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In this paper, the authors present a distributed algorithm to dynamically allocate the available resources of a service-oriented network to delay sensitive network services. They use a utility-based framework to differentiate services based on both their relative profitability and quality-of-service requirements. Their performance metric is the end-to-end delay that a service class experiences in the network. They use network calculus to obtain a deterministic upper bound of this delay and they incorporate this information into their optimization problem formulation. They leverage a moving average control scheme to capture traffic shifts in real time, which makes their solution to react adaptively to traffic dynamics.
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