Fault detection in modern networks is done with a set of specially instrumented nodes which send probes to find faults. These probes generate additional traffic in network and compete with other regular traffic for bandwidth. In this paper we consider the problem of dynamically adapting the probes based on traffic dynamics experienced by nodes. We propose to profile the links and nodes to get aggregate I/O statistics in a time window and use it as an instantaneous measure of congestion. We consider the network with I/O statistics to generate a weighted graph and formulate an optimization problem to find a set of probes covering whole network with minimum weight. By showing that finding minimum weight probes maps to a known NP complete problem, we propose three greedy algorithms for selecting probes. With both simulation and real graphs of Internet Service Provider (ISP) networks, we perform five sets of experiments and show that proposed algorithms can dynamically adapt to changes in traffic dynamics and also can select probes in large networks in reasonable time.

中文翻译：

---

用于网络故障检测的流量动态感知探针选择

现代网络中的故障检测是通过一组特殊检测的节点完成的，这些节点发送探测器以查找故障。这些探测会在网络中产生额外的流量，并与其他常规流量争夺带宽。在本文中，我们考虑了基于节点所经历的流量动态动态调整探针的问题。我们建议对链接和节点进行概要分析，以获取时间窗口中的聚合 I/O 统计信息，并将其用作拥塞的即时度量。我们考虑具有 I/O 统计信息的网络以生成加权图并制定优化问题以找到一组覆盖整个网络的最小权重的探针。通过表明寻找最小权重探针映射到已知的 NP 完全问题，我们提出了三种用于选择探针的贪婪算法。