摘要
With the increasing number of switches in Software-Defined Network-ing(SDN),there are more and more faults rising in the data plane.However,due to the existence of link redundancy and multi-path forwarding mechanisms,these problems cannot be detected in time.The current faulty path detection mechan-isms have problems such as the large scale of detection and low efficiency,which is difficult to meet the requirements of efficient faulty path detection in large-scale SDN.Concerning this issue,we propose an efficient network path fault testing model ProbD based on probability detection.This model achieves a high prob-ability of detecting arbitrary path fault in the form of small-scale random sam-pling.Under a certain path fault rate,ProbD obtains the curve of sample size and probability of detecting arbitrary path fault by randomly sampling network paths several times.After a small number of experiments,the ProbD model can cor-rectly estimate the path fault rate of the network and calculate the total number of paths that need to be detected according to the different probability of detecting arbitrary path fault and the path fault rate of the network.Thefinal experimental results show that,compared with the full path coverage test,the ProbD model based on probability detection can achieve efficient network testing with less overhead.Besides,the larger the network scale is,the more overhead will be saved.
基金
supported by the Fundamental Research Funds for the Central Universities(2021RC239)
the Postdoctoral Science Foundation of China(2021 M690338)
the Hainan Provincial Natural Science Foundation of China(620RC562,2019RC096,620RC560)
the Scientific Research Setup Fund of Hainan University(KYQD(ZR)1877)
the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(QCXM201910)
the National Natural Science Foundation of China(61802092,62162021).