How Bilibili’s Smart Cabling Platform Boosts Data Center Efficiency

Background

Efficient operation of a data‑center depends on a well‑engineered interconnect network. Poor cabling management leads to longer delivery cycles, over‑length cables, chaotic layouts, difficult equipment installation, increased maintenance effort, and can even disrupt airflow, causing localized overheating. The rapid adoption of AI workloads raises bandwidth, latency, and power‑efficiency requirements, making digital cabling management a critical research direction.

Data Center Cabling Overview

Before a cabling scheme is designed, the business network requirements must be captured to define the topology. Two principal cabling strategies are used:

Structured cabling : employs standardized connection points and pathways, enabling easy re‑patching while keeping permanent links stable. It reduces cable count but requires more upfront design and installation effort.

Unstructured (point‑to‑point) cabling : forgoes predefined standards, offering lower installation cost and time at the expense of higher long‑term operational cost.

In practice, unstructured cabling is preferred for regular server racks, whereas structured cabling is applied to core network cabinets where stability and manageability are paramount.

Smart Cabling Management Platform

The platform addresses three pain points in multi‑batch cabling projects: (1) inconsistent or inaccurate documentation, (2) low efficiency and error‑prone manual route planning, and (3) fragmented data across many roles leading to isolated information islands. Its objective is to digitize, visualize, and automate cabling planning, execution, and lifecycle management.

1. Basic Information Maintenance

All physical entities—cables, cabinets, side cabinets, aisles, columns, head‑tail cabinets, bridge‑rack rooms, cross‑room bridge‑racks, etc.—are recorded as abstract data models (e.g., cabinet model, aisle model, cross‑room interconnect model). These models constitute the foundation for routing calculations.

2. Cabling Route Automation

Method 1: Scenario‑Based Calculation

Operators sketch a simplified room layout, define rows and columns, and link basic objects to establish relative positions. Six high‑frequency scenarios are identified (e.g., same‑room same‑aisle, cross‑room with/without a prescribed direction). A unified distance formula evaluates each scenario and selects the shortest feasible route.

Method 2: Shortest‑Path Optimization

The routing problem is transformed into a graph‑theoretic shortest‑path problem. Physical devices (cabinets, distribution units, bridge‑racks) are sequentially numbered; their geometric relationships are encoded as edges with associated lengths. Initial bridge‑rack lengths are supplied, after which a shortest‑path algorithm (e.g., Dijkstra) automatically computes the minimal‑length path between any two devices.

3. Cabling Task Creation

Task Generation

Users create a task by specifying a name, start and end rooms, cabinets, U‑positions, cable type, and the system auto‑generates a unique cable ID. The platform then runs the selected routing algorithm, outputs the optimal path, and produces a detailed bill of materials including estimated length.

Task Execution

The generated task follows a workflow of approval → digital documentation → real‑time status updates → final acceptance. Each step is recorded, ensuring traceability and consistency across stakeholders.

4. Cabling Operation Management

Completed tasks populate a persistent knowledge base. Visual dashboards provide quick insight into key metrics such as deployment status, cable‑type vs. device‑port compatibility, failure rates, and cost trends, supporting data‑driven fault isolation and continuous improvement.

Platform Deployment and Future Outlook

Version 1.0 of the Smart Cabling Management Platform is in production, and an invention patent titled “Cabinet Cabling Method and System” is under substantive examination. Automated routing reduces calculated cable length by an average of 10 % compared with manual estimates, lowering material cost and accelerating delivery.

Future work will integrate implementation feedback, delivery data, and network‑operation experience to bridge network management, IDC operations, and cabling management into a unified, intelligent platform for rapid delivery, smart operation, and fine‑grained control of data‑center cabling.