Adaptive Resource Reservation for Indoor Wireless LANs

Emerging communication-intensive applications such as multimedia teleconferencing require signiicant networking resources for eecient operation. In an indoor mobile computing environment, limited wireless resources and user mobility require eeective resource reservation algorithms. These requirements demand an eecient advance reservation algorithm in order to minimize handoo call dropping while not compromise network utilization. This paper proposes a design framework and algorithms for advance resource reservation over the wireless link in indoor cellular wireless LANs. The key insight presented in this paper is that diierent cells in an indoor mobile computing environment behave diierently based on location, and need to manage their resources according to their behavior prooles. We present two results: (a) classiication of cells and predictive advance reservation based on location and behavior prooles, (b) state-dependent resource reservation based on statistical information.