Gil Einziger

Senior Academic

Detecting traffic anomalies with adaptive sampling

Liat Pele, Udi Buczko, Oren Galor, Nokia Israel, Gil Einziger, Ben Gurion

Sampling is a fundamental method to detect traffic anomalies. However, some traffic anomalies (E.g., micro-bursts) require high sampling rates to identify. Unfortunately, current NFV deployments cannot cope with high sampling rates for a prolonged duration of time. Therefore, our work augments Open vSwitch nodes with a light-weight change detection algorithm that determines when to amplify the sampling ratio to detect traffic anomalies. Our preliminary results on real Nokia lab data demonstrate the potential in this method.

Publication language English
Pages 186
Publication status Published - 22.05.2019

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering
Computer Science Applications
Software
Access to Document
10.1145/3319647.3325847
Other files and links
Link to publication in Scopus