Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6888602 | Pervasive and Mobile Computing | 2018 | 17 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Ran Ben Basat, Gil Einziger, Roy Friedman,