Predicting network states for answering what-if scenario outcomes

An apparatus, comprising:

• one or more network interfaces to communicate with a network;
• a processor coupled to the network interfaces and configured to execute one or more processes;
• and
• a memory configured to store a process executable by the processor, the process when executed configured to:
• construct a set of controlled what-if input parameters for evaluating a what-if scenario in a network, wherein the set of controlled what-if input parameters relate to features of the network that are independently controlled;
• use the set of controlled what-if input parameters and state data indicative of a current state of the network as input to a network state model comprising a conditional generative adversarial network that implements a conditioning signal, wherein the conditioning signal a) steers a prediction of values for the state data conditioned on the what-if input parameters and b) is a concatenation of the set of controlled what-if input parameters and the state data;
• predict a key performance indicator (KPI) in the network by using the predicted values for the state data from the network state model comprising the conditional generative adversarial network as input to a machine learning-based KPI prediction model;
• and
• initiate a routing change in the network based in part on the predicted KPI.

A tangible, non-transitory, computer-readable medium storing program instructions that cause a device to execute a process comprising:

• constructing, by the device, a set of controlled what-if input parameters for evaluating a what-if scenario in a network, wherein the set of controlled what-if input parameters relate to features of the network that are independently controlled;
• using, by the device, the set of controlled what-if input parameters and state data indicative of a current state of the network as input to a network state model comprising a conditional generative adversarial network that implements a conditioning signal, wherein the conditioning signal a) steers a prediction of values for the state data conditioned on the what-if input parameters and b) is a concatenation of the set of controlled what-if input parameters and the state data;
• predicting, by the device, a key performance indicator (KPI) in the network by using the predicted values for the state data from the network state model comprising the conditional generative adversarial network as input to a machine learning-based KPI prediction model;
• and
• initiating, by the device, a routing change in the network based in part on the predicted KPI.