As more and more 5G services come online, consuming, processing, and taking action with organizational data has outpaced the capabilities and capacity of traditional databases and now demands increasingly sophisticated data visualization tools and applications. Time-series databases and artificial intelligence and machine learning (AI/ML) are needed to build, train, and interpret network models capable of understanding and emulating human experiences at machine scale.
Why do network operators need analytics?
Using network models and automating recovery reduces the number of catastrophic events over time. No human being could perform that kind of highly granular network monitoring. Providers need AI/ML so they can focus their time and energy on being efficient and focused on directional items and customer experience. Let the AI system manage typical operational tasks with a neural network brain.
How can AI/ML be used in a provider network?
Today, providers and their NOCs are most likely monitoring network behaviors with manual thresholds. When an event crosses a threshold, the system sends a notification, and the person who receives that notification may or may not take corrective action- again, manually. But it doesn’t have to work that way.
Here are four real-world examples of how a network operator can use AI/ML to improve their network management capabilities.
Predictive network planning
Predictive network planning allows network operators to reduce downtime and increase revenue by pinpointing exactly where network congestion and bottlenecks occur, and then automatically allocating new resources—either with idle capacity or with new equipment recommendations that match the need.
Consistent problem solving
Improving the consistency of problem-solving is a significant goal of every Network Operations Center (NOC.) For example, on the back end of network events, such as an outage or planned maintenance, effective machine learning and artificial intelligence tools can provide NOCs with consistent measurements and automated responses that return the network to steady-state convergence.
Adaptive network solutions
5G networks are constantly evolving, and NOCs need adaptive problem-solving approaches that include fast and accurate root-cause identification and remediation. But when a problem occurs, it’s impossible to sift through network events, alarms, and obscure behaviors without advanced tools. AI/ML can automatically identify and sort relevant PM data, classify it appropriately, and pinpoint systemic issues and causes quickly.
Fewer executive escalations
Solving network problems consistently and faster, with well-documented and automated solutions, will inevitably reduce the number of escalations the NOC must negotiate between customers and executives. With adaptive network solutions powered by AI/ML, NOC staff and administrators will spend less time firefighting and explaining themselves.
AI/ML with Virtuora® AX
Virtuora Analytics Transformation leverages cloud-native architecture that scales to fit data consumption and operation needs, and runs in public or private clouds. Virtuora AX is a member of the Virtuora cloud family of products. Virtuora cloud unifies orchestration, control, and management of the multilayer, multivendor network stack, unwinding complexity and enabling powerful functionality. With a Virtuora cloud solution, anyone can build a network around offerings and services powered by software.