TY - GEN
T1 - 5G-Slicer
T2 - 7th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2022
AU - Symeonides, Moysis
AU - Trihinas, Demetris
AU - Pallis, George
AU - Dikaiakos, Marios D.
AU - Psomas, Constantinos
AU - Krikidis, Ioannis
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 5G is emerging as a key mobile network technology offering Gbps transmission rates, lower communication latency, and support for 10-100x more connected devices. The full exploitation of 5G relies on network slicing, a network virtualization technique where operators split a physical network among a wide number and variety of services, in accordance to their individual needs. However, experimentation with 5G-enabled services and measurement of key performance indicators (KPIs) over network slices is extremely challenging as it requires the deployment and coordination of numerous physical devices, including edge and cloud resources. In this paper, we introduce 5G-Slicer; an open and extensible framework for modeling and rapid experimentation of 5G-enabled services via a scalable network slicing emulator. Through modeling abstractions, our solution eases the definition of 5G network slices, virtual and physical fog resources, and the mobility of involved entities. With the blueprint of an emulated testbed at hand, users can create reproducible experiments to evaluate application functionality and KPIs by injecting load, faults and even changing runtime configurations. To show the wide applicability of 5G-Slicer, we introduce a proof-of-concept use-case that encompasses different scenarios for capacity management in a city-scale intelligent transportation service. Evaluation results exploiting real 5G data show that 5G-slicer presents, at most, an 11.7% deviation when comparing actual and emulated network Quality of Service (QoS).
AB - 5G is emerging as a key mobile network technology offering Gbps transmission rates, lower communication latency, and support for 10-100x more connected devices. The full exploitation of 5G relies on network slicing, a network virtualization technique where operators split a physical network among a wide number and variety of services, in accordance to their individual needs. However, experimentation with 5G-enabled services and measurement of key performance indicators (KPIs) over network slices is extremely challenging as it requires the deployment and coordination of numerous physical devices, including edge and cloud resources. In this paper, we introduce 5G-Slicer; an open and extensible framework for modeling and rapid experimentation of 5G-enabled services via a scalable network slicing emulator. Through modeling abstractions, our solution eases the definition of 5G network slices, virtual and physical fog resources, and the mobility of involved entities. With the blueprint of an emulated testbed at hand, users can create reproducible experiments to evaluate application functionality and KPIs by injecting load, faults and even changing runtime configurations. To show the wide applicability of 5G-Slicer, we introduce a proof-of-concept use-case that encompasses different scenarios for capacity management in a city-scale intelligent transportation service. Evaluation results exploiting real 5G data show that 5G-slicer presents, at most, an 11.7% deviation when comparing actual and emulated network Quality of Service (QoS).
KW - Edge Computing
KW - Mobility
KW - Network Slicing
UR - http://www.scopus.com/inward/record.url?scp=85134160420&partnerID=8YFLogxK
U2 - 10.1109/IoTDI54339.2022.00008
DO - 10.1109/IoTDI54339.2022.00008
M3 - Conference contribution
AN - SCOPUS:85134160420
T3 - Proceedings - 7th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2022
SP - 115
EP - 127
BT - Proceedings - 7th ACM/IEEE Conference on Internet of Things Design and Implementation, IoTDI 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 May 2022 through 6 May 2022
ER -