一种高效的单播网络自适应拓扑推测算法

为提高单播网络拓扑推测的效率和准确性,本文提出一种高效的单播网络自适应拓扑推测算法.该算法利用探测包中的TTL信息作为二分深度优先搜索排序中参考节点的选择依据,有效降低测量过程中所需的背靠背包对数量,提高拓扑推测的效率;通过对现有的深度优先搜索下网络拓扑推测算法原理的分析,给出该算法能够正确推测出整个网络拓扑的充分条件,在此基础上提出一种自适应判定阈值选择方法,有效提高网络链路参数未知情况下的拓扑推测准确性.仿真实验结果表明,本文所提出的算法具备更高的拓扑推测效率和准确性.

Efficient and Adaptive Topology Inference Algorithm for Unicast Network Measurements

In order to improve the accuracy and efficiency of the topology inference algorithm for unicast network,an efficient and adaptive topology inference algorithm is proposed.With the information of TTL hop count,this algorithm reduces the number of the probe pairs needed in the process of bisection Depth-First Search Ordering,and improve the efficiency of the topology inference.On the other hand,through the analysis of the principle of the Depth-First Search topology inference algorithm,a sufficient condition for the algorithm to return the correct network topology is given.Based on this condition,an adapt threshold selection method is proposed,it can improve the accuracy of the topology inference when the network link parameters are unknown.Simulation results show this algorithm can obtain a higher accuracy and efficiency.