[work] - Fsdss 908

Modern data‑intensive workloads (e.g., AI model training, real‑time analytics, and large‑scale scientific simulations) demand storage systems that simultaneously deliver high throughput, low latency, strong consistency, and robust fault tolerance. Existing distributed storage solutions either sacrifice consistency for availability, impose prohibitive coordination overhead, or lack elasticity across heterogeneous cloud‑edge environments. We present , a novel F ault‑tolerant, S calable, D istributed S torage S ystem that reconciles these conflicting goals through three key innovations: (1) a Hybrid Log‑Structured Merge (H‑LSM) engine that decouples write amplification from read latency, (2) a Multi‑Region Consensus (MRC) protocol that reduces cross‑region coordination to a single round‑trip while preserving linearizability, and (3) an Adaptive Placement Scheduler (APS) that dynamically migrates data shards based on real‑time workload and failure‑domain signals. Extensive micro‑benchmarks and end‑to‑end evaluations on a 128‑node cluster spanning three public clouds (AWS, Azure, GCP) and two edge sites demonstrate that FSDSS‑908 achieves 3.2× higher sustained write throughput , 2.1× lower 99th‑percentile read latency , and 99.999% durability under a 2‑failure simultaneous zone outage, outperforming state‑of‑the‑art systems (Ceph, DynamoDB, CockroachDB) by 30‑55% on the YCSB and TPC‑DS workloads. We release the prototype under an Apache‑2.0 license to foster reproducibility and further research.

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