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Views: 0 Author: Site Editor Publish Time: 2025-11-13 Origin: Site
The network links of the future will no longer be cold cables and ports, but neural networks of intelligent systems.
Artificial intelligence is reshaping the field of network management at an unprecedented speed, from automatic fault detection to predictive maintenance, from intelligent traffic scheduling to adaptive security policies. Every link in network operation and maintenance is undergoing intelligent transformation.
However, as the cornerstone of all network communications, the importance of physical cabling infrastructure has not declined but increased in the AI era. The rise of intelligent computing centers has brought about brand-new changes and challenges to network transmission systems.
Network management is advancing from the traditional manual intervention model to the era of intelligent autonomy. According to the "Taiwan Industry AI Transformation Survey" report, although the proportion of Taiwanese enterprises entering the "AI large-scale application" stage has increased by 4% compared to 2022, nearly 70% of enterprises have yet to cross the threshold for practical AI application.
Most enterprises merely view AI as a tool rather than building an overall AI-driven architecture.
Ai-driven network operation can achieve an active management mode. Through predictive analysis and machine learning algorithms, it can monitor the network status in real time, detect anomalies and quickly fix problems. This transformation has turned network management from a "fire brigade" into a "preventive officer".
The key differences between traditional network management and AI-driven network management are reflected in three aspects:
- Level of automation: AI automates manual routine tasks, such as network performance monitoring, anomaly detection and maintenance work, freeing up human resources.
- Problem response: AI has predictive analysis capabilities, which can identify and respond to potential problems in advance, preventing them from evolving into major crises.
- Resource Optimization: Through AI-driven insights, enterprises can make more informed decisions on resource allocation, capacity planning, and cybersecurity investment.
In an AI-driven network environment, the importance of physical cabling has not decreased but changed. Intelligent computing centers are fundamentally different from traditional data centers. Their demand for network speed is much greater than that of general computing centers.
In AI workloads, zero tolerance for information delay is one of the main differences between intelligent computing and general computing. Network latency directly affects the training and inference efficiency of AI models.
It is estimated that when running large training models, 30% of the time is spent on network latency and 70% on computing. Since the cost of training a large model can be as high as 10 million US dollars, even saving 50 nanoseconds or 10 meters of optical fiber latency can have a very obvious effect.
The demand for bandwidth in AI clusters is growing at an unprecedented rate. The network speed of intelligent computing centers has advanced from 400G and 800G to 1.6T/3.2T.
This leap in bandwidth is not only an increase in quantity but also a qualitative transformation. It requires the cabling system to provide support for high-frequency signal transmission at the physical layer.
In the network architecture of intelligent computing centers, the Super Spine layer is usually introduced to ensure the interconnection and interoperability among each computing plane (such as the parameter plane, data plane and storage plane).
Due to the expansion of the network architecture scale, how to reduce latency and ensure the stability of network transmission has become the key to network architecture design.
In response to the new demands of AI network management, the selection criteria for structured cabling have also undergone fundamental changes.
The continuous improvement of network speed has put forward higher requirements for cabling systems. How to select the appropriate transceiver solution, ensure the compatibility and stability of multi-core MPO, and how to test multi-core MPO have become important considerations in the cabling design of intelligent computing centers.
For the MPO 16-core, the industry advocates the unified adoption of APC interfaces and Key Up/Key Down adapters to ensure connection stability in high-density environments.
In AI clusters, the choice between copper cables and optical fibers is no longer a simple binary decision. Short-distance Dacs (direct copper cables) still have their place in cabinet connections - increasing the usage of Dacs inside cabinets is an effective strategy to address the operational and maintenance challenges of intelligent computing centers.
For long-distance transmission, optical fiber is the best choice.
Single-mode and multi-mode optical fiber applications can support links up to 100 meters long. The development of silicon photonics technology has reduced the cost of single-mode transceivers, making them closer to the cost of equivalent multi-mode transceivers.
In traditional structured cabling systems, labels are affixed to patch panels, jumpers and panels in accordance with the TIA-606 standard. However, the information that labels can record is, after all, limited. Therefore, the application of visual integrated wiring management software has emerged.
Systems such as nVisual have introduced AI OCR technology. By integrating with mobile data acquisition and management terminals, they can identify the label text on the comprehensive wiring patch panels, jumps, and panels in real time.
After successful identification, the label is associated with the digital twin within the nVisual system, thereby displaying more abundant information beyond the label content through the mobile software.
To build cabling infrastructure for the AI era, it is necessary to consider the requirements of intelligent network management from the very beginning of the design.
Intelligent cabling management systems such as AMPTRAC can monitor in real time the equipment and cabling connection status of data center computer rooms, main computer rooms, and all floor distribution room computer rooms through the virtual distribution room function provided by the server software.
The implemented system can automatically update the connected data records within a few milliseconds without the need for manual intervention. In the event of an emergency (such as an unexpected interruption of a jumper port), the system can send an alert to the management personnel via email and list the detailed information of the port.
The intelligent cabling system usually adopts the dual patch panel mode (also known as the interconnection mode) - an additional patch panel is added between the original patch panel and the switch, and the switch ports are fixedly connected to the added patch panel one by one through single-ended patch cords with crystal heads.
This design reduces the failure rate of switch ports because they are fixedly connected and do not need to be frequently plugged and unplugged.
The cabling management of the intelligent computing center should be based on the principle of logical thinking and adopt a closed-loop management approach of "port identification - record archiving - work order dispatch - on-site operation - update archiving".
This method can achieve efficient management of ports during long-term operation and maintenance.
Building wiring infrastructure that ADAPTS to the AI era requires long-term planning and a forward-looking perspective.
In AI data centers, a balance needs to be struck between direct connection and structured cabling forms. Adopt applicable connection methods as needed to provide flexibility for the interconnection of various computing planes.
Meanwhile, the adoption of stable and reliable components and ultra-low loss products is the foundation for ensuring network reliability.
Network technology is still evolving rapidly, from 400G to 800G, and then to 1.6T/3.2T. The cabling system must reserve sufficient space for upgrades.
Choosing cabling products and solutions that can support future high-speed standards can extend the life cycle of infrastructure and improve the return on investment.
Optimizing the production and testing processes is a key element in enhancing the efficiency of network operation and maintenance. Emphasis should be placed on on-site installation management and testing, which is a prerequisite for achieving effective management of the entire network.
In the construction of intelligent computing centers, NVIDIA's architecture provides a typical example. The DGX H100 GPU server released by NVIDIA features 4 800G switch ports (operating as 8 400GE ports), 4 400GE storage ports, as well as 1GE and 10GE management ports.
A DGX SuperPOD can contain 32 such GPU servers, which can be connected to 18 switches in a single row. Each line will have 384 400GE optical fiber links for switch networks and storage, as well as 64 copper cable links for management.
In this case, the number of optical fiber links in the data center will increase significantly.
The deep integration of AI and network management is redefining the core value and selection criteria of structured cabling. The cabling system is no longer a passive underlying infrastructure but an indispensable participating element in intelligent network management.
In the face of the advent of the era of billions of intelligent agents, we need to build a more intelligent, efficient and reliable cabling infrastructure. Only by re-examining and optimizing the physical cabling layer can we provide solid support for AI-driven future businesses.
In the AI era, investing in future-oriented cabling infrastructure is investing in the cornerstone of an enterprise's future digital transformation.
