TY - GEN
T1 - A Case for SDN-based Network Virtualization
AU - Yang, Gyeongsik
AU - Shin, Changyong
AU - Yoo, Yeonho
AU - Yoo, Chuck
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Network virtualization (NV) becomes an essential technology in cloud computing that isolates network flows for tenants. However, because existing NV technologies like overlay do not enable tenants to directly program (i.e., provision, control, and monitor) network resources, software-defined networking (SDN)-based NV (SDN-NV) has been proposed. Despite its great benefits, SDN-NV has been believed to bring considerable overheads due to the network hypervisor (NH). However, to date, there is no definite performance evaluation that proves the overheads of SDN-NV. To this end, this paper comprehensively investigates the performance and overheads of SDN-NV. Our experiment results reveal that SDN-NV provides the data plane performance comparable to or even better (up to 10.5× better TCP throughput) than the existing NV technologies. Also, the results on NH show that its overheads remain mostly constant, even when the number of switches, virtual networks, or network flows increases. In short, our evaluation indicates that the overhead of SDN-NV should not deter its practical use in datacenters.
AB - Network virtualization (NV) becomes an essential technology in cloud computing that isolates network flows for tenants. However, because existing NV technologies like overlay do not enable tenants to directly program (i.e., provision, control, and monitor) network resources, software-defined networking (SDN)-based NV (SDN-NV) has been proposed. Despite its great benefits, SDN-NV has been believed to bring considerable overheads due to the network hypervisor (NH). However, to date, there is no definite performance evaluation that proves the overheads of SDN-NV. To this end, this paper comprehensively investigates the performance and overheads of SDN-NV. Our experiment results reveal that SDN-NV provides the data plane performance comparable to or even better (up to 10.5× better TCP throughput) than the existing NV technologies. Also, the results on NH show that its overheads remain mostly constant, even when the number of switches, virtual networks, or network flows increases. In short, our evaluation indicates that the overhead of SDN-NV should not deter its practical use in datacenters.
KW - Cloud computing
KW - Network virtualization
KW - Performance evaluation
KW - Software-defined networking
UR - https://www.scopus.com/pages/publications/85123160961
U2 - 10.1109/MASCOTS53633.2021.9614291
DO - 10.1109/MASCOTS53633.2021.9614291
M3 - Conference contribution
AN - SCOPUS:85123160961
T3 - Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
BT - Proceedings - 29th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2021
PB - IEEE Computer Society
T2 - 29th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2021
Y2 - 3 November 2021 through 5 November 2021
ER -