TY - GEN
T1 - Slicing networks with P4 hardware and software targets
AU - Hauser, Eric
AU - Simon, Manuel
AU - Stubbe, Henning
AU - Gallenmüller, Sebastian
AU - Carle, Georg
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/8/22
Y1 - 2022/8/22
N2 - Running applications over a shared network may lead to unwanted impairments or performance impacts. To avoid these effects, the partitioning of network resources is an integral aspect of effective 5G networks. These virtually partitioned networks or slices allow the provisioning of network resources to guarantee a specific service quality to dedicated virtual networks. Programmable network devices, pushed by new languages such as P4, with their intrinsic flexibility, present themselves as a promising technique to realize slicing. This paper explores three approaches to network slicing and their respective implementation on a P4 soft- and hardware network device. We focus our effort on investigating P4 primitives that do not require the features of a specific P4 device but are available across different P4 targets. Based on our findings, we provide target-specific guidelines minimizing the impact of P4-based slicing for software and hardware targets alike.
AB - Running applications over a shared network may lead to unwanted impairments or performance impacts. To avoid these effects, the partitioning of network resources is an integral aspect of effective 5G networks. These virtually partitioned networks or slices allow the provisioning of network resources to guarantee a specific service quality to dedicated virtual networks. Programmable network devices, pushed by new languages such as P4, with their intrinsic flexibility, present themselves as a promising technique to realize slicing. This paper explores three approaches to network slicing and their respective implementation on a P4 soft- and hardware network device. We focus our effort on investigating P4 primitives that do not require the features of a specific P4 device but are available across different P4 targets. Based on our findings, we provide target-specific guidelines minimizing the impact of P4-based slicing for software and hardware targets alike.
KW - P4
KW - network experiments
KW - network slicing
UR - http://www.scopus.com/inward/record.url?scp=85138306039&partnerID=8YFLogxK
U2 - 10.1145/3538394.3546043
DO - 10.1145/3538394.3546043
M3 - Conference contribution
AN - SCOPUS:85138306039
T3 - 5G-MeMU 2022 - Proceedings of the ACM SIGCOMM 2022 Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases - Part of SIGCOMM 2022
SP - 36
EP - 42
BT - 5G-MeMU 2022 - Proceedings of the ACM SIGCOMM 2022 Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases - Part of SIGCOMM 2022
PB - Association for Computing Machinery, Inc
T2 - 2022 ACM SIGCOMM Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases, 5G-MeMU 2022, co-located with ACM SIGCOMM 2022
Y2 - 22 August 2022
ER -