Algorithms and estimators for summarization of unaggregated data streams Academic Article uri icon


  • Statistical summaries of IP traffic are at the heart of network operation and are used to recover aggregate information on subpopulations of flows. It is therefore of great importance to collect the most accurate and informative summaries given the router's resource constraints. A summarization algorithm, such as Cisco's sampled NetFlow, is applied to IP packet streams that consist of multiple interleaving IP flows. We develop sampling algorithms and unbiased estimators which address sources of inefficiency in current methods. First, we design tunable algorithms whereas currently a single parameter (the sampling rate) controls utilization of both memory and processing/access speed (which means that it has to be set according to the bottleneck resource). Second, we make a better use of the memory hierarchy, which involves exporting partial summaries to slower storage during the measurement period. 2014 Elsevier Inc. All rights reserved.

published proceedings


author list (cited authors)

  • Cohen, E., Duffield, N., Kaplan, H., Lund, C., & Thorup, M.

citation count

  • 12

complete list of authors

  • Cohen, Edith||Duffield, Nick||Kaplan, Haim||Lund, Carstent||Thorup, Mikkel

publication date

  • November 2014