Imagine an advanced 5G network with the capacity to anticipate problems and optimise performance, with a focus on further improving the user experience and being able to detect unusual traffic patterns that may pose a risk to cybersecurity in advance. Artificial intelligence at the core of mobile networks is already a reality, and it’s called NWDAF: Network Data Analytics Function.
In technical terms, NWDAF is a function within the architecture of the 5G network core that is responsible for collecting data, analysing it and making predictions. This allows the network to be more efficient, as it can anticipate future scenarios to make decisions in the present. For example, if a lot of robots in a factory are going to need to communicate at the same time, the NWDAF can foresee this and adjust the network so that everyone can communicate in a timely manner once that moment arrives.
The metaphor: 5G networks as a superhero
To put it simply: NWDAF in 5G networks is like a superhero with a toolbox full of superpowers.
- X-ray vision: it can see through the network and detect anomalies before they become problems.
- Telepathy: it communicates with other network functions to coordinate and optimise performance.
- Precognition: predicts where and when network congestion will occur and takes measures to avoid it.
- Super Speed: allows the network to adapt quickly to changes, ensuring that data flows without interruption.
- Multiplication: manages billions of devices, always trying to ensure that everyone has the connectivity they need.
- Camouflage: helps improve cybersecurity, keeping the network and user data safe.
With these superpowers, the NWDAF not only keeps the 5G network running smoothly, but also opens up a world of possibilities for innovative services and enhanced user experiences. It is the silent guardian and omnipresent protector of the 5G network! A guardian that opens the door to many future utilities that will make our lives perfectly connected:
- Emergency applications running on the 5G network in crowded environments, such as demonstrations or events, thanks to predictive algorithms that will help locate emergency services in a specific network slice as they travel to the incident area.
- Autonomous cars and drones that will choose their path based on how our network predicts the quality of service on their journey through the country.
- Industrial robots that will decide when to start an inspection round based on the future information provided by the 5G network.
- Gamers who will have a perfect gaming experience on the move because the network is able to predict which Edge Computing node will continue to provide them with service on their journey by car.
In short, the future of technology is here to stay… and to predict it. To make it more accurate and with less uncertainty. Or, in other words, to be able to guess the future
