoding for honest encodings
• Lemma 1: Validity and Deterministic Resolution
• proof
• Lemma 2: Header and Commitment Non-Malleability
• proof
• Lemma 3: Unique decode for honest senders
• proof
• Theorem 1: Order Determinism