Ericsson has launched an intelligent, cloud-native transport controller that uses artificial intelligence and machine learning to analyze and automate microwave, IP and optical networks, providing communications service providers (CSPs) with an advanced solution for maximizing mobile transport network efficiency.
The new Ericsson Transport Automation Controller helps service providers stay ahead of the challenges that can impact network status and performance by enabling data-driven decisions. It instantly pinpoints degradations and capacity utilization issues and provides insights on how to optimize the overall network performance. Further on, it reduces human errors and troubleshooting, thanks to AI-driven automation.
Most network issues are still solved manually, resulting in significant operational costs and bringing the risk of human errors and potential security concerns. Simultaneously, the increase in data traffic and user expectations for high-speed, low-latency connectivity calls for the deployment of new sites and hardware that must be monitored and managed alongside legacy equipment.
Ericsson Transport Automation Controller reduces transport network complexity and boosts operational and energy efficiency while optimizing performance. This is done by providing real-time network observability and data analysis, which helps CSPs understand why certain issues occur and what trends and performance anomalies happen in the network, enabling proactive network control such as preventive maintenance. It can be deployed in hours and easily scaled as needed to fit any network size, resulting in lower total cost of ownership (TCO) and higher flexibility. It is also easy to use and manage thanks to its intuitive web-based user interface.
Jari Augustin, Head of Product Line Transport Automation says: “Ericsson Transport Automation Controller is our latest cloud-native AI software that allows our customers to see, understand, and automate their microwave, IP and optical networks easily and cost-efficiently. It builds upon nearly 50 years of experience in microwave technology, with more than a decade of extensive research in artificial intelligence and machine learning for transport networks. This new product is a unique combination of an analytics tool and a software-defined network controller, leading the way toward a self-optimizing and self-healing transport network.”
Ericsson Transport Automation Controller works through three main actions:
- Observing – gaining real-time visibility, data collection, and monitoring of the transport network via an intuitive web-based user interface with interactive maps and configurable dashboards.
- Analyzing – identifying network problems and preventing potential disruption and downtime before they impact users with AI/ML predictive analytics.
- Acting – keeping transport network running smoothly and efficiently with intelligent automation for intent-driven problem resolution and resource optimization.
Grant Lenahan, Partner and Principal Analyst, Appledore Research, says: “Ericsson’s expertise in radio, backhaul, microwave, and analytics provide a solid platform for the Transport Automation Controller. The combination of automatic configuration, pathfinding, and other advanced functionality, along with AIOps (Artificial Intelligence for IT Operations), help drive intelligent transport automation for consumer and enterprise use cases.”
Find out more about about Ericsson Transport Automation Controller
NOTES TO EDITORS
Ericsson Transport Automation Controller’s key characteristics are:
AI-driven intelligence and insights – advanced analytics based on real-time transport network monitoring and frequent data collection, provided by leveraging AI/ML models developed using Ericsson’s expertise in 5G Transport.
Analytics and automation made easy – a single pane of glass for transport network observability, enabling intelligent automation and control via an easy-to-use web-based interface with customizable dashboards and configuration wizards.
Flexibility and scalability – cloud-native product intended for deployment on customer premises, with the ability to easily scale from small to large networks.
Endorsing standardization and openness – standards-based, multi-domain AI product built for vendor-agnostic control and easy integration with third-party product components and transport nodes.
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