Revenue Maximization in Delay-Aware Computation Offloading Among Service Providers With Fog Federation

[EN] In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog node allocates its computing resources to the end-user in its proximity, whil...

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Detalles Bibliográficos
Autores: Mukherjee, Mithun, Kumar, Vikas, Lloret, Jaime, Zhang, Qi
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/189387
Acceso en línea:https://riunet.upv.es/handle/10251/189387
Access Level:acceso abierto
Palabra clave:Task analysis
Delays
Computational modeling
Computational efficiency
Pricing
Frequency modulation
Collaboration
Fog computing
Fog federation
Computational offloading
Delay-sensitive tasks
Descripción
Sumario:[EN] In this letter, we study the computational offloading scheme for the delay-aware tasks of the end-users in the fog computing network. We consider a fog federation of different service providers where an individual fog node allocates its computing resources to the end-user in its proximity, while a fog manager coordinates the load balancing among the fog nodes over the entire network. At first, an individual fog node aims to maximize its revenue by selling the computational resources to the end-user in a distributed manner without any global knowledge of the network. To further maximize the overall revenue considering all fog nodes in the fog federation, the fog manager utilizes the remaining computing resources of the underloaded fog nodes. The extensive simulation results show the revenue improvement leveraging fog federation over entire network while maintaining the same and even better delay-performance for the end-users.