Fast flow volume estimation

Ran Ben Basat, Gil Einziger, Roy Friedman

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The increasing popularity of jumbo frames means growing variance in the size of packets transmitted in modern networks. Consequently, network monitoring tools must maintain explicit traffic volume statistics rather than settle for packet counting as before. We present constant time algorithms for volume estimations in streams and sliding windows, which are faster than previous work. Our solutions are formally analyzed and are extensively evaluated over multiple real-world packet traces as well as synthetic ones. For streams, we demonstrate a run-time improvement of up to 2.4X compared to the state of the art. On sliding windows, we exhibit a memory reduction of over 100X on all traces and an asymptotic runtime improvement to a constant. Finally, we apply our approach to hierarchical heavy hitters and achieve an empirical 2.4-7X speedup.

Original languageEnglish
Pages (from-to)101-117
Number of pages17
JournalPervasive and Mobile Computing
Volume48
DOIs
StatePublished - 1 Aug 2018
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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