Autonomic Network Management
Increasing complexity of networks and growing user demands complicate the task of network operators to provide optimum performance of the network while reducing cost. In particular, the manual control of the network facing changing traffic patterns becomes a challenge. The aim of this project is to automatize networking tasks using machine learning. In order to do so, a software-defined network is used which provides "sensors" which acquire load information and "actuators" which can redirect or shape the load to optimize network utilization.