Nokia and Vodafone to use machine learning on Google Cloud to detect network anomalies

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.

References:

One thought on “Nokia and Vodafone to use machine learning on Google Cloud to detect network anomalies

  1. “The goal here is to work with the carriers,” explained Sunay Tripathi, Google’s new director and head of products for telecom and the “distributed cloud edge.”

    Tripathi, who spoke at a 5G Future Forum event here, typified the new trend: He cut his teeth at Sun Microsystems before helping to found software-defined networking company Pluribus Networks. For the past three years, he was the CTO of Deutsche Telekom’s MobiledgeX. According to his LinkedIn profile, he joined Google in July. “We are rearchitecting a lot of the underlying network, and that creates a lot of opportunity,” Tripathi explained.

    Google, Microsoft and Amazon have long played in the telecom industry as software, IT and cloud suppliers. And like most modern enterprises across all industries, mobile network operators have increasingly pushed their IT operations into the public cloud.

    But during the past two years, Google, Microsoft and Amazon have all begun developing cloud computing products specifically designed to host wireless providers’ network functions. Whether it’s Microsoft’s Azure for Operators or Google’s Anthos for Telecom, it’s intended to get network operators to put their crown jewels – their core network functions – into a hyperscale cloud.

    And it’s something all three cloud companies are serious about, judging from their telecom hiring sprees or their acquisitions in the space. Microsoft, for example, last year spent an estimated $1.8 billion buying longtime telecom vendors Affirmed Networks and Metaswitch Networks.

    New ideas and new disruption

    According to analysts, the entry of the public cloud hyperscalers represents a major new strategic turn in the industry, considering network operators have historically retained tight control over their networking systems. And though most have been moving toward cloud technologies they own and operate, few have agreed to run their networking software in a public cloud operated by a hyperscaler.

    “In outsourcing the infrastructure to cloud providers, telcos risk losing control of different aspects of their network and technology roadmap over the long term,” warned analyst Frank Rayal of Xona Partners in a post to his website titled “How telcos outsourced their brains.”

    Nonetheless, there are increasing indications that operators around the world are more than open to the idea. “The technologies that we will build [with the cloud] will let others consume our network,” explained Luciano Ramos, SVP of network development, planning and engineering for Rogers Comunications in Canada.

    Indeed, AT&T recently announced it would transition its 5G core network operations into Microsoft’s cloud over the next three years. And Dish Network plans to run all of its network operations in the Amazon Web Services cloud.

    According to Rakuten’s outspoken mobile chief, Tareq Amin, it’s ultimately necessary. He said he designed Rakuten’s mobile network in Japan to natively run in the cloud, and that it required a major shift in his team’s thinking. “I wanted to pick the right mentality” when staffing up Rakuten Mobile, he said. “It was easier to deploy cloud because the Rakuten people wanted to be open to new ideas,” he said. “They were open to new ideas and new disruption.”

    Amin made his comments during a keynote address at the MWC LA show here. He made sure to point out that Rakuten Mobile in Japan now counts around 5 million customers, and boasts leading network metrics. It was essentially Amin’s victory lap after announcing his plan to build such a network just a few years ago, at the MWC Barcelona show in 2019.

    https://www.lightreading.com/service-provider-cloud/that-time-public-cloud-hyperscalers-invaded-mwc-la/a/d-id/773111?

Leave a Reply

Your email address will not be published.

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

*

 
 

 

Solve : *
18 ⁄ 3 =