What is AF (Class) Instance

The increased use of software-driven and virtualization techniques enables more versatile network infrastructures. Realizing the full potential of such large and dynamic systems requires advanced automation and adaptation capabilities. In this chapter, the authors review recent development of so-called self-driving networks combining cognitive techniques and autonomic behaviors. In particular, the authors provide insights on a set of core mechanisms for the operation of self-driving networks: (1) a governance function to help operators deploy, pilot, control, and track run-time behaviors and performance of self-driving functions; (2) a coordination function to ensure stability and performance when several self-driving functions are running together; (3) a knowledge function to share relevant information to empowering their actions; and (4) common workflows, lifecycles, and APIs to enable deployment and interoperability of autonomic functions. The analysis connects with reference work in scientific literature and the most recent developments in standards (e.g., IETF/IRTF and ETSI).