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We develop an Accelerated Back Pressure (ABP) algorithm using Accelerated Dual Descent (ADD), a distributed approximate Newton-like algorithm that only uses local information. Our construction is based on writing the backpressure algorithm as the solution to a network feasibility problem solved via stochastic dual subgradient descent. We apply stochastic ADD in place of the stochastic gradient descent...
In this paper, we propose a distributed algorithm for optimal routing in wireless multi-hop networks. We build our approach on a recently proposed model for stochastic routing, whereby each node selects a neighbor to forward a packet according to a given probability distribution. Our solution relies on dual decomposition techniques with regularization, that can significantly improve on the slow convergence...
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