Transforming network operations: The role of autonomous architecture in modern connectivity

The role of telecom networks has transformed significantly over the past few years, especially since the onset of the Covid-19 pandemic. As people increasingly turned to digital applications to perform everyday tasks, telecom networks evolved to provide the necessary digital infrastructure to address these requirements - be it education, entertainment, jobs, shopping, banking, healthcare needs, agriculture, or others. To address the evolving connectivity demands, Telecom Service Providers (TSPs) also integrated additional platform-based services powered by modern technologies such as the Internet of Things (IoT), blockchain, and edge computing. While these efforts have significantly improved customer experience, they have turned network management into a complex, costly, and time-consuming process. This is where the role of network automation comes in.
 
Today, autonomous networks powered by Artificial Intelligence (AI) and Machine Learning (ML) are revolutionising telecom services delivery worldwide. They simplify every operation, from policy implementation to network testing, from predictive maintenance to problem resolution, and more. 

How Indian Telcos Benefit from Autonomous Networks  

India has witnessed a staggering growth in Internet subscriptions over the past few years. With an overall internet penetration of 85.85%, India is home to the second-largest telecom industry in the world. While the growth has provided TSPs in India with ample opportunities for revenue generation, the challenges associated with infrastructure build-out and management have outpaced those benefits. According to a report by Cisco, the cost of managing today’s complex networks is two to three times more than the cost of the network itself. Thus, network automation has emerged as the way forward to reduce network management costs. 

Network automation reduces or completely eliminates human intervention in network operations. With improved responsiveness and predictive maintenance capabilities, autonomous networks can resolve common network issues as they happen, without human involvement, significantly reducing the chances of network downtime while also saving associated labour costs.  

Automation also simplifies application deployment, a key process in network management, and also a major cause of network downtime for telcos. With automation, TSPs can gain complete control of the process by speeding up the application deployment and reducing human errors, thereby eliminating network outages.

With AI/ML, network automation has become even more intelligent. It provides advanced network analysis leveraging historical and real-time data and facilitates network discovery. With these insights, TSPs can identify possible issues associated with each network element and proactively address them to avoid performance issues. Furthermore, insights on customer intent can help operators provide more targeted and personalised services. 

Software-defined network (SDN), a programmable network management system in automated networks, is also gaining popularity among telcos. With SDN, TSPs can track network changes in real time and deploy new configurations, like adjusting routing paths based on real-time traffic conditions, ensuring efficient data delivery, and minimising congestion. With automatic configuration of security controls, it also eliminates the risks associated with manual misconfigurations. With such insights and automated controls, networks become more agile and secure. 

Automated Networks for Network Optimisation and Sustainability

Operators around the globe are striving to reduce greenhouse gas emissions and cut down electricity consumption in order to save costs and achieve UN’s Sustainable Development Goals (SDGs). Automated networks are the answer to this as they help in optimising network resources. With AI integration, network provisioning becomes even more intelligent, leading to significant savings on resources. AI automation can improve the energy efficiency of networks by maximising network utilisation without impacting the performance of energy-saving features. It can reduce energy consumption by up to 30%, cutting CO2 emissions and cooling costs by 70%, as per Nokia estimates.

Network Automation by Indian TSPs

TSPs in India have realised the value of automating their networks to drive operational efficiency and cost savings. The four major operators have invested heavily and collaborated with leading tech companies to bolster their networks with advanced AI/ML technologies.

Reliance Jio has partnered with Guavus to leverage their AI-based solutions to provide real-time consumer experience and predictive analytics that would enable the telco to automate network troubleshooting and garner key marketing insights. Bharti Airtel has deployed Avanseus’s predictive maintenance (PdM) solution across its operations. It has also entered into partnerships with IBM, Red Hat, Cisco and Ericsson to further enhance their networks through automation. Vodafone Idea also has partnered with Cisco and Red Hat. Its strategic partnership with Red Hat to automate its IT infrastructure has helped reduce costs and improve operational efficiency. It has also partnered with Nokia to deploy the massive MIMO solution for network flexibility. State-owned BSNL too has partnered with Nokia for industrial automation solutions. It also signed a Memorandum of Understanding (MoU) with Ciena for its 5G network solutions. 

Automating the Future of Telecom in India

As network automation stays at the heart of innovative business models for telecom operators in India, its implementation requires a strategic and step-by-step approach. First, it requires thorough network analysis to identify key areas for automation and then select the right tools based on the requirements. As networks evolve to address the new demands, automation efforts will also have to undergo innovations so that networks stay agile and responsive to market requirements. By adopting appropriate network automation strategies, TSPs can stay on top of the digital innovation curve and drive efficiency across the entire value chain.

Authored by Lt. Gen. Dr. S.P. Kochhar, Director General, COAI