The next generation of cellular networks are expected to support multiple user-oriented services that have various quality of service (QoS) requirements, yet must be serviced by a single infrastructure. To achieve this, network virtualization can play an important role by partitioning/slicing a single physical network resource into multiple virtual networks such that each of the slices can support various services independently. The main contribution of this work is an implementation of static and dynamic resource allocation schemes for different slices supporting different services. We use this implementation to study the effects of increasing the number of network slices on the number of optimization trigger events. Moreover, we propose a non-uniform resource sharing agreement (policy) between the participating network slices and investigate how these sharing agreements affect the frequency of optimization trigger events.
SoftSLICE: Policy-based dynamic spectrum slicing in 5G cellular networks / Gebremariam, A. A.; Chowdhury, M.; Usman, M.; Goldsmith, A.; Granelli, F.. - 2018-:(2018), pp. 1-6. (Intervento presentato al convegno 2018 IEEE International Conference on Communications, ICC 2018 tenutosi a USA nel 2018) [10.1109/ICC.2018.8422148].
SoftSLICE: Policy-based dynamic spectrum slicing in 5G cellular networks
Gebremariam A. A.;Usman M.;Granelli F.
2018-01-01
Abstract
The next generation of cellular networks are expected to support multiple user-oriented services that have various quality of service (QoS) requirements, yet must be serviced by a single infrastructure. To achieve this, network virtualization can play an important role by partitioning/slicing a single physical network resource into multiple virtual networks such that each of the slices can support various services independently. The main contribution of this work is an implementation of static and dynamic resource allocation schemes for different slices supporting different services. We use this implementation to study the effects of increasing the number of network slices on the number of optimization trigger events. Moreover, we propose a non-uniform resource sharing agreement (policy) between the participating network slices and investigate how these sharing agreements affect the frequency of optimization trigger events.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione