I. Industry Background: AI Is Reshaping the Foundation of the Optical Communications Industry

The explosive growth of AI computing demand is transforming the optical communications industry from a traditional data transmission infrastructure into an intelligent computing network. Two major trends are driving this transformation:

Accelerated Technology Evolution

800G optical modules have become the standard deployment for AI data centers, while 1.6T optical modules have entered commercial mass production. The technology upgrade cycle has shortened dramatically from the traditional four to five years to approximately two years, ushering the industry into a period of rapid capacity expansion and continuous technological innovation.

A New Growth Model

The industry's growth engine is shifting from simple penetration rate expansion to a dual driver of higher value per optical port and growing AI computing demand. As a result, the market is evolving from scale expansion to value creation. Cloud service providers are increasingly defining optical module specifications and procurement standards, making customization, ultra-high speed, and high reliability the new industry benchmarks. This shift is accelerating the transition from standardized products to customized optical solutions.

At the same time, AI foundation models are imposing three new requirements on network architectures:

• Massive burst traffic: AI training workloads generate instantaneous traffic at the TB/s level, making traditional fixed-bandwidth networks prone to congestion.
• High concurrency and synchronization: Model parameter synchronization is highly sensitive to microsecond-level latency, where even slight latency fluctuations can significantly reduce training efficiency.
• Dynamic communication patterns: Traffic patterns change frequently throughout AI training, requiring networks to support topology reconfiguration within milliseconds.

II. Three Fundamental Challenges of Traditional Electrical Switching Networks

The fixed-topology architecture of conventional electrical switching networks has become a major bottleneck limiting AI computing performance. It faces three fundamental physical limitations:

· Power Wall

Traditional electrical switching relies on repeated optical-electrical-optical (O-E-O) conversions, resulting in substantial energy loss. Network infrastructure typically accounts for 20%–25% of a data center's total power consumption, making it a key obstacle to improving energy efficiency.

· Latency Wall

Each electrical switch introduces processing latency on the order of hundreds of nanoseconds. In multi-hop network architectures, accumulated latency significantly reduces synchronization efficiency for distributed AI training, ultimately limiting computing performance.

 · Cost Wall

The rapid upgrade cycle of switching ASICs requires frequent replacement of network equipment whenever transmission speeds increase. This leads to high capital expenditures (CAPEX), greater operational complexity, and increased long-term operating costs.

III. OCS Technology Roadmap and Strategic Positioning

Optical Circuit Switching (OCS) establishes end-to-end optical paths directly at the physical layer without any optical-to-electrical conversion or electrical signal processing. As a result, OCS provides an effective solution to overcome the power, latency, and cost barriers inherent in conventional electrical switching networks.

Today, the industry is primarily developing three mainstream OCS technologies, each with distinct characteristics and levels of maturity.

MEMS Micromirror Technology

MEMS-based optical switching is currently the most mature and widely deployed solution. It offers a compelling combination of high port density, low insertion loss, and millisecond-level switching, making it the dominant technology in today's OCS market.

Liquid Crystal (LC) Technology

Liquid crystal (LC)-based optical switching eliminates mechanical movement, resulting in exceptional reliability and long operational lifetime. It is particularly well suited for applications requiring continuous, highly stable operation.

Silicon Photonics (SiPh) Technology

Silicon photonics represents the long-term evolution of OCS toward higher integration, lower latency, and chip-scale implementation. With the potential for ultra-fast switching and highly integrated photonic circuits, SiPh is regarded as the future direction of optical switching, although it is still progressing through technological development and commercial adoption.

IV. GLSUN OCS System Solution

GLSUN focuses on MEMS-based optical switching technology and offers highly integrated Optical Circuit Switching (OCS) solutions designed for AI computing clusters, hyperscale data centers, and next-generation optical networks.

4.1 Technology Overview

The GLSUN OCS system is built around a dual-axis MEMS micromirror array, which dynamically redirects optical signals by precisely controlling the angle of each micromirror. This architecture enables millisecond-level optical path provisioning, non-blocking all-optical switching, and rapid network reconfiguration with exceptional reliability, providing the hardware foundation for flexible, high-speed optical networks.

4.2 Key Performance Advantages

4.3 Performance Validation

Comprehensive laboratory testing of the 3D MEMS M×N OCS architecture demonstrates excellent optical performance consistency across all ports.

• Insertion Loss: Minimum 1.0 dB, typical 1.5 dB
• Wavelength Dependent Loss (WDL): Typical 0.3 dB across both the O-band and C-band, with stable performance throughout the operating wavelength range
• Switching Time: Typical 30 ms, enabling rapid optical path establishment
• Polarization Dependent Loss (PDL): Typical 0.3 dB, ensuring low polarization sensitivity

4.4 Application Value

The GLSUN OCS solution is designed for a wide range of high-performance networking applications, including:

• AI computing cluster interconnection
• Data Center Interconnect (DCI)
• Optical backbone switching
• Cloud computing infrastructure
• High-performance computing (HPC)

Compared with conventional electrical switching architectures, GLSUN's OCS significantly reduces power consumption and equipment footprint while supporting protocol-agnostic, rate-transparent optical transmission. The solution enables the construction of low-latency, high-bandwidth, and highly flexible optical interconnect networks, providing a robust hardware foundation for AI computing infrastructure and cloud-network convergence.

V. OCS Market Trends and Industry Outlook

Rapid Market Growth

According to industry forecasts, the global Optical Circuit Switching (OCS) market is expected to reach several billion U.S. dollars by 2029, with a compound annual growth rate (CAGR) exceeding 50% over the next four years. OCS is widely recognized as one of the fastest-growing segments within the optical communications industry.

Expanding Deployment Scenarios

OCS is evolving from a customized solution adopted by a small number of hyperscale cloud providers into a foundational infrastructure technology for AI networking across the industry. Its applications continue to expand, including:

· AI model training clusters

· AI inference networks

· Data Center Interconnect (DCI)

· High-availability and disaster recovery networks

· Next-generation cloud infrastructure

· Industry Consensus

A broad industry consensus has emerged that Optical Circuit Switching is becoming a critical enabling technology for hyperscale cloud providers and high-performance data centers. As AI workloads continue to grow, OCS is expected to become one of the most strategically important infrastructure technologies in optical communications, driving sustained market growth over the coming years.