Hyper-Converged Data Center Network: Architecture, Benefits, and Future Trends

This research report introduces the significance of data‑center networking for computational power, summarizes the factors influencing the evolution toward fully Ethernet‑based data centers, and describes the typical characteristics and value of hyper‑converged data‑center network architectures.

Data‑center processing comprises three resource zones: the storage zone (servers with HDD, SSD, or optical media providing storage, read/write, and backup via storage networks), the high‑performance computing zone (servers with minimal virtualization, equipped with CPU/GPU for HPC or AI training, interconnected by high‑performance compute networks), and the general‑purpose computing zone (servers using VMs or containers, connected through a unified application/network layer to serve external users).

The network acts as the central nervous system linking compute and storage throughout the data‑center lifecycle; its performance directly impacts overall computational efficiency (CE), defined as compute output per watt of IT power (FLOPS/W). Enhancing network capability can significantly improve CE, as demonstrated by ODCC2019 tests showing a >20% reduction in HPC task completion time and a corresponding 20% energy saving when using Ethernet‑integrated compute (RoCE) versus traditional RoCE networks.

In storage networks, adopting lossless Ethernet with NVMe‑over‑Fabric can boost IOPS by up to 87% compared with traditional Fibre Channel, further illustrating how network redesign elevates compute efficiency while supporting greener data‑center operation.

Full‑flash storage drives the RoCE ecosystem: SSDs provide ~100× performance gains over HDDs, but FC networks become bottlenecks in bandwidth and latency. NVMe‑over‑Fabric (including NVMe‑over‑RoCE) offers open, scalable, and AI‑enabled management advantages, positioning it as the next‑generation storage networking solution.

With AI workloads exposing PCIe bottlenecks, industry leaders such as Habana (Gaudi) and Huawei (Ascend 910) integrate RoCE Ethernet ports directly on AI chips, eliminating PCIe constraints and enabling massive, scalable inter‑node connectivity.

IPv6 large‑scale deployment further accelerates Ethernet adoption, providing abundant address space and enhanced security essential for the exploding IP demand of smart‑world data‑centers.

The hyper‑converged data‑center network architecture is defined by three core features: (1) lossless Ethernet that unifies storage, general, and high‑performance compute traffic on a single 0‑loss packet‑level stack; (2) lifecycle‑wide automated management using digital twins, big data, and AI for planning, construction, maintenance, and optimization; (3) service‑oriented capabilities exposing physical, logical, application, interconnect, security, and analytics services to support multi‑cloud and diverse industry scenarios.

Best practices include AI‑driven dynamic queue management to replace static watermarks, millisecond‑level fault notification and coordinated storage failover for sub‑second recovery, and plug‑and‑play storage provisioning that eliminates manual per‑node configuration.

Performance analysis highlights four latency components—dynamic queue delay, static forwarding delay, hop count, and ingress count—each optimized in next‑generation lossless Ethernet to meet HPC requirements.

Current data‑center network designs rely heavily on engineering experience, lacking unified theoretical guidance; traditional CLOS architectures prioritize universality at the expense of latency and cost, prompting research into new topologies and optimization methods.