Mobility Prediction and Resource Reservation in Cellular Networks with Distributed Markov Chains

In recent years, mobile hosts desire to benefit a good level of satisfaction for the received services in wireless networks, with adequate quality of service guarantees. In this work the attention is focused on wireless services in cellular networks, where the hand-over effects need to be mitigated, through an appropriate reservation policy. Passive resources are used to ensure service continuity when mobile hosts are moving among different coverage cells. The system is modeled through a distributed set of Hidden Markov Chains and the related theory is used to design a mobility predictor (in terms of future probably visited cells), as the main component of the proposed idea, that does not depend on the considered transmission technology (GSM, UMTS, WLAN, etc.), mobility model or vehicular scenario (urban, suburban, etc.). MRSVP has been used in order to realize the active/passive bandwidth reservation in the considered network topology and a severe simulation campaign has been led-out in order to appreciate the robustness of the reservation scheme.