Adaptive resource reservation for indoor wireless LANs

Emerging communication-intensive applications such as multimedia teleconferencing require significant networking resources for efficient operation. In an indoor mobile computing environment, limited wireless resources and user mobility require effective resource reservation algorithms. These requirements demand an efficient advance reservation algorithm in order to minimize handoff call dropping while not compromising the 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 is that different cells in an indoor mobile computing environment behave differently based on location, and need to manage their resources according to their behavior profiles. We present two results: (a) classification of cells and predictive advance reservation based on location and behavior profiles, and (b) state-dependent resource reservation based on statistical information