IT and Multi-layer Online Resource Allocation and Offline Planning in Metropolitan Networks

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Abstract

Metropolitan networks are undergoing a major technological breakthrough leveraging the capabilities of software-defined networking (SDN) and network function virtualization (NFV). NFV permits the deployment of virtualized network functions (VNFs) on commodity hardware appliances which can be combined with SDN flexibility and programmability of the network infrastructure. SDN/NFV-enabled networks require decision-making in two time scales: short-Term online resource allocation and mid-To-long term offline planning. In this paper, we first tackle the dimensioning of SDN/NFV-enabled metropolitan networks paying special attention to the role that latency plays in the capacity planning. We focus on a specific use-case: The metropolitan network that covers the Murcia-Alicante Spanish regions. Then, we propose a latency-Aware multilayer service-chain allocation (LA-ML-SCA) algorithm to explore a range of maximum latency requirements and their impact on the resources for dimensioning the metropolitan network. We observe that design costs increase for low latency requirements as more data center facilities need to be spread to get closer to the network edge, reducing the economies of scale on the IT infrastructure. Subsequently, we review our recent joint computation of multi-site VNF placement and multilayer resource allocation in the deployment of a network service in a metro network. Specifically, a set of subroutines contained in LA-ML-SCA are experimentally validated in a network optimization-As-A-service architecture that assists an Open-Source MANO instance, virtual infrastructure managers and WAN controllers in a metro network test-bed.

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Garrich, M., Romero-Gazquez, J. L., Moreno-Muro, F. J., Hernandez-Bastida, M., Delgado, M. V. B., Bravalheri, A., … Marino, P. P. (2020). IT and Multi-layer Online Resource Allocation and Offline Planning in Metropolitan Networks. Journal of Lightwave Technology, 38(12), 3190–3199. https://doi.org/10.1109/JLT.2020.2990066

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