Planificación descentralizada basada en sistemas multiagente para orquestadores en la niebla

  1. O. Casquero 1
  2. A. Armentia 1
  3. I. Sarachaga 1
  4. D. Orive 1
  5. M. Marcos 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Liburua:
XL Jornadas de Automática: libro de actas. Ferrol, 4-6 de septiembre de 2019
  1. Jose Luis Calvo Rolle (coord.)
  2. Jose Luis Casteleiro Roca (coord.)
  3. María Isabel Fernández Ibáñez (coord.)
  4. Óscar Fontenla Romero (coord.)
  5. Esteban Jove Pérez (coord.)
  6. Alberto José Leira Rejas (coord.)
  7. José Antonio López Vázquez (coord.)
  8. Vanesa Loureiro Vázquez (coord.)
  9. María Carmen Meizoso López (coord.)
  10. Francisco Javier Pérez Castelo (coord.)
  11. Andrés José Piñón Pazos (coord.)
  12. Héctor Quintián Pardo (coord.)
  13. Juan Manuel Rivas Rodríguez (coord.)
  14. Benigno Rodríguez Gómez (coord.)
  15. Rafael Alejandro Vega Vega (coord.)

Argitaletxea: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-716-9

Argitalpen urtea: 2019

Orrialdeak: 126-132

Biltzarra: Jornadas de Automática (40. 2019. Ferrol)

Mota: Biltzar ekarpena

Laburpena

Fog computing is a paradigm that takes advantage of the fast response times of moving the computing infrastructure closer to the devices that collect the data, and the storage and processing features of the cloud. Fog computing can be used to improve the controllability of automation processes by introducing a higher-level control loop: Fog-in-the-loop (FIL). FIL allows capturing data from the plant, processing it to extract value-added information and feedback actions to the plant. Therefore, FIL applications are context-aware applications that require the deployment of distributed components and dynamic reconfiguration. This paper describes a custom scheduler for Kubernetes (K8s) orchestrator that distributes the scheduling task among the processing nodes by means of a multi-agent system. This new scheduling approach proved to be faster than the centralized scheduling approach used by the default scheduler of K8s.