Earthquake-Resistant Distributed Database Replication Models
Keywords:
Distributed database replication; earthquake resilience; CAP theorem; Raft consensus; Paxos; quorum-based replication; write-ahead log; seismic zone classification; network resilience; disaster recovery; geo-distributed systems; data center placement.Abstract
to seismic events, which impose simultaneous network partitions, power disruptions, and
hardware failures across geographically correlated zones. This paper synthesizes current
research on earthquake-resistant distributed database replication models, examining
the intersection of consensus-based replication protocols, seismic zone-aware network
design, and disaster-resilient cloud infrastructure deployment. The Brewer Consistency-
Availability-Partition (CAP) theorem and its PACELC extension are evaluated as theoretical
foundations for protocol selection under seismic-induced partition scenarios. Quorumbased
replication mechanisms, including the Quorum-Log approach, are analyzed against
classical Raft and Paxos implementations, demonstrating throughput improvements of
up to 42% and recovery time reductions of approximately 82% relative to asynchronous
replication baselines. Seismic zone classification frameworks drawn from optical network
resilience research are adapted to inform data-center placement strategies, revealing that
Zone IV and Zone V environments require a minimum of five geographically distributed
replica nodes to achieve 99.99% availability. Network resilience techniques—including
Shared Risk Link Group (SRLG) diversity and integer linear programming (ILP)-based
routing—are evaluated for their applicability to database replication transport layers.
Write-Ahead Log (WAL) parallelization achieves replay throughputs of 520 MB/s, reducing
post-earthquake recovery time objectives to as low as three seconds. The paper concludes
by proposing a multi-layer reference architecture integrating seismic awareness, consensuslayer
adaptability, and network-level redundancy to achieve robust data continuity under
extreme geophysical events.
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