面向地球观测数据访问的以网络为中心的本地部署架构设计与实证评估
Design and Empirical Evaluation of a Network-Centric, On-Premises Architecture for Earth Observation Data Access
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中文总结 AI 辅助
本文针对大西洋盆地机构的EO数据访问需求，设计并在AIR数据中心部署以网络为中心的本地部署架构，通过隔离网络带宽变量的实验明确其对存储吞吐量的约束阈值，为相关设施建设提供依据。
中文摘要 AI 辅助
地球观测（EO）项目产生的数据量已超出多数机构网络的传输与存储能力。公共云平台可为资源充足的机构解决该问题，但大西洋盆地的各机构面临连通性、主权及资金方面的限制，使得本地部署基础设施成为唯一可行路径。云原生数据格式支持高效的部分读取操作，但其性能取决于底层网络结构的带宽，而这种依赖关系极少被单独测量。本文提出一种可复制的、以网络为中心的本地部署EO数据访问架构，并在其首个运营部署点——大西洋云创始节点AIR数据中心进行评估。该系统由100 GbE结构上的MinIO对象存储集群、PostGIS元数据目录及OGC API-EDR访问层组成。我们在持续并行负载下对该结构进行特性分析，评估EO代表性工作负载的对象存储吞吐量，并在相同硬件上将实测性能与受限基线进行对比，将网络带宽作为唯一变量进行隔离。与合作机构开展的多站点复制基准测试，对该模型所依赖的联邦原语进行了特性分析。对于批量EO数据访问，网络带宽是存储吞吐量的主要约束，直至达到某一阈值；超过该阈值后，决定系统可利用带宽的是端点内存拓扑而非容量。对于该硬件类别，该阈值高于每服务器10 Gbps。低于该阈值时，仅网络容量决定设施的交付能力；高于该阈值时，进一步网络投资的回报取决于端点内存配置，后者可推迟至后续采购。
英文摘要
Earth observation (EO) programmes generate data at volumes that exceed the transfer and storage capacity of most institutional networks. Public cloud platforms address this for well-resourced organisations, but institutions across the Atlantic basin face constraints in connectivity, sovereignty and funding that make on-premises infrastructure the only viable path. Cloud-native data formats enable efficient partial reads, yet their performance depends on the bandwidth of the underlying network fabric, a dependency rarely measured in isolation. This paper presents a replicable, network-centric architecture for on-premises EO data access, evaluated at its first operational deployment: the AIR Data Centre, founding node of the Atlantic Cloud. The system comprises a MinIO object storage cluster on a 100 GbE fabric, a PostGIS metadata catalogue and an OGC API-EDR access layer. We characterise the fabric under sustained parallel load, evaluate object storage throughput for EO-representative workloads, and compare measured performance against throttled baselines on identical hardware, isolating network bandwidth as the sole variable. Multi-site replication benchmarks with partner institutions characterise the federation primitive the model depends on. Network bandwidth is the dominant constraint on storage throughput for bulk EO data access up to a threshold; beyond it, endpoint memory topology rather than capacity governs how much bandwidth a system can use. For this hardware class that threshold lies above 10 Gbps per server. Below it, network capacity alone sets what the facility can deliver; above it, the return on further network investment depends on endpoint memory provisioning, which can be deferred and bought later.
