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Novel resource and energy management for 5G integrated backhaul/fronthaul (5G-Crosshaul)

: Li, X.; Ferdous, R.; Chiasserini, C.F.; Casetti, C.E.; Moscatelli, F.; Landi, G.; Casellas, R.; Sakaguchi, K.; Chundrigar, S.B.; Vilalta, R.; Mangues, J.; Garcia-Saavedra, A.; Costa-Perez, X.; Goratti, L.; Siracusa, D.


Jamalipour, A. ; Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Communications Workshops, ICC 2017 : 21-25 May 2017, Paris
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-1525-2
ISBN: 978-1-5090-1526-9
International Conference on Communications (ICC) <2017, Paris>
International Workshop on 5G RAN Design <3, 2017, Paris>
Fraunhofer HHI ()

The integration of both fronthaul and backhaul into a single transport network (namely, 5G-Crosshaul) is envisioned for the future 5G transport networks. This requires a fully integrated and unified management of the fronthaul and backhaul resources in a cost-efficient, scalable and flexible way through the deployment of an SDN/NFV control framework. This paper presents the designed 5G-Crosshaul architecture, two selected SDN/NFV applications targeting for cost-efficient resource and energy usage: the Resource Management Application (RMA) and the Energy Management and Monitoring Application (EMMA). The former manages 5G-Crosshaul resources (network, computing and storage resources). The latter is a special version of RMA with the focus on the objectives of optimizing the energy consumption and minimizing the energy footprint of the 5G-Crosshaul infrastructure. Besides, EMMA is applied to the mmWave mesh network and the high speed train scenarios. In particular, we present the key application design with their main components and the interactions with each other and with the control plane, and then we present the proposed application optimization algorithms along with initial results. The first results demonstrate that the proposed RMA is able to cost-efficiently utilize the Crosshaul resources of heterogeneous technologies, while EMMA can achieve significant energy savings through energy-efficient routing of traffic flows. For experiments in real system, we also set up Proof of Concepts (PoCs) for both applications in order to perform real trials in the field.