An Energy-Friendly Scheduler for Edge Computing Systems

The deployment of modern applications, like massive Internet of Things (IoT), poses a combination of challenges that service providers need to overcome: high availability of the offered services, low latency, and low energy consumption. To overcome these challenges, service providers have been placi...

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Autores principales:	Alejandro Llorens-Carrodeguas, Stefanos G. Sagkriotis, Cristina Cervelló-Pastor, Dimitrios P. Pezaros
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	fog computing IoT resilience scheduling single board computer state of charge Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/0ddb95a00d3746a4b97bf1297ca42b28
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spelling	oai:doaj.org-article:0ddb95a00d3746a4b97bf1297ca42b282021-11-11T19:08:43ZAn Energy-Friendly Scheduler for Edge Computing Systems10.3390/s212171511424-8220https://doaj.org/article/0ddb95a00d3746a4b97bf1297ca42b282021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7151https://doaj.org/toc/1424-8220The deployment of modern applications, like massive Internet of Things (IoT), poses a combination of challenges that service providers need to overcome: high availability of the offered services, low latency, and low energy consumption. To overcome these challenges, service providers have been placing computing infrastructure close to the end users, at the edge of the network. In this vein, single board computer (SBC) clusters have gained attention due to their low cost, low energy consumption, and easy programmability. A subset of IoT applications requires the deployment of battery-powered SBCs, or clusters thereof. More recently, the deployment of services on SBC clusters has been automated through the use of containers. The management of these containers is performed by orchestration platforms, like Kubernetes. However, orchestration platforms do not consider remaining energy levels for their placement decisions and therefore are not optimized for energy-constrained environments. In this study, we propose a scheduler that is optimised for energy-constrained SBC clusters and operates within Kubernetes. Through comparison with the available schedulers we achieved 23% fewer event rejections, 83% less deadline violations, and approximately a 59% reduction of the consumed energy throughout the cluster.Alejandro Llorens-CarrodeguasStefanos G. SagkriotisCristina Cervelló-PastorDimitrios P. PezarosMDPI AGarticlefog computingIoTresilienceschedulingsingle board computerstate of chargeChemical technologyTP1-1185ENSensors, Vol 21, Iss 7151, p 7151 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fog computing IoT resilience scheduling single board computer state of charge Chemical technology TP1-1185
spellingShingle	fog computing IoT resilience scheduling single board computer state of charge Chemical technology TP1-1185 Alejandro Llorens-Carrodeguas Stefanos G. Sagkriotis Cristina Cervelló-Pastor Dimitrios P. Pezaros An Energy-Friendly Scheduler for Edge Computing Systems
description	The deployment of modern applications, like massive Internet of Things (IoT), poses a combination of challenges that service providers need to overcome: high availability of the offered services, low latency, and low energy consumption. To overcome these challenges, service providers have been placing computing infrastructure close to the end users, at the edge of the network. In this vein, single board computer (SBC) clusters have gained attention due to their low cost, low energy consumption, and easy programmability. A subset of IoT applications requires the deployment of battery-powered SBCs, or clusters thereof. More recently, the deployment of services on SBC clusters has been automated through the use of containers. The management of these containers is performed by orchestration platforms, like Kubernetes. However, orchestration platforms do not consider remaining energy levels for their placement decisions and therefore are not optimized for energy-constrained environments. In this study, we propose a scheduler that is optimised for energy-constrained SBC clusters and operates within Kubernetes. Through comparison with the available schedulers we achieved 23% fewer event rejections, 83% less deadline violations, and approximately a 59% reduction of the consumed energy throughout the cluster.
format	article
author	Alejandro Llorens-Carrodeguas Stefanos G. Sagkriotis Cristina Cervelló-Pastor Dimitrios P. Pezaros
author_facet	Alejandro Llorens-Carrodeguas Stefanos G. Sagkriotis Cristina Cervelló-Pastor Dimitrios P. Pezaros
author_sort	Alejandro Llorens-Carrodeguas
title	An Energy-Friendly Scheduler for Edge Computing Systems
title_short	An Energy-Friendly Scheduler for Edge Computing Systems
title_full	An Energy-Friendly Scheduler for Edge Computing Systems
title_fullStr	An Energy-Friendly Scheduler for Edge Computing Systems
title_full_unstemmed	An Energy-Friendly Scheduler for Edge Computing Systems
title_sort	energy-friendly scheduler for edge computing