Middleware Vertical Handoff Manager: A Neural Network-Based Solution

Major research challenges in the next generation of wireless networks include the provisioning of worldwide seamless mobility across heterogeneous wireless networks, the improvement of end-to-end quality of service (QoS), supporting high data rates over wide area and enabling users to specify their personal preferences. The integration and interoperability of this multitude of available networks will lead to the emergence of the fourth generation (4G) of wireless technologies. 4G wireless technologies have the potential to provide these features and many more, which at the end will change the way we use mobile devices and provide a wide variety of new applications. However, such technology does not come without its challenges. One of these challenges is the user´s ability to control and manage handoffs across heterogeneous wireless networks. This paper proposes a solution to this problem using artificial neural networks (ANNs). The proposed method is capable of distinguishing the best existing wireless network that matches predefined user preferences set on a mobile device when performing a vertical handoff. The overall performance of the proposed method shows 87.0 % success rate in finding the best available wireless network. To test for the robustness and effectiveness of the neural network algorithm, some of the features were removed from the training set and results showed a significant impact on the overall performance of the system. Hence, managing vertical handoffs through user preferences can be significantly affected with the selection of features used to provide the closest match of the available wireless networks.