Skip to main content
SpringerLink
Log in

Distributed Auction-Based SFC Placement in a Multi-domain 5G Environment

  • Original Research
  • Published:
SN Computer Science Aims and scope Submit manuscript

Abstract

The fifth generation of mobile networks (5G) brings an evolution of network service provisioning through a new communication paradigm, which enables the development of new applications and improves users’ experience. With 5G, it is envisioned that networks will provide services accessed by a variety of mobile users, some of such services requiring ultra-low latency and very high reliability. 5G also enables massive connectivity of sensors and actuators in the Internet of Things and Cyber-physical Systems scenarios, standing for massive Machine-Type Communication applications. Network Function Virtualization (NFV) is an emerging and promising solution to deal with such demands for flexible and agile service provisioning by replacing dedicated hardware implementations with software instances based on virtualization. A well-known challenge in NFV is the resource allocation problem. In particular, the Service Function Chain (SFC) placement problem is considered a major challenge, even more, when considering the distributed placement in a multi-administrative domain context. We propose a novel solution for the SFC placement problem called Multi-Domain Distributed Auction-Based SFC Placement Algorithm, which relies on an auction-based strategy. The proposed algorithm targets different 5G application scenarios with a focus on solving the SFC placement problem taking into consideration the dynamic aspects of unpredictable requests and the management of the entire auction process to decide which domain will be selected to meet the required SFC. Evaluations were carried out in a simulated environment aiming at assessing the performance of the algorithm in terms of the profit for each service provider during the allocation of the requested services in the respective domain that the service provider is responsible for. Results showed that adopting an auction-based mechanism, and thus allowing a domain to outsource the provision of requested services, successfully reduced the total cost of the service execution in a multi-domain environment. The auction-based approach increases the service provider profit by around 20% in the tested scenarios. Moreover, the number of services placed increases in comparison to the approach where all the services must be executed in the decision domain (with no auction).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Yang S, Li F, Trajanovski S, Yahyapour R, Fu X. Recent advances of resource allocation in network function virtualization. IEEE Trans Parallel Distrib Syst. 2020;32(2):295–314. https://doi.org/10.1109/TPDS.2020.3017001.

    Article  Google Scholar 

  2. Benkacem I, Taleb T, Bagaa M, Flinck H. Optimal VNFs placement in CDN slicing over multi-cloud environment. IEEE J Sel Areas Commun. 2018;36(3):616–27. https://doi.org/10.1109/JSAC.2018.2815441.

    Article  Google Scholar 

  3. Reyhanian N, Farmanbar H, Mohajer S, Luo Z-Q. Joint resource allocation and routing for service function chaining with in-subnetwork processing. In: ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4990–4994 (2020). https://doi.org/10.1109/ICASSP40776.2020.9054706 . IEEE

  4. ETSI: ETSI Network Functions Virtualisation (NFV) Release 2; Management and Orchestration; Architectural Framework Specification; 2021. https://www.etsi.org/deliver/etsi_gs/nfv/001_099/006/02.01.01_60/gs_nfv006v020101p.pdf

  5. Zhao D, Liao D, Sun G, Xu S. Towards resource-efficient service function chain deployment in cloud-fog computing. IEEE Access. 2018;6:66754–66. https://doi.org/10.1109/ACCESS.2018.2875124

  6. Mountaser G, Condoluci M, Mahmoodi T, Dohler M, Mings I. Cloud-ran in support of urllc. 2017;1–6. https://doi.org/10.1109/GLOCOMW.2017.8269135

  7. Alves Esteves JJ, Boubendir A, Guillemin F, Sens P. Heuristic for edge-enabled network slicing optimization using the “power of two choices”, pp. 1–9 (2020). https://doi.org/10.23919/CNSM50824.2020.9269099

  8. Abu-Lebdeh M, Naboulsi D, Glitho R, Tchouati CW. NFV orchestrator placement for geo-distributed systems. In: 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA), pp. 1–5 (2017). https://doi.org/10.1109/NCA.2017.8171391 . IEEE

  9. Franco MF, Scheid EJ, Granville LZ, Stiller B. BRAIN: Blockchain-based reverse auction for infrastructure supply in virtual network functions-as-a-service. In: 2019 IFIP Networking Conference (IFIP Networking), pp. 1–9 (2019). https://doi.org/10.23919/IFIPNetworking.2019.8816843. IEEE

  10. Sun G, Li Y, Liao D, Chang V. Service function chain orchestration across multiple domains: a full mesh aggregation approach. IEEE Trans Netw Serv Manage. 2018;15(3):1175–91. https://doi.org/10.1109/TNSM.2018.2861717.

    Article  Google Scholar 

  11. Gao C, Cankaya HC, Jue JP. Survivable inter-domain routing based on topology aggregation with intra-domain disjointness information in multi-domain optical networks. J Opt Commun Netw. 2014;6(7):619–28. https://doi.org/10.1364/JOCN.6.000619.

