Abstract
Recent advances, related to the concepts of Artificial Intelligence (AI) and Machine Learning (ML) and with applications across multiple technology domains, have gathered significant attention due, in particular, to the overall performance improvement of such automated systems when compared to methods relying on human operation. Consequently, using AI/ML for managing, operating and optimizing transport networks is increasingly seen as a potential opportunity targeting, notably, large and complex environments.Such AI-assisted automated network operation is expected to facilitate innovation in multiple aspects related to the control and management of future optical networks and is a promising milestone in the evolution towards autonomous networks, where networks self-adjust parameters such as transceiver configuration.To accomplish this goal, current network control, management and orchestration systems need to enable the application of AI/ML techniques. It is arguable that Software-Defined Networking (SDN) principles, favouring centralized control deployments, featured application programming interfaces and the development of a related application ecosystem are well positioned to facilitate the progressive introduction of such techniques, starting, notably, in allowing efficient and massive monitoring and data collection.In this paper, we present the control, orchestration and management architecture designed to allow the automatic deployment of 5G services (such as ETSI NFV network services) across metropolitan networks, conceived to interface 5G access networks with elastic core optical networks at multi Tb/s. This network segment, referred to as Metro-haul, is composed of infrastructure nodes that encompass networking, storage and processing resources, which are in turn interconnected by open and disaggregated optical networks. In particular, we detail subsystems like the Monitoring and Data Analytics or the in-operation planning backend that extend current SDN based network control to account for new use cases.
Highlights
The benefits of Software-Defined Networking (SDN) based architectures go well beyond the separation of data and control planes, and centralized controllers
We present the control, orchestration and management architecture designed to allow the automatic deployment of 5G services across metropolitan networks, conceived to interface 5G access networks with elastic core optical networks at multi Tb/s
We briefly mention some of the targeted use cases, in addition to the common failure detection and localization [7] and virtual network topology (VNT) adaptability based on daily traffic models [8]
Summary
The benefits of SDN based architectures go well beyond the separation of data and control planes, and centralized controllers. Driven by the ever-increasing amount of devices, and the raise of disaggregated deployments, control, orchestration and management (COM) systems need to automate service provisioning and recovery, but need to monitor network and computing performances. This goal is to react to events such as failures, and to foresee degradations or capacity exhaustion. Monitoring and telemetry are automated tasks by which measurements data from network and IT devices, applications and services, are collected, transmitted, and stored in a repository, to be used as input of Data Analytics (DA) algorithms
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