Nokia and Vodafone have partnered to jointly develop a new machine learning (ML) system designed to detect and remediate network anomalies before they impact customers. Based on Nokia’s Bell Labs algorithm, the Anomaly Detection Service product runs on Google Cloud and is already being rolled out across Vodafone’s pan-European network.
In a joint statement, the partners said the ML system quickly detects and troubleshoots irregularities, such as mobile site congestion and interference, as well as unexpected latency, that may have an impact on customer service quality. Following an initial deployment in Italy on more than 60,000 LTE cells, Vodafone said it will be extending the service to all its European markets by early 2022, and there are plans to eventually apply it on the company’s 5G and core networks.
Vodafone added that it expects that around 80 percent of all its anomalous mobile network issues and capacity demands to be automatically detected and addressed using Anomaly Detection Service.
Vodafone’s deal with Nokia signed last year complements its recent six-year agreement with Google Cloud to jointly build integrated cloud-based capabilities backed by hubs of networking and software engineering expertise.
The platform, called ’Nucleus’, will house a new system ‘Dynamo’, which will drive data throughout Vodafone to enable it to more quickly offer its customers new, personalized products and services across multiple markets. Dynamo is expected to help Vodafone to tailor new connectivity services for homes and businesses through the release of new features such as providing a sudden broadband speed boost.
Capable of processing around 50 TB of data per day, Nucleus and Dynamo are considered “industry firsts”. Being built in-house by Vodafone and Google Cloud specialist teams, the project involves up to 1,000 employees of both companies located in Spain, the UK and the US.
Vodafone said it has already identified more than 700 use-cases to deliver new products and services quickly across its markets, support fact-based decision-making, reduce costs, remove duplication of data sources, and simplify and centralize operations.
Johan Wibergh, Chief Technology Officer, Vodafone, said: “We are building an automated and programmable network that can respond quickly to our customers’ needs. As we extend 5G across Europe, it is important to match the speed and responsiveness of this new technology with a great service. With machine learning, we can ensure a consistently high-quality performance that is as smart as the technology behind it.”
Amol Phadke, Managing Director, Telecom Industry Solutions, Google Cloud, said:
“We are thrilled to partner with Nokia and Vodafone to deliver a data- and AI-driven solution that scales quickly and leverages automation to increase cost efficiency and ensures seamless customer experiences across Europe. As behaviors change and the data needed for analysis increases in velocity, volume, and complexity, automation and a cloud-based data platform are now key in making fast and informed decisions.”
Anil Rao, Research Director, Analysys Mason, said: “Vodafone’s anomaly detection use case, developed in partnership with Nokia and run on Google Cloud, automates root-cause analysis for efficient network planning, optimization, and operations. This type of partnership provides a new opportunity for operators to rethink data management and increase the focus on use cases and application development.”
Raghav Sahgal, President of Cloud and Network Services, Nokia, said: “This first commercial deployment of Anomaly Detection Service with Vodafone on Google Cloud provides a great boost to customer service. It not only addresses the critical need to quickly detect and remedy anomalies impacting network performance using machine learning-based algorithms, but it also highlights Nokia’s technology leadership and the deep technical expertise of Nokia Bell Labs.”
Vodafone said it will convert its entire SAP environment to Google Cloud, including the migration of its core SAP workloads and key corporate SAP modules such as SAP Central Finance.