    Article  Google Scholar 

  12. Hamzaoui I, Duthil B, Courboulay V, Medromi H. A survey on the current challenges of energy-efficient cloud resources management. SN Comput. Sci. 2020;1(2). https://doi.org/10.1007/s42979-020-0078-9

  13. Sun G, Li Y, Yu H, Vasilakos A.V, Du X, Guizani M. Energy-efficient and traffic-aware service function chaining orchestration in multi-domain networks. Future Gener Comput Syst. 2019;91:347–60. https://doi.org/10.1016/j.future.2018.09.037

  14. Liu Y, Zhang H, Chang D, Hu H. GDM: a general distributed method for cross-domain service function chain embedding. IEEE Trans Netw Serv Manag. 2020;17(3):1446–59. https://doi.org/10.1109/TNSM.2020.2993364.

    Article  Google Scholar 

  15. Zavlanos M.M, Spesivtsev L, Pappas GJ. A distributed auction algorithm for the assignment problem. In: 2008 47th IEEE Conference on Decision and Control, pp. 1212–1217 (2008). https://doi.org/10.1109/CDC.2008.4739098

  16. Borjigin W, Ota K, Dong M. In broker we trust: a double-auction approach for resource allocation in NFV markets. IEEE Trans Netw Serv Manag. 2018;15(4):1322–33. https://doi.org/10.1109/TNSM.2018.2882535

  17. Avasalcai C, Tsigkanos C, Dustdar S. Decentralized resource auctioning for latency-sensitive edge computing. In: 2019 IEEE International Conference on Edge Computing (EDGE), pp. 72–76 (2019). https://doi.org/10.1109/EDGE.2019.00027

  18. ETSI: Network Functions Virtualisation (NFV) Release 3; Management and Orchestration; Multiple Administrative Domain Aspect Interfaces Specification (2018). https://www.etsi.org/deliver/etsi_gs/nfv-ifa/001_099/030/03.01.01_60/gs_nfv-ifa030v030101p.pdf

  19. ETSI: MEC 003—V3.1.1—Multi-access Edge Computing (MEC); Framework and Reference Architecture. Technical report, ETSI, Valbonne/França (2022). https://www.etsi.org/deliver/etsi_gs/MEC/001_099/003/03.01.01_60/gs_MEC003v030101p.pdf

  20. Zheng S, McAven L, Mu Y. First price sealed bid auction without auctioneers. In: Proceedings of the 2007 International Conference on Wireless Communications and Mobile Computing, pp. 127–131 (2007)

  21. Caldiera VRBG, Rombach HD. The goal question metric approach. Encyclop Softw Eng, pp. 528–532 (1994)

  22. Vieira JL, Battisti ALE, Macedo ELC, Pires PF, Muchaluat-Saade DC, Delicato FC, Oliveira ACB. Dynamic and mobility-aware vnf placement in 5g-edge computing environments. In: 2023 IEEE 9th International Conference on Network Softwarization (NetSoft), pp. 53–61 (2023). https://doi.org/10.1109/NetSoft57336.2023.10175437

Download references

Acknowledgements

This work was partially funded by DELL EMC, CAPES, CNPq, FAPERJ, and FAPESP. Professors Débora Muchaluat-Saade, Flavia Delicato, and Paulo Pires are CNPq Fellows. Professors Débora Muchaluat-Saade and Flavia Delicato are also FAPERJ Fellows.

Funding

This study was partially funded by DELL EMC (ID FEC 4717), FAPESP (Grant No. 2015/24144-7), and FAPERJ (Grant No. 200.972/2022).

Author information

Authors and Affiliations

  1. MídiaCom Laboratory, Universidade Federal Fluminense, Niterói, Brazil

    Anselmo L. E. Battisti, Juan Lucas Vieira, Paulo F. Pires, Débora C. Muchaluat-Saade & Flavia C. Delicato

  2. High-Speed Networks Laboratory, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

    Evandro L. C. Macedo

  3. Dell EMC Research Center, Rio de Janeiro, Brazil

    Julia Noce, Paulo F. Pires & Ana C. B. Oliveira

Authors
  1. Evandro L. C. Macedo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anselmo L. E. Battisti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan Lucas Vieira
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Julia Noce
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Paulo F. Pires
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Débora C. Muchaluat-Saade
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ana C. B. Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Flavia C. Delicato
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Flavia C. Delicato.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the topical collection “Dependable Cyber-Physical Systems and Cyber Security” guest edited by Deepak Puthal and Niranjan K. Ray.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Macedo, E.L.C., Battisti, A.L.E., Vieira, J.L. et al. Distributed Auction-Based SFC Placement in a Multi-domain 5G Environment. SN COMPUT. SCI. 5, 48 (2024). https://doi.org/10.1007/s42979-023-02291-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s42979-023-02291-1

Keywords

Search

Navigation