Wi-Fi Energy-Saving Technology Research Based On Context Awareness

In recent years,the continuous development of the mobile device,which features a more powerful and embedded sensors,such as the position sensor(GPS)and optical sensors.It is because of the convenience and functionality of mobile devices,users will often carry,so through the embedded device in the sensor to collect information can be more closely reflect the user's daily habits.Through some way such as by the mobile device collect environment data which is called scene data,mining of the data which can be used to provide personalized and context aware services for mobile device users.If the context data is excavated and the context-aware system model is established,the system can provide personalized,context-aware services for mobile device users based on the established model.At present,the energy consumption of Wi-Fi in mobile devices is the concern of many mobile phone users,especially if the user does not need to connect Wi-Fi without closing it,at this time,Wi-Fi module needs to keep scanning and lead to unnecessary waste of electricity.To solve unnecessary Wi-Fi scanning in order to achieve energy saving effect.This article has found that users connected to Wi-Fi and users are often in a day and the location and time are closely linked,so the use of trajectory mining Apriori clustering algorithm mining user frequent mode,and then according to the user frequently used the appropriate system the OPTICS density algorithm detects the user's Wi-Fi cycle,establishes a Wi-Fi cycle scenario-aware model for different mobile device users,and provides intelligent switching Wi-Fi services based on the user's Wi-Fi cycle model,resulting in energy savings.Experiment result shows that about 17%of the energy is saved for regular users,and about 10%of the energy of the user in the regular course of activity.