IP Network Management from the Perspective of Distributed Artificial Intelligence: State of the Art

Juan Carlos Zegarra-Vásquez, Nestor Mamani-Macedo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

An approach to study Distributed artificial intelligence is through software agent-based intelligent systems. Instead of having a large centralized system that collects complete system information, there is a small number of subsystems or agents, which are focused on the effort to cooperate to solve a given problem. Agents can communicate with each other, exchange views and find various strategies to obtain a specific solution. Due to the exponential growth of network devices and the massive use of broadband networks, current centralized management systems are reaching limits in terms of managing the amount of information to be managed, which is why distributed management based on the paradigm of intelligent agents can be applied in this domain. In the literature, there are several experimental and academic prototypes that attempt to demonstrate how the use of distributed artificial intelligence can be an interesting alternative to the classic centralized network management systems. This article benchmarks these prototypes, emphasizing two aspects (i) the strategy and (ii) the inherent functional blocks of each proposal.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 5th Brazilian Technology Symposium - Emerging Trends, Issues, and Challenges in the Brazilian Technology
EditoresYuzo Iano, Rangel Arthur, Osamu Saotome, Guillermo Kemper, Reinaldo Padilha França
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas153-160
Número de páginas8
ISBN (versión impresa)9783030575472
DOI
EstadoPublicada - 2021
Publicado de forma externa
Evento5th Brazilian Technology Symposium, BTSym 2019 - Campinas, Brasil
Duración: 22 oct. 201924 oct. 2019

Serie de la publicación

NombreSmart Innovation, Systems and Technologies
Volumen201
ISSN (versión impresa)2190-3018
ISSN (versión digital)2190-3026

Conferencia

Conferencia5th Brazilian Technology Symposium, BTSym 2019
País/TerritorioBrasil
CiudadCampinas
Período22/10/1924/10/19

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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