A data streaming algorithm for estimating subpopulation flow size distribution

Statistical information about the flow sizes in the traffic passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and improve network performance through traffic engineering. Previous work on estimating the flow size distribution for the complete population of flows has produced techniques that either make inferences from sampled network traffic, or use data streaming approaches. In this work, we identify and solve a more challenging problem of estimating the size distribution and other statistical information about arbitrary subpopulations of flows. Inferring subpopulation flow statistics is more challenging than the complete population counterpart, since subpopulations of interest are often specified a posteriori (i.e., after the data collection is done), making it impossible for the data collection module to “plan in advance”. Our solution consists of a novel mechanism that combines...

• Type: Conference
• Year: 2005
• Where: SIGMETRICS
• Authors: Abhishek Kumar, Minho Sung, Jun Xu, Ellen W. Zegura
• Keywords: Data Collection Modules, Data Streaming Approaches, SIGMETRICS 2005, Subpopulation flow Statistics