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This letter presents packet scheduling disciplines based on application utility functions and network traffic measurements. The disciplines support different classes of adaptive applications over the Internet, providing differentiation, fairness, and dynamic allocation of network resources. They are composed of a decision procedure, where a fairness criterion based on utility functions is used; and a measurement procedure, which considers the statistics involving packet arrivals and departures. The underlying algorithm is then applied to emulate the proportional differentiation services, and is shown-via simulation-that its results outperform the best alternative algorithms published in the literature.