Predictive Optimization

Service providers of all types are looking to achieve greater agility. They want to be able to respond more quickly to changes in demand for services, or to requests for completely new kinds of service.

Virtualization, in the form of SDN and NFV, should allow changes to be made more quickly. But for any given situation, the question remains, what is the right change to make?

Deciding how best to change networks to meet certain criteria is incredibly complex. It’s why – despite automation in many areas – this has remained a task that only humans can carry out.

But with today’s multi-layer, multi-technology, global networks; with physical and virtual resources, and the relentless pace of change, more automated solutions are now essential.

Introducing Aria

Aria has perfected the technology needed to turn the Big Data generated by networks into business-optimal changes.

By looking at historical data on demand growth, capacity consumption, performance, revenue information and more, Aria builds a predictive model of future behaviour.

But this is much more than just conventional analytics or trending. Thanks to Aria’s unique business-driven optimization approach, service providers can use Aria’s predictive optimization capabilities to answer key questions:

  • where and when will we run out of capacity?
  • where and how should we rationalize resources?
  • which part of the network would be the most profitable network to expand?

Aria uses AI to create a dynamic model, that adapts as updated information is fed in. Such machine learning is recognized by many as integral to the success of virtualized and software-defined networks.

Predictive Optimization is a core capability of the Aria suite, and underpins many of the applications for network planning and optimization.