Parallel algorithm for network tomography

Network tomography aims to obtain link-level performance characteristics, such as loss ratio and average delay on each link, by end-to-end measurement. We proposed an approach in the multicast class that uses a Bayesian network to carry out statistical inference. Studies show that our approach can achieve the same results as other methods with strong robustness. In this paper, we propose a parallel algorithm to accelerate the statistical inference process.