Latest News

sciencenews.png

Realizing the IOWN High-Capacity Optical Network: Aiming for Zero Sudden Communication Failures

2022.09.09

NTT has demonstrated the world's first technology for detecting predictors of multiple failure types and estimating where the relevant issue is. The technique uses optical fiber cables and optical transmission equipment already laid in the field.

IOWN, proposed by NTT, is an information and communications infrastructure to support the smart world of the near future through cutting-edge optical technology (photonics-electronics convergence technologies). APN is an innovative network based on photonics technology that plays a crucial role in the IOWN infrastructure. To realize IOWN APN, further capacity increases are being made to optical transmission equipment. However, increased capacity causes an inevitable increase in effects when failures occur.

To address this issue, NTT has improved the granularity of estimates for predicting failure locations by collecting and analyzing optical signal characteristic information in detail. It has now established and successfully demonstrated a technology that can identify package sections before they affect services.

NTT expects this technology to enable new preventative maintenance, improving the efficiency and quality of fault handling and helping avoid sudden service interruptions. It is hoping these benefits will help promote the introduction of IOWN APN in the future. Communication traffic is expected to grow due to progress with IoT and DX and rapid increases in remote work. These changes have created a need to accommodate traffic in an economical and power-efficient manner.

The company is now considering further ultra-high-capacity optical transmission using signals exceeding 400 gigabits per second. However, since increased capacity also increases the impact of failure, the company has been studying ways to minimize the impacts of this optical transmission equipment failing and improve reliability in line with this increased capacity. To improve the scalability and flexibility of optical transmission networks, a multi-vendor disaggregation configuration is also being considered that enables various multiple optical transmission systems with different applications to be directly and optically accommodated through openness.

However, direct optical connections of multiple transmission systems using the same configuration restrict monitoring and control coordination. Furthermore, since there is no conversion from optical to electrical signals, it also complicates identifying failure sites because the information obtained from connection points is reduced.

The results of NTT's findings mean that collecting and analyzing optical signal characteristic information in detail, which was previously not used for maintenance and operations, can enable highly accurate identification of the section of the optical transmission equipment package to be replaced. This identification includes predictive signs of failure before services are affected or alarms are issued, down to the actual package unit of the optical transmission equipment needing to be replaced.

The company's verification experiment used an experimental configuration consisting of pre-existing optical fiber cables and optical transmission equipment. It performed verification by incorporating a simulation system that simulates multiple predictive failure modes for multiple package sections and a new functional section that collects and analyzes optical signal characteristics information. As a result, the company successfully confirmed that it is possible to identify the location of predictive failure signs even after taking into account optical signal fluctuations caused by real-world operating environments and the behavior of equipment in these environments.

This article has been translated by JST with permission from The Science News Ltd.(https://sci-news.co.jp/). Unauthorized reproduction of the article and photographs is prohibited.

Back to Latest News

Latest News

Recent Updates

    Most Viewed