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Flow Scheduling in Data Center Networks with Time and Energy Constraints: A Software-Defined Network Approach

Author

Listed:
  • Martin Fraga

    (Departamento de Computación, FCEN, Instituto de Investigación en Ciencias de la Computación (ICC), Universidad de Buenos Aires, UBA/CONICET, Buenos Aires C1428, Argentina
    These authors contributed equally to this work.)

  • Matías Micheletto

    (Instituto de Ciencias e Ingeniería de Computación (ICIC), UNS/CONICET, Bahía Blanca B8000, Argentina
    These authors contributed equally to this work.)

  • Andrés Llinás

    (Instituto de Ciencias e Ingeniería de Computación (ICIC), UNS/CONICET, Bahía Blanca B8000, Argentina
    Departamento de Ingeniería Eléctrica y de Computadoras, Universidad Nacional del Sur, Bahía Blanca B8000, Argentina
    These authors contributed equally to this work.)

  • Rodrigo Santos

    (Instituto de Ciencias e Ingeniería de Computación (ICIC), UNS/CONICET, Bahía Blanca B8000, Argentina
    Departamento de Ingeniería Eléctrica y de Computadoras, Universidad Nacional del Sur, Bahía Blanca B8000, Argentina
    These authors contributed equally to this work.)

  • Paula Zabala

    (Departamento de Computación, FCEN, Instituto de Investigación en Ciencias de la Computación (ICC), Universidad de Buenos Aires, UBA/CONICET, Buenos Aires C1428, Argentina
    These authors contributed equally to this work.)

Abstract

Flow scheduling in Data Center Networks (DCN) is a hot topic as cloud computing and virtualization are becoming the dominant paradigm in the increasing demand of digital services. Within the cost of the DCN, the energy demands associated with the network infrastructure represent an important portion. When flows have temporal restrictions, the scheduling with path selection to reduce the number of active switching devices is a NP-hard problem as proven in the literature. In this paper, an heuristic approach to schedule real-time flows in data-centers is proposed, optimizing the temporal requirements while reducing the energy consumption in the network infrastructure via a proper selection of the paths. The experiments show good performance of the solutions found in relation to exact solution approximations based on an integer linear programming model. The possibility of programming the network switches allows the dynamic schedule of paths of flows under the software-defined network management.

Suggested Citation

  • Martin Fraga & Matías Micheletto & Andrés Llinás & Rodrigo Santos & Paula Zabala, 2022. "Flow Scheduling in Data Center Networks with Time and Energy Constraints: A Software-Defined Network Approach," Future Internet, MDPI, vol. 14(2), pages 1-26, February.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:2:p:65-:d:754467
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    References listed on IDEAS

    as
    1. Guoyan Li & Kaixin Li & Yi Liu & Yuheng Pan, 2019. "An Efficient Dynamic Load Balancing Scheme Based on Nash Bargaining in SDN," Future Internet, MDPI, vol. 11(12), pages 1-18, December.
    2. Aaqif Afzaal Abbasi & Hai Jin, 2018. "v-Mapper: An Application-Aware Resource Consolidation Scheme for Cloud Data Centers," Future Internet, MDPI, vol. 10(9), pages 1-17, September.
    Full references (including those not matched with items on IDEAS)

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