Distributed flow control is a key issue in wireless sensor network design to achieve good network performance.This paper presents a node energy and link capacity constrained flow control optimization model for distributed flow control in wireless sensor networks.Since subgradient-based dual-decomposition method suffers from slow convergence rate and sensitivity in step-size choosing

this paper adopts matrix-splitting based distributed Newton algorithm to maximize the network utility.The proposed algorithm can achieve quadratic convergence rate while requiring almost the same communication overhead as the subgradient-based dual-decomposition algorithm.Moreover

it is shown by simulations that the proposed algorithm has a much better convegence performance than the subgradient-based dual-decomposition algorithm.