TY - GEN
T1 - Detecting traffic anomalies with adaptive sampling
AU - Pele, Liat
AU - Buczko, Udi
AU - Galor, Oren
AU - Israel, Nokia
AU - Einziger, Gil
AU - Gurion, Ben
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/5/22
Y1 - 2019/5/22
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85067101281
U2 - 10.1145/3319647.3325847
DO - 10.1145/3319647.3325847
M3 - Conference contribution
AN - SCOPUS:85067101281
T3 - SYSTOR 2019 - Proceedings of the 12th ACM International Systems and Storage Conference
SP - 186
BT - SYSTOR 2019 - Proceedings of the 12th ACM International Systems and Storage Conference
PB - Association for Computing Machinery, Inc
T2 - 12th ACM International Systems and Storage Conference, SYSTOR 2019
Y2 - 3 June 2019 through 5 June 2019
ER -