Upgrading networks for the next era of connectivity
While technologies such as self-driving vehicles will take time to go mainstream in India, intelligent networks will play a crucial role from the start in supporting and ushering in the next wave of 5G-enabled wireless connectivity. Ciena India’s Nihar Panda details how a new approach to networking is needed for service providers to succeed at the edge.This article was originally published on Fortune India.
Over the past year, communications networks have been in the spotlight for allowing people to continue with professional and personal tasks as lockdowns and social distancing norms made it impossible to lead normal lives. Emerging as a de facto way to connect with our colleagues, associates, and loved ones, communications networks are now our biggest (and sometimes only) entertainment source, healthcare partner, and mechanism to work. The edge is the new frontier for connectivity. Insatiable demand from consumers and businesses for new services, applications, and content shows no sign of slowing down.
With 5G and the rise of IoT and cloud services, service providers must rapidly scale to requirements of the edge. Rethinking networks to be simple, open, and automated enables service providers to grow and deliver incredible customer experiences.
The surging data demand can sometimes bog down networks, resulting in inferior quality of customer experience and often downtime. It is even more challenging for Indian businesses that have already started their journey towards Industry 4.0, connecting machines to the network for improved efficiency and agility. Using automation in networks minimises manual interventions, allowing operators to plan and manage their edge networks more efficiently. More importantly, they are imperative for the 5G era.
Modernising India’s edge requires automation
When we talk about 5G as the most promising technology for a country like India, networks will become increasingly important by providing new and exciting use cases. India will benefit from several 5G use cases enabled by edge cloud like online gaming, Industry 4.0, telemedicine, and smart cities, among others.
Industry 4.0 similarly has massive potential for India and requires a similar reliable, high-speed, and low-latency network. A Capgemini Research Institute study from 2019 points out that smart factories can add at least $1.5 trillion to the global economy by 2023 through productivity gains and improvements in quality and customer services.
However, different industries or customers have different latency requirements. 5G networks have the capability to provide advanced multi-tenancy and network slicing, allowing communication service providers (CSPs) to address the unique, specialised performance requirements of a variety of industries at an affordable price. But this has to be achieved with the help of intelligent automation.
Building a programmable network requires software
Software-defined networking, network function virtualisation, and cloud-native computing act as building blocks for a flexible, dynamic, and programmable 5G network platform.
CSPs can benefit from these capabilities to build separate ‘end-to-end network slices’ with different latency, performance, and availability requirements with a different service level agreement (SLA) for each slice. These slices can run independently and enable industry-specific services, a use case-based service, or an enterprise-specific service catering to only a specific group of subscribers.
Reducing complexity enables more seamless digital experiences at the edge
As new use cases continue to evolve that enable CSPs to better monetise their 5G investments, networks must become increasingly dynamic and agile to better service an increasingly on-demand market. Training the workforce on each and every aspect of the network and finding enough network engineers to manage and maintain it will be significantly challenging. Further, this approach substantially burdens the bloating operational budgets that CSPs have been consistently trying to reduce. A shift towards network autonomy, driven by data-driven artificial intelligence (A.I.) and machine learning, will help alleviate these new challenges.
Data-driven automation can accurately predict network faults, detect them in real-time, quickly diagnose and recover. These networks can also self-configure, self-optimise, and self-heal.
CSPs can leverage the massive data sets that their existing systems generate and use them for training the machine learning algorithms, eventually allowing them to build a fully automated and autonomous network. It will then run with little to no human intervention and configure, monitor, and maintain itself independently.
CSPs need to advance A.I. and cloud technologies to simplify network operations and enhance efficiency.
With software-driven networks, all that CSPs will require is to create 5G network slices for each use case of a customer segment and then let the automated network do its job—designing, planning, provisioning, monitoring, and even maintaining the network. And if you think we’re talking about the future, remember that this future is now!