Topology-aware scalable resource management in multi-hop dense networks

The current society is becoming increasingly interconnected and hyper-connected. Communication networks are advancing, as well as logistics networks, or even networks for the transportation and distribution of natural resources. One of the key benefits of the evolution of these networks is to bring...

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Detalles Bibliográficos
Autores: Carrascal Acebron, David|||0000-0002-6982-9365, Rojas Sánchez, Elisa|||0000-0002-6385-2628, Carral Pelayo, Juan Antonio|||0000-0002-5545-9463, Martinez Yelmo, Isaias|||0000-0001-9648-8669, Álvarez Horcajo, Joaquín|||0000-0002-8522-9933
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/62409
Acceso en línea:http://hdl.handle.net/10017/62409
https://dx.doi.org/10.1016/j.heliyon.2024.e37490
Access Level:acceso abierto
Palabra clave:Network resource management
Collaborative edge computing
Fog computing
Microgrids
Logistics
Routing
Informática
Computer science
Descripción
Sumario:The current society is becoming increasingly interconnected and hyper-connected. Communication networks are advancing, as well as logistics networks, or even networks for the transportation and distribution of natural resources. One of the key benefits of the evolution of these networks is to bring consumers closer to the source of a resource or service. However, this is not a straightforward task, particularly since networks near final users are usually shaped by heterogeneous nodes, sometimes even in very dense scenarios, which may demand or offer a resource at any given moment. In this paper, we present DEN2NE, a novel algorithm designed for the automatic distribution and reallocation of resources in distributed environments. The algorithm has been implemented with six different criteria in order to adapt it to the specific use case under consideration. The results obtained from DEN2DE are promising, owing to its adaptability and its average execution time, which follows a linear distribution in relation to the topology size.