Intelligent network discovery for next generation community wireless networks

Nowadays, IEEE 802.11 networks are the most popular option to have wireless access to the Internet and a promising technology to tackle the digital divide that accounts for 2/3 of the world population. However, the popularity of these networks have raised a complex discovery and connection process, i.e., any device has to pass through an expensive scanning process of available Access Points in crowded and chaotic deployments. The scanning process can be modelled by a set of metrics exposing a trade-off between latency and the discovery rate when searching for appropriate Wi-Fi connection. Consequently, in order to improve the connection process, we use a multi-objective optimisation approach for generating optimal scanning sequences. We propose a framework to assist the network discovery within a Community Network, and we have adapted a Cultural Algorithm as an intelligent component for calculating optimal scanning sequences. Results show that we can derive optimal scanning sequences better than standard approaches for scanning in chaotic network deployments.