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WiFi is probably the most popular short-range wireless access technology with an exponential increase of access point deployments for the past few years.
In order to support high connectivity and reduce latency of services, a large number of WLAN have been widely deployed.
They are being deployed in companies, schools, public and private areas; resulting in a high APs density and overlapping coverage areas. The density of access points is over-provisioned in order to provide enough capacity to meet the demands of peak hours.
Over 103000 access points were detected in the city of Taipei through war-walking, while the estimated density of access points deployed in different cities in Germany to vary between 488 access points per km²in industrial areas, and 6103 access points per km²in urban residential areas. However, during the off -peak period, the capacity demand declines sharply, and many access points become idle or in low utilisation. Even though, all access points are kept switched on all the time, even when the number of users served by the wireless access network is very low, resulting in a high and partially wasteful energy consumption. Even though a single access point consumes only few watts, the total energy consumed could reach hundreds of kilo watts in large deployments. Faced by access point proliferation and with the goal of reducing the energy consumption, recent research efforts have proposed algorithms to dynamically switch on and off a set of access points depending on the traffic load.
In continuity with these efforts, this thesis aims to design an Energy Proportional Networks by taking intelligent decisions into the network such as switching on and off network components in order to adapt the energy consumption to the user needs.
Our work mainly focuses on reducing the energy consumption by adapting the number of access points that are operating to the actual user need.