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Distributed Agent-Based Orchestrator Model for Fog Computing
Fog computing is an extension of cloud computing that provides computing services closer to user end-devices at the network edge. One of the challenging topics in fog networks is the placement of tasks on fog nodes to obtain the best performance and resource usage. The process of mapping tasks for r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371437/ https://www.ncbi.nlm.nih.gov/pubmed/35957450 http://dx.doi.org/10.3390/s22155894 |
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author | Liutkevičius, Agnius Morkevičius, Nerijus Venčkauskas, Algimantas Toldinas, Jevgenijus |
author_facet | Liutkevičius, Agnius Morkevičius, Nerijus Venčkauskas, Algimantas Toldinas, Jevgenijus |
author_sort | Liutkevičius, Agnius |
collection | PubMed |
description | Fog computing is an extension of cloud computing that provides computing services closer to user end-devices at the network edge. One of the challenging topics in fog networks is the placement of tasks on fog nodes to obtain the best performance and resource usage. The process of mapping tasks for resource-constrained devices is known as the service or fog application placement problem (SPP, FAPP). The highly dynamic fog infrastructures with mobile user end-devices and constantly changing fog nodes resources (e.g., battery life, security level) require distributed/decentralized service placement (orchestration) algorithms to ensure better resilience, scalability, and optimal real-time performance. However, recently proposed service placement algorithms rarely support user end-device mobility, constantly changing the resource availability of fog nodes and the ability to recover from fog node failures at the same time. In this article, we propose a distributed agent-based orchestrator model capable of flexible service provisioning in a dynamic fog computing environment by considering the constraints on the central processing unit (CPU), memory, battery level, and security level of fog nodes. Distributing the decision-making to multiple orchestrator fog nodes instead of relying on the mapping of a single central entity helps to spread the load and increase scalability and, most importantly, resilience. The prototype system based on the proposed orchestrator model was implemented and tested with real hardware. The results show that the proposed model is efficient in terms of response latency and computational overhead, which are minimal compared to the placement algorithm itself. The research confirms that the proposed orchestrator approach is suitable for various fog network applications when scalability, mobility, and fault tolerance must be guaranteed. |
format | Online Article Text |
id | pubmed-9371437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93714372022-08-12 Distributed Agent-Based Orchestrator Model for Fog Computing Liutkevičius, Agnius Morkevičius, Nerijus Venčkauskas, Algimantas Toldinas, Jevgenijus Sensors (Basel) Article Fog computing is an extension of cloud computing that provides computing services closer to user end-devices at the network edge. One of the challenging topics in fog networks is the placement of tasks on fog nodes to obtain the best performance and resource usage. The process of mapping tasks for resource-constrained devices is known as the service or fog application placement problem (SPP, FAPP). The highly dynamic fog infrastructures with mobile user end-devices and constantly changing fog nodes resources (e.g., battery life, security level) require distributed/decentralized service placement (orchestration) algorithms to ensure better resilience, scalability, and optimal real-time performance. However, recently proposed service placement algorithms rarely support user end-device mobility, constantly changing the resource availability of fog nodes and the ability to recover from fog node failures at the same time. In this article, we propose a distributed agent-based orchestrator model capable of flexible service provisioning in a dynamic fog computing environment by considering the constraints on the central processing unit (CPU), memory, battery level, and security level of fog nodes. Distributing the decision-making to multiple orchestrator fog nodes instead of relying on the mapping of a single central entity helps to spread the load and increase scalability and, most importantly, resilience. The prototype system based on the proposed orchestrator model was implemented and tested with real hardware. The results show that the proposed model is efficient in terms of response latency and computational overhead, which are minimal compared to the placement algorithm itself. The research confirms that the proposed orchestrator approach is suitable for various fog network applications when scalability, mobility, and fault tolerance must be guaranteed. MDPI 2022-08-07 /pmc/articles/PMC9371437/ /pubmed/35957450 http://dx.doi.org/10.3390/s22155894 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 | Article Liutkevičius, Agnius Morkevičius, Nerijus Venčkauskas, Algimantas Toldinas, Jevgenijus Distributed Agent-Based Orchestrator Model for Fog Computing |
title | Distributed Agent-Based Orchestrator Model for Fog Computing |
title_full | Distributed Agent-Based Orchestrator Model for Fog Computing |
title_fullStr | Distributed Agent-Based Orchestrator Model for Fog Computing |
title_full_unstemmed | Distributed Agent-Based Orchestrator Model for Fog Computing |
title_short | Distributed Agent-Based Orchestrator Model for Fog Computing |
title_sort | distributed agent-based orchestrator model for fog computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371437/ https://www.ncbi.nlm.nih.gov/pubmed/35957450 http://dx.doi.org/10.3390/s22155894 |
work_keys_str_mv | AT liutkeviciusagnius distributedagentbasedorchestratormodelforfogcomputing AT morkeviciusnerijus distributedagentbasedorchestratormodelforfogcomputing AT venckauskasalgimantas distributedagentbasedorchestratormodelforfogcomputing AT toldinasjevgenijus distributedagentbasedorchestratormodelforfogcomputing |