中文摘要：

针对大规模IP网络拥塞链路丢包率范围推断算法中存在的不足,提出一种贪婪启发式拥塞链路丢包率范围推断算法.借助多时隙路径探测,避开单时隙探测对时钟同步的强依赖;通过学习各链路拥塞先验概率,借助贝叶斯最大后验定位拥塞链路;提出了聚类拥塞链路相关、性能相近路径集合的策略,通过对聚类路径集合中性能相似系数求解,循环推断拥塞链路丢包率范围.实验验证了算法的准确性及鲁棒性.

英文摘要：

Addressing the shortcomings of existing link congestion loss rate range inference algorithms in large scale IP network, a new link congestion loss rate range inference algorithm based on greedy heuristic method is proposed. The strong dependency on the clock synchronization of single slot E2E path measurements is avoided through using multiple slots E2E path measurements. Each congested link can be located through adopting the link congestion Bayesian maximum a-posterior （BMAP） after learning prior probabilities of the link congestion. The set consisting of paths with related congested links and similar performance is constructed. Through solving the performance similarity coefficient dynamically, loss rate range of each congested link can be recurrently inferred. The accuracy and robustness of the algorithm proposed in this paper is verified by experiments.