A Data-Fusion-Assisted Telemetry Layer for Autonomous Optical Networks

Abstract

For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred. Considering a large number of optical components in an optical network and many digital signal processing modules in each optical transceiver, massive real-time data can be collected. However, for a traditional monitoring structure, collecting, storing and processing a large size of data are challenging tasks. Moreover, strong correlations and similarities between data from different sources and regions are not properly considered, which may limit function extension and accuracy improvement. To address abovementioned issues, a data-fusion-assisted telemetry layer between the physical layer and control layer is proposed in this paper. The data fusion methodologies are elaborated on three different levels: Source Level, Space Level and Model Level. For each level, various data fusion algorithms are introduced and relevant works are reviewed. In addition, proof-of-concept use cases for each level are provided through simulations, where the benefits of the data-fusion-assisted telemetry layer are shown.

Photonics tomography for enhancing monitoring capability of optical networks

“…Proactive operation with closed-loop control is essential for high availability of optical networks. Monitoring is key to enable the closed-loop control and management of the optical networks [1,2]. In recent years, the open optical networks based on multi-vendor equipment with flexibility in selecting baud rates/modulation formats have made it challenging to do effective end-to-end monitoring.…”