Flow-level traffic measurement is important for network traffic accounting, traffic engineering, and network security. However, flow-level measurement in high speed networks poses great challenges due to the requirements of high packet processing speed and large memory size (high time/space complexity). To reduce these demanding requirements, sampling is usually used and samplers are deployed i...

Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein controller keeps track of all active flows and samples devices on each flow path to collect real-time statistics. There is a tradeoff between controller’s sampling preference balancing loads among devices. On one hand, may prefer sample some ...

With the increase in cyber threats recent years, there have been more forms of demand for network security protection measures. Network traffic classification technology is used to adapt dynamic threat environment. However, has a natural unbalanced class distribution problem, and single model leads low accuracy high false-positive rate traditional detection model. Given above two problems, this...

We conduct a detailed simulation study to assess how well various sampling techniques recover network characteristics such as degree, clustering coefficient, and path length distributions of several simulated population networks that have the high clustering tendency characteristic of social networks but vary in terms of degree distribution and density. We consider several alternative sampling ...