"East Data West Compute" & Community Data Centers: Strategic Positioning as Edge Nodes

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In the grand architecture of the nationally integrated computing power network, community data centers are not bystanders — they are the computing anchors closest to end users.

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The Basic Architecture of "East Data West Compute"

The "East Data West Compute" (东数西算) project is a nationally integrated big data center collaborative innovation system advanced by the National Development and Reform Commission (NDRC) and other departments. Its fundamental logic:

- East (Beijing-Tianjin-Hebei, Yangtze River Delta, Greater Bay Area, Chengdu-Chongqing): Dense user populations, constrained land and energy → handles low-latency "hot data" (real-time inference, interactive services)

- West (Inner Mongolia, Guizhou, Gansu, Ningxia): Abundant energy, favorable climate → handles high-throughput "cold data" (AI training, batch processing, offline analysis)

Eight national hub nodes and ten national data center clusters have been broadly delineated. But this blueprint has one role that remains insufficiently discussed: community data centers as edge nodes in city computing networks.

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The Precise Positioning of Community Data Centers

Not a Hub — An Edge

Community data centers are not competitors to national hub nodes — they are their terminal extensions. They do not handle petabyte-scale offline training tasks, but millisecond-level local inference requests — the computing layer closest to end users in the "East Data West Compute" network.

Computing Network Tier	Functional Positioning	Community Data Center's Role
National Hub Nodes (Inner Mongolia, Guizhou, etc.)	Large-scale AI training · Cold data storage · Batch processing	Not involved — this is the domain of hyperscale DCs
Provincial / City Computing Networks	Regional computing scheduling · City-level services	Serves as distributed access points for city computing networks
Edge Inference Nodes	Low-latency inference · Real-time interaction · Local services	⭐ This is precisely the core battleground for community data centers

Technical Rationale

ODCC (Open Data Center Committee) has recently released the Cloud-Edge Collaborative AI Network Technology White Paper (ODCC2504001), explicitly identifying edge computing cluster networks as a key technical direction for AI inference. The China Academy of Information and Communications Technology (CAICT) launched the development of "Computing Power Cluster Token Evaluation Series Standards" in June 2026, further signaling that computing power is transitioning from infrastructure-level measurement to service-oriented (tokenized) measurement — meaning the value of edge computing nodes close to users will further increase.

The physical positioning of community data centers — embedded in urban communities, close to end users — gives them irreplaceable advantages in the following scenarios:

- Low-latency AI inference: Autonomous driving assistance, real-time translation, intelligent security — these scenarios require < 5ms response latency, achievable only by edge nodes

- Local data compliance: Medical imaging analysis, financial risk control — certain data is legally prohibited from leaving the province or city; community DCs provide localized processing capability

- Community smart services: Intelligent building management, community energy scheduling, public safety alerts — directly serving the digital needs of the host community

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Alignment with National Computing Power Network Planning

Policy Document	Community DC Alignment Point
NDRC Implementation Opinions on Building a Nationally Integrated Computing Power Network (2023)	City computing networks extending to the edge — community DCs as distributed access nodes
MIIT Three-Year Action Plan for New Data Center Development	Edge data center classification — community DCs apply edge-class standards
ODCC Edge Computing Working Group White Papers	Cloud-edge collaborative AI networks — community DCs as edge inference nodes
CAICT Computing Power Token Evaluation Framework	Computing power servitization — community DCs provide low-latency local computing services

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The Complementary Relationship Between Community DCs and National Hub Nodes

Community data centers and national hub nodes do not compete — they are complementary computing infrastructure layers:

``

National Hub Nodes (West)

↕ Batch training results distributed downward

City Computing Networks (Provincial)

↕ Model distribution · Computing scheduling

Community Data Centers (Edge) ← Core domain of this framework

↕ Real-time inference · Local services

End Users

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What This Means for Communities

This positioning means community data centers are not merely computing infrastructure — they are a community digital foundation:

- Providing local enterprises with affordable, low-latency AI inference services

- Serving as smart city terminal nodes, participating in urban governance digitalization

- Through carbon accounting and green electricity procurement, occupying a legitimate position within the energy consumption indicator system of "East Data West Compute"

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