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The increasing use of wireless networks has raised the desire to have not only a stable and good quality access to the network, but also to seamlessly change the network when moving. Various handover algorithms have been proposed to handle this situation. Unfortunately, many of these handover algorithms have only been evaluated by simulations. They do not take the wide range of mobile devices with varying system parameters into account. For the practical deployment, handover algorithms are required that adapt to various device parameters and network characteristics. In this paper we present a fuzzy-based vertical handover decision algorithm which adjusts itself to the given device and network capabilities. Starting with a discussion of handover requirements we present the algorithm and describe how it is activated in the handover process. Finally we present several experiments which evaluate the accuracy of the handover decision, the quality of service guarantees for the application, and the resource consumption.
Cooperation and interactions of mobile users is a characteristic feature of mobile collaborative applications. The users are located in different mobile communication networks or move in or among them, respectively. This requires horizontal and vertical handovers. The latter is required when the networks use different network technologies. Usually each mobile device independently chooses the most appropriate network for its purposes to switch to. In group-oriented applications this may lead to an uncoordinated network selection and as consequence to increased energy consumption. In this paper, we present a distributed vertical handover decision algorithm that coordinates the selection of the network among the mobile devices in order to ensure an optimal quality of service for the collaborative application and a low energy consumption of the involved mobile devices. The network selection is based on the calculation of a group benefit for each alternative network using the Simple Additive Weighting (SAW) algorithm. The feasibility of the algorithm is evaluated regarding varying group sizes and resource requirements.