Contextual Chain: Single-State Ledger Design for Mobile/IoT Networks with Frequent Partitions

TL;DR

This paper introduces a lightweight, context-aware ledger protocol tailored for mobile and IoT networks with frequent partitions, emphasizing adaptive synchronization and local context validation.

Contribution

The paper proposes a novel ledger design using contextual authentication and adaptive synchronization to improve recovery in partitioned, noisy networks.

Findings

Quarantine alone does not significantly improve agreement under noisy conditions.

Increased synchronization enhances agreement probability and reduces recovery time.

Scaling experiments show that parameters effective at small scale may not work at larger scales.

Abstract

We study a lightweight ledger protocol for intermittent and noisy networks, motivated by IoT and mobile settings in which partitions are common and full-history verification is impractical. Our design centers on an \emph{operational} notion of \textbf{contextual authentication}: each node decides whether a chain extension is acceptable in its current local context, using checkpoint-first fork choice, a local branch score derived from recent proposer behavior, and an inconsistency-driven \emph{quarantine} signal. To improve recovery after partitions, we combine this acceptance rule with \textbf{adaptive synchronization}, which increases gossip effort only when inconsistency becomes prevalent. We evaluate the protocol with a discrete-event simulator under controlled partitions and two network regimes (clean and noisy). Across 500 seeds at $N=20$, the main result is that quarantine alone does not materially improve agreement or recovery under noisy conditions, whereas increased synchronization (\texttt{Gossip\_only} and \texttt{Both}) substantially improves both final agreement probability and recovery-time tails after partition rejoin. Longer-horizon experiments show that low-synchronization failures are not removed simply by waiting longer, and scaling experiments at $N=50$ and $N=100$ show that parameters that work at small scale do not automatically generalize. These results indicate that, under noisy partition/rejoin dynamics, recovery in the current design is limited primarily by information availability, making synchronization policy a first-class design problem.