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Flow and admission control algorithms have been proposed for efficient resource utilization in wireless networks with scarce and randomly varying resource availability. Transport and lower layer control protocols administer generic control behavior, ignoring particular application requirements or characteristics. Network-aware applications, on the other hand, enable us to develop application specific control mechanisms. We propose a novel control theory based adaptive resource management framework for network-aware scalable multimedia applications in wireless networks. In particular, we design an application-aware pro-active middleware based on level crossing analysis of stochastic models assisting a set of control algorithms founded on automatic control theory, thus avoiding network congestion and ensuring optimal resource utilization and application level QoS. Simulation experiments show that the resource management framework is capable of achieving bandwidth utilization within 1.5% of the optimum (theoretical) value and a delay jitter of 1.3 msec2 only, for real-time video streaming. Also, it ensures a low session blocking rate (less than 10% for high session arrival rate) and high percentage of sessions with good quality video.