An Activity Based Mobility Prediction Strategy Using Markov Modeling for Wireless Networks

The foremost objective of a wireless network is to facilitate the communication of mobile users regardless of their point of attachment to the network. The system must discern the location of the mobile terminal, to afford flawless service to the mobile terminal. Mobility prediction is widely used to assist handoff management, resource reservation and service pre-configuration. Prediction techniques that are currently used don't consider the motivation behind the movement of mobile nodes and incur huge overheads to manage and manipulate the information required to make predictions. This paper proposes an activity based mobility prediction technique that uses activity prediction and Markov modeling techniques to devise a prediction methodology that could make accurate predictions than existing techniques.