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Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks

Over the last decade, the usage of Internet of Things (IoT) enabled applications, such as healthcare, intelligent vehicles, and smart homes, has increased progressively. These IoT applications generate delayed- sensitive data and requires quick resources for execution. Recently, software-defined net...

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Autores principales: Lakhan, Abdullah, Mohammed, Mazin Abed, Abdulkareem, Karrar Hameed, Jaber, Mustafa Musa, Nedoma, Jan, Martinek, Radek, Zmij, Petr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414942/
https://www.ncbi.nlm.nih.gov/pubmed/36015699
http://dx.doi.org/10.3390/s22165937
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author Lakhan, Abdullah
Mohammed, Mazin Abed
Abdulkareem, Karrar Hameed
Jaber, Mustafa Musa
Nedoma, Jan
Martinek, Radek
Zmij, Petr
author_facet Lakhan, Abdullah
Mohammed, Mazin Abed
Abdulkareem, Karrar Hameed
Jaber, Mustafa Musa
Nedoma, Jan
Martinek, Radek
Zmij, Petr
author_sort Lakhan, Abdullah
collection PubMed
description Over the last decade, the usage of Internet of Things (IoT) enabled applications, such as healthcare, intelligent vehicles, and smart homes, has increased progressively. These IoT applications generate delayed- sensitive data and requires quick resources for execution. Recently, software-defined networks (SDN) offer an edge computing paradigm (e.g., fog computing) to run these applications with minimum end-to-end delays. Offloading and scheduling are promising schemes of edge computing to run delay-sensitive IoT applications while satisfying their requirements. However, in the dynamic environment, existing offloading and scheduling techniques are not ideal and decrease the performance of such applications. This article formulates joint and scheduling problems into combinatorial integer linear programming (CILP). We propose a joint task offloading and scheduling (JTOS) framework based on the problem. JTOS consists of task offloading, sequencing, scheduling, searching, and failure components. The study’s goal is to minimize the hybrid delay of all applications. The performance evaluation shows that JTOS outperforms all existing baseline methods in hybrid delay for all applications in the dynamic environment. The performance evaluation shows that JTOS reduces the processing delay by 39% and the communication delay by 35% for IoT applications compared to existing schemes.
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spelling pubmed-94149422022-08-27 Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks Lakhan, Abdullah Mohammed, Mazin Abed Abdulkareem, Karrar Hameed Jaber, Mustafa Musa Nedoma, Jan Martinek, Radek Zmij, Petr Sensors (Basel) Article Over the last decade, the usage of Internet of Things (IoT) enabled applications, such as healthcare, intelligent vehicles, and smart homes, has increased progressively. These IoT applications generate delayed- sensitive data and requires quick resources for execution. Recently, software-defined networks (SDN) offer an edge computing paradigm (e.g., fog computing) to run these applications with minimum end-to-end delays. Offloading and scheduling are promising schemes of edge computing to run delay-sensitive IoT applications while satisfying their requirements. However, in the dynamic environment, existing offloading and scheduling techniques are not ideal and decrease the performance of such applications. This article formulates joint and scheduling problems into combinatorial integer linear programming (CILP). We propose a joint task offloading and scheduling (JTOS) framework based on the problem. JTOS consists of task offloading, sequencing, scheduling, searching, and failure components. The study’s goal is to minimize the hybrid delay of all applications. The performance evaluation shows that JTOS outperforms all existing baseline methods in hybrid delay for all applications in the dynamic environment. The performance evaluation shows that JTOS reduces the processing delay by 39% and the communication delay by 35% for IoT applications compared to existing schemes. MDPI 2022-08-09 /pmc/articles/PMC9414942/ /pubmed/36015699 http://dx.doi.org/10.3390/s22165937 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
Lakhan, Abdullah
Mohammed, Mazin Abed
Abdulkareem, Karrar Hameed
Jaber, Mustafa Musa
Nedoma, Jan
Martinek, Radek
Zmij, Petr
Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title_full Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title_fullStr Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title_full_unstemmed Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title_short Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks
title_sort delay optimal schemes for internet of things applications in heterogeneous edge cloud computing networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414942/
https://www.ncbi.nlm.nih.gov/pubmed/36015699
http://dx.doi.org/10.3390/s22165937
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