Track papers across labs, topics, and trends.
Search papers, labs, and topics across Lattice.
This paper introduces a lightweight ledger protocol, Contextual Chain, designed for mobile/IoT networks with frequent partitions, using contextual authentication based on local branch scores and inconsistency-driven quarantine. The study evaluates the protocol's performance under controlled partitions and noisy network conditions using a discrete-event simulator. The key finding is that increased synchronization significantly improves both final agreement probability and recovery time after partition rejoin, suggesting that information availability is the primary limitation in noisy partition/rejoin dynamics.
Naive quarantine strategies don't cut it in noisy, partitioned IoT networks; aggressive synchronization is the real key to ledger agreement and rapid recovery.
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.