In recent years, there has been an increasing demand for ubiquitous streaminglike applications in data networks. In this paper, we concentrate on NUM-basedrate allocation for streaming applications with the so-called S-curve utilityfunctions. Due to non-concavity of such utility functions, the underlying NUMproblem would be non-convex for which dual methods might become quite useless.To tackle the non-convex problem, using elementary techniques we make theutility of the network concave, however this results in reverse-convexconstraints which make the problem non-convex. To deal with such a transformedNUM, we leverage Sequential Convex Programming (SCP) approach to approximatethe non-convex problem by a series of convex ones. Based on this approach, wepropose a distributed rate allocation algorithm and demonstrate that under mildconditions, it converges to a locally optimal solution of the original NUM.Numerical results validate the effectiveness, in terms of tractable convergenceof the proposed rate allocation algorithm.
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