IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v14y2022i12p361-d989483.html
   My bibliography  Save this article

A Novel Strategy for VNF Placement in Edge Computing Environments

Author

Listed:
  • Anselmo Luiz Éden Battisti

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Evandro Luiz Cardoso Macedo

    (High-Speed Networks Laboratory, Systems Engineering and Computer Science Program (PESC), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-914, Brazil)

  • Marina Ivanov Pereira Josué

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Hugo Barbalho

    (Dell EMC Research Center, Rua Antônio Barros de Castro, 119, Cidade Universitária, Rio de Janeiro 21941-615, Brazil)

  • Flávia C. Delicato

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Débora Christina Muchaluat-Saade

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Paulo F. Pires

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Douglas Paulo de Mattos

    (MidiaCom Laboratory, Institute of Computing, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil)

  • Ana Cristina Bernardo de Oliveira

    (Dell EMC Research Center, Rua Antônio Barros de Castro, 119, Cidade Universitária, Rio de Janeiro 21941-615, Brazil)

Abstract

Network function virtualization (NFV) is a novel technology that virtualizes computing, network, and storage resources to decouple the network functions from the underlying hardware, thus allowing the software implementation of such functions to run on commodity hardware. By doing this, NFV provides the necessary flexibility to enable agile, cost-effective, and on-demand service delivery models combined with automated management. Different management and orchestration challenges arise in such virtualized and distributed environments. A major challenge in the selection of the most suitable edge nodes is that of deploying virtual network functions (VNFs) to meet requests from multiple users. This article addresses the VNF placement problem by providing a novel integer linear programming (ILP) optimization model and a novel VNF placement algorithm. In our definition, the multi-objective optimization problem aims to (i) minimize the energy consumption in the edge nodes; (ii) minimize the total latency; and (iii) reducing the total cost of the infrastructure. Our new solution formulates the VNF placement problem by taking these three objectives into account simultaneously. In addition, the novel VNF placement algorithm leverages VNF sharing, which reuses VNF instances already placed to potentially reduce computational resource usage. Such a feature is still little explored in the community. Through simulation, numerical results show that our approach can perform better than other approaches found in the literature regarding resource consumption and the number of SFC requests met.

Suggested Citation

  • Anselmo Luiz Éden Battisti & Evandro Luiz Cardoso Macedo & Marina Ivanov Pereira Josué & Hugo Barbalho & Flávia C. Delicato & Débora Christina Muchaluat-Saade & Paulo F. Pires & Douglas Paulo de Matto, 2022. "A Novel Strategy for VNF Placement in Edge Computing Environments," Future Internet, MDPI, vol. 14(12), pages 1-20, November.
  • Handle: RePEc:gam:jftint:v:14:y:2022:i:12:p:361-:d:989483
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/14/12/361/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/14/12/361/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jaeggi, D.M. & Parks, G.T. & Kipouros, T. & Clarkson, P.J., 2008. "The development of a multi-objective Tabu Search algorithm for continuous optimisation problems," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1192-1212, March.
    2. Aris Leivadeas & George Kesidis & Mohamed Ibnkahla & Ioannis Lambadaris, 2019. "VNF Placement Optimization at the Edge and Cloud †," Future Internet, MDPI, vol. 11(3), pages 1-23, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu Wang & Bin Shi & Yili Fang, 2023. "Distributed Systems for Emerging Computing: Platform and Application," Future Internet, MDPI, vol. 15(4), pages 1-2, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shen, Xin & Chen, Jin-Ge & Zhu, Xiao-Cheng & Liu, Peng-Yin & Du, Zhao-Hui, 2015. "Multi-objective optimization of wind turbine blades using lifting surface method," Energy, Elsevier, vol. 90(P1), pages 1111-1121.
    2. Symeon Papavassiliou, 2020. "Software Defined Networking (SDN) and Network Function Virtualization (NFV)," Future Internet, MDPI, vol. 12(1), pages 1-3, January.
    3. Fischer, Gunter Reinald & Kipouros, Timoleon & Savill, Anthony Mark, 2014. "Multi-objective optimisation of horizontal axis wind turbine structure and energy production using aerofoil and blade properties as design variables," Renewable Energy, Elsevier, vol. 62(C), pages 506-515.
    4. Lee, Sangkeum & Cho, Hong-Yeon & Har, Dongsoo, 2018. "Operation optimization with jointly controlled modules powered by hybrid energy source: A case study of desalination," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3070-3080.
    5. Capitanescu, F. & Marvuglia, A. & Benetto, E. & Ahmadi, A. & Tiruta-Barna, L., 2017. "Linear programming-based directed local search for expensive multi-objective optimization problems: Application to drinking water production plants," European Journal of Operational Research, Elsevier, vol. 262(1), pages 322-334.
    6. Long, Jiancheng & Szeto, W.Y. & Huang, Hai-Jun, 2014. "A bi-objective turning restriction design problem in urban road networks," European Journal of Operational Research, Elsevier, vol. 237(2), pages 426-439.
    7. Prah Klemen & Keshavarzsaleh Abolfazl & Kramberger Tomaž & Jereb Borut & Dragan Dejan, 2018. "Optimal Bus Stops’ Allocation: A School Bus Routing Problem with Respect to Terrain Elevation," Logistics, Supply Chain, Sustainability and Global Challenges, Sciendo, vol. 9(2), pages 1-15, October.
    8. Feng, Bo & Fan, Zhi-Ping & Li, Yanzhi, 2011. "A decision method for supplier selection in multi-service outsourcing," International Journal of Production Economics, Elsevier, vol. 132(2), pages 240-250, August.
    9. Tarik Chargui & Abdelghani Bekrar & Mohamed Reghioui & Damien Trentesaux, 2019. "Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption," Sustainability, MDPI, vol. 11(11), pages 1-23, June.
    10. Ahmad Rodzi MAHMUD & Vini INDRIASARI, 2009. "Facility Location Models Development To Maximize Total Service Area," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 4(1S), pages 87-100, April.
    11. Aymeric Blot & Marie-Éléonore Kessaci & Laetitia Jourdan, 2018. "Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation," Journal of Heuristics, Springer, vol. 24(6), pages 853-877, December.
    12. Manuel Lozano, 2021. "Comments on: Tabu search tutorial. A Graph Drawing Application," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 357-362, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:14:y:2022:i:12:p:361-:d:989483. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.