Abstract

The orchestration of radio, transport, and cloud resources is a key enabler for efficient service delivery in 5G networks. Orchestration can be achieved with a hierarchical software-defined networking (SDN) control architecture in which a global orchestrator operates above the domain controllers. In such an architecture, the abstraction of resources between the controllers and the orchestrator plays a fundamental role for the system performance. In order to reduce the orchestrator complexity, the controllers should hide as much detail as possible from the orchestrator. On the other hand, the more details are available to the orchestrator the more optimal resource orchestration strategy can be obtained. In order to assess this trade-off, we recently proposed two transport abstraction models, namely big switch (BiS) and virtual link (VL), for centralized radio access networks (C-RANs) with orchestration of radio and transport resources. We observed that VL can provide a more efficient resource orchestration than BiS at the expense of an increased implementation complexity. The contribution of this paper is twofold. We extend the BiS and VL models to make them applicable to any orchestration scenario. Then, we propose a new transport abstraction model, referred to as optical transport transformation (OTT), that aims at achieving efficient resource orchestration with a reduced implementation complexity. We compare the performance of these new abstraction models in a C-RAN use case in which backhaul and fronthaul traffic are carried over a dense wavelength division multiplexing (DWDM) network. Our results prove that in a C-RAN the best choice for the transport abstraction model depends on the availability and the reachability of the radio resources. If radio resources are scarce compared to transport resources, complex transport abstraction models are not needed and a BiS abstraction is the best choice. On the other hand, if radio resources are widely available and reachable, an OTT model guarantees the best overall performance.

© 2016 Optical Society of America

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