TY - GEN
T1 - Netboa
T2 - 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, NetAI 2019, Part of SIGCOMM 2019
AU - Zerwas, Johannes
AU - Kalmbach, Patrick
AU - Henkel, Laurenz
AU - Rétvári, Gábor
AU - Kellerer, Wolfgang
AU - Blenk, Andreas
AU - Schmid, Stefan
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/8/14
Y1 - 2019/8/14
N2 - Communication networks have not only become a critical infrastructure of our digital society, but are also increasingly complex and hence error-prone. This has recently motivated the study of more automated and self-driving networks: networks which measure, analyze, and control themselves in an adaptive manner, reacting to changes in the environment. In particular, such networks hence require a mechanism to recognize potential performance issues. This paper presents NetBOA, an adaptive and data-driven approach to measure network performance, allowing the network to identify bottlenecks and to perform automated what-if analysis, exploring improved network configurations. As a case study, we demonstrate how the NetBOA approach can be used to benchmark a popular software switch, Open vSwitch. We report on our implementation and evaluation, and show that NetBOA can find performance issues efficiently, compared to a non-data-driven approach. Our results hence indicate that NetBOA may also be useful to identify algorithmic complexity attacks.
AB - Communication networks have not only become a critical infrastructure of our digital society, but are also increasingly complex and hence error-prone. This has recently motivated the study of more automated and self-driving networks: networks which measure, analyze, and control themselves in an adaptive manner, reacting to changes in the environment. In particular, such networks hence require a mechanism to recognize potential performance issues. This paper presents NetBOA, an adaptive and data-driven approach to measure network performance, allowing the network to identify bottlenecks and to perform automated what-if analysis, exploring improved network configurations. As a case study, we demonstrate how the NetBOA approach can be used to benchmark a popular software switch, Open vSwitch. We report on our implementation and evaluation, and show that NetBOA can find performance issues efficiently, compared to a non-data-driven approach. Our results hence indicate that NetBOA may also be useful to identify algorithmic complexity attacks.
KW - Automated network measurements
KW - Automated performance analysis
KW - Bayesian optimization
KW - Self-driving networks
UR - https://www.scopus.com/pages/publications/85072026321
U2 - 10.1145/3341216.3342207
DO - 10.1145/3341216.3342207
M3 - Conference contribution
AN - SCOPUS:85072026321
T3 - NetAI 2019 - Proceedings of the 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, Part of SIGCOMM 2019
SP - 8
EP - 14
BT - NetAI 2019 - Proceedings of the 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, Part of SIGCOMM 2019
PB - Association for Computing Machinery
Y2 - 23 August 2019
ER -