TY - GEN
T1 - Survivability Assessment of 5G Network Slicing During Massive Outages
AU - Gajić, Marija
AU - Lange, Stanislav
AU - Vatten, Trond
AU - Furdek, Marija
AU - Heegaard, Poul E.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Mobile networks support variety of heterogeneous services, including the emergency and mission-critical ones. The next generation of mobile networks introduces the concept of network slicing where different services can have a dedicated, logically separated virtual network running over a shared physical infrastructure. Each slice may have a specific set of functional and non-functional requirements including performance, security, resilience, and survivability. Given the importance of emergency services during massive outages caused by a natural disaster, the network operators need an efficient way to evaluate the performance of the sliced network in such adverse circumstances. In this paper, we describe how survivability quantification framework can be applied to assess and compare the performance of different slicing configurations during and after massive outages. We demonstrate our proposal in a simplified use-case scenario where the performance metric for each stage of the recovery is represented with delay and throughput of the clients at a sliced, shared bottleneck. The metrics are acquired from OMNeT++ simulations. Survivability is then obtained from an analytical model and the time until the critical services (for the first responders) are recovered is of particular interest. In the scenario we consider 8 application types, 4 priority levels, and 5 approaches to map clients to slices. The results show significant performance variations between different slicing configurations, both for the critical and non-critical applications and thus highlight the importance of having a slicing configuration optimally tailored to the use case.
AB - Mobile networks support variety of heterogeneous services, including the emergency and mission-critical ones. The next generation of mobile networks introduces the concept of network slicing where different services can have a dedicated, logically separated virtual network running over a shared physical infrastructure. Each slice may have a specific set of functional and non-functional requirements including performance, security, resilience, and survivability. Given the importance of emergency services during massive outages caused by a natural disaster, the network operators need an efficient way to evaluate the performance of the sliced network in such adverse circumstances. In this paper, we describe how survivability quantification framework can be applied to assess and compare the performance of different slicing configurations during and after massive outages. We demonstrate our proposal in a simplified use-case scenario where the performance metric for each stage of the recovery is represented with delay and throughput of the clients at a sliced, shared bottleneck. The metrics are acquired from OMNeT++ simulations. Survivability is then obtained from an analytical model and the time until the critical services (for the first responders) are recovered is of particular interest. In the scenario we consider 8 application types, 4 priority levels, and 5 approaches to map clients to slices. The results show significant performance variations between different slicing configurations, both for the critical and non-critical applications and thus highlight the importance of having a slicing configuration optimally tailored to the use case.
KW - SG network slicing
KW - Survivability
KW - critical infras-tructure
KW - disaster recovery
KW - network resilience
UR - http://www.scopus.com/inward/record.url?scp=85178256040&partnerID=8YFLogxK
U2 - 10.1109/RNDM59149.2023.10293082
DO - 10.1109/RNDM59149.2023.10293082
M3 - Conference contribution
AN - SCOPUS:85178256040
T3 - Proceedings of 2023 13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023
BT - Proceedings of 2023 13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023
A2 - Fischer, Mathias
A2 - Rak, Jacek
A2 - Kassler, Andreas
A2 - Kassler, Andreas
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023
Y2 - 20 September 2023 through 22 September 2023
ER -