Role of machine learning in configuration management of ad hoc wireless networks

Abstract

In this work, we show that machine learning, e.g., graphical models, plays an important role for the self-configuration of ad hoc wireless network. The role of such a learning approach includes a simple representation of complex dependencies in the network and a distributed algorithm which can adaptively find a nearly optimal configuration.