1 research outputs found
Boundaries of Flow Table Usage Reduction Algorithms Based on Elephant Flow Detection
The majority of Internet traffic is caused by a relatively small number of
flows (so-called elephant flows). This phenomenon can be exploited to
facilitate traffic engineering: resource-costly individual flow forwarding
entries can be created only for elephants while serving mice over the shortest
paths. Although this idea already appeared in proposed TE systems, it was not
examined by itself. It remains unknown what extent of flow table occupancy and
operations number reduction can be achieved or how to select thresholds or
sampling rates to cover the desired fraction of traffic. In this paper, we use
reproducible traffic models obtained from a 30-day-long campus trace covering 4
billion flows, to answer these questions. We establish theoretical boundaries
for flow table usage reduction algorithms that classify flows since the first
packet, after reaching a predefined counter threshold or detect elephants by
sampling. An important finding is that simple packet sampling performs
surprisingly well on realistic traffic, reducing the number of flow entries by
a factor up to 400, still covering 80% of the traffic. We also provide an
open-source software package allowing the replication of our experiments or the
performing of similar evaluations for other algorithms or flow distributions.Comment: IFIP Networking Conference (Networking 2021