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Integrated Resource Management for Fog Networks

In this paper, we consider integrated resource management for fog networks inclusive of intelligent energy perception, service level agreement (SLA) planning and replication-based hotspot offload (RHO). In the beginning, we propose an intelligent energy perception scheme which dynamically classifies...

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Detalles Bibliográficos
Autores principales: Yang, Jui-Pin, Su, Hui-Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950010/
https://www.ncbi.nlm.nih.gov/pubmed/35336575
http://dx.doi.org/10.3390/s22062404
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author Yang, Jui-Pin
Su, Hui-Kai
author_facet Yang, Jui-Pin
Su, Hui-Kai
author_sort Yang, Jui-Pin
collection PubMed
description In this paper, we consider integrated resource management for fog networks inclusive of intelligent energy perception, service level agreement (SLA) planning and replication-based hotspot offload (RHO). In the beginning, we propose an intelligent energy perception scheme which dynamically classifies the fog nodes into a hot set, a warm set or a cold set, based on their load conditions. The fog nodes in the hot set are responsible for a quality of service (QoS) guarantee and the fog nodes in the cold set are maintained at a low-energy state to save energy consumption. Moreover, the fog nodes in the warm set are used to balance the QoS guarantee and energy consumption. Secondly, we propose an SLA mapping scheme which effectively identifies the SLA elements with the same semantics. Finally, we propose a replication-based load-balancing scheme, namely RHO. The RHO can leverage the skewed access pattern caused by the hotspot services. In addition, it greatly reduces communication overheads because the load conditions are updated only when the load variations exceed a specific threshold. Finally, we use computer simulations to compare the performance of the RHO with other schemes under a variety of load conditions. In a word, we propose a comprehensive and feasible solution that contributes to the integrated resource management of fog networks.
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spelling pubmed-89500102022-03-26 Integrated Resource Management for Fog Networks Yang, Jui-Pin Su, Hui-Kai Sensors (Basel) Communication In this paper, we consider integrated resource management for fog networks inclusive of intelligent energy perception, service level agreement (SLA) planning and replication-based hotspot offload (RHO). In the beginning, we propose an intelligent energy perception scheme which dynamically classifies the fog nodes into a hot set, a warm set or a cold set, based on their load conditions. The fog nodes in the hot set are responsible for a quality of service (QoS) guarantee and the fog nodes in the cold set are maintained at a low-energy state to save energy consumption. Moreover, the fog nodes in the warm set are used to balance the QoS guarantee and energy consumption. Secondly, we propose an SLA mapping scheme which effectively identifies the SLA elements with the same semantics. Finally, we propose a replication-based load-balancing scheme, namely RHO. The RHO can leverage the skewed access pattern caused by the hotspot services. In addition, it greatly reduces communication overheads because the load conditions are updated only when the load variations exceed a specific threshold. Finally, we use computer simulations to compare the performance of the RHO with other schemes under a variety of load conditions. In a word, we propose a comprehensive and feasible solution that contributes to the integrated resource management of fog networks. MDPI 2022-03-21 /pmc/articles/PMC8950010/ /pubmed/35336575 http://dx.doi.org/10.3390/s22062404 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Yang, Jui-Pin
Su, Hui-Kai
Integrated Resource Management for Fog Networks
title Integrated Resource Management for Fog Networks
title_full Integrated Resource Management for Fog Networks
title_fullStr Integrated Resource Management for Fog Networks
title_full_unstemmed Integrated Resource Management for Fog Networks
title_short Integrated Resource Management for Fog Networks
title_sort integrated resource management for fog networks
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950010/
https://www.ncbi.nlm.nih.gov/pubmed/35336575
http://dx.doi.org/10.3390/s22062404
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