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CNS-AOM: Design, Implementation and Integration of an Architecture for Orchestration and Management of Cloud-Network Slices

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Abstract

Cloud-Network Slice (CNS) is defined as an end-to-end infrastructure composed by computing, networking, and storage resources and it is expected to be a key enabler for novel verticals such as Industry 4.0, IoT and Vehicular Networks. This paper presents the design, implementation and integration of the Architecture for Orchestration and Management of Cloud-Network Slices (CNS-AOM), a modular architecture to orchestrate and manage slice resources and services in CNSs. The CNS-AOM is designed and implemented considering three important characteristics: (i) the business model called Slice-as-a-Service (SlaaS); (ii) the multiple administrative and technological domains; and (iii) the slice elasticity, which means the capacity of dynamically growing and shrinking the slice resources to improve service performance. To prove the feasibility of our proposal, two Proofs of Concept (PoC) are implemented in real environments to validate the CNS-AOM. First, an end-to-end content distribution service (CDN) is deployed across three different cities in Brazil to emphasize the multiple domains. Second, we present an IoT service using a fully-featured commercial service platform called dojot, which is instantiated and orchestrated by the proposed architecture. The dojot slice is instantiated overseas in four cities across two countries. The evaluation for the CDN slice considers the appropriate metrics that should be monitored and the actual services that should be instantiated to meet the end-user’s requirements depending on its location. Moreover, in the dojot slice, elasticity operations (vertical and horizontal) are tested and evaluated along with the time taken to deploy the slice infrastructure and the service. The main contributions of this paper are: (i) the design, implementation and integration of the CNS-AOM; (ii) the orchestration control-loop of the slice resources; and (iii) the execution of real proof-of-concept scenarios that demonstrate the feasibility of the CNS-AOM to instantiate and orchestrate services across geographically-distanced cities.

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Notes

  1. http://www.h2020-necos.eu/.

  2. Slice resources mean the slice parts, i.e, the components that make part of the infrastructure of the slice. Features such traffic steering, load balancing, caching and others may be deployed by the tenant and are beyond the scope of the slice resources.

  3. http://www.5gex.eu/.

  4. http://sonata-nfv.eu/.

  5. http://www.it.uc3m.es/wnl/5gnorma/.

  6. http://5g-transformer.eu/.

  7. https://5g-pagoda.aalto.fi/.

  8. https://slicenet.eu/.

  9. http://www.h2020-necos.eu/.

  10. http://clayfour.ee.ucl.ac.uk/lattice/.

  11. All the source code used in this paper is available at https://gitlab.com/necos/demos/musts.

  12. https://www.cncf.io.

  13. http://www.maps.upc.edu/public/MLO_demo_video_with_audio.mp4.

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Acknowledgements

Work funded through the H2020 4th EU-BR Collaborative Call, under the grant agreement no. 777067 (NECOS - Novel Enablers for Cloud Slicing). This work was financed also by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES).

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Correspondence to André Luiz Beltrami Rocha.

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Rocha, A.L.B., Cesila, C.H., Maciel, P.D. et al. CNS-AOM: Design, Implementation and Integration of an Architecture for Orchestration and Management of Cloud-Network Slices. J Netw Syst Manage 30, 34 (2022). https://doi.org/10.1007/s10922-022-09641-z

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