Python
Predict the throughput of a access point (AP) in a campus WiFi network, with machine learning
History AP throughput data of Heriot-Watt University campus for one week.
Random Forest Regression
The machine learning results are compared with real data, as shown in the .png figures
Java
Access Point Sleep in WiFi network, is a ontology-based application that enable energy efficiency for Indoor WiFi networks. ASleep can satisfy the WiFi clients demand with the minimum number of WiFi APs, and turn the other APs to sleep mode. In indoor scenario of WiFi networks for office, universities, or shopping malls, the traffic of WiFi network has clear periodic patterns. In period of low traffic, e.g., after 5 PM on working days and holidaies, there are very few, if any, clients are using WiFi networks. While all the WiFi APs are working full time at full speed. ASleep is designed for this scenario. At low traffic period, ASleep will asign APs to cover clients, making the number of APs minimum, without deteriorate QoS. The other APs are set to sleep mode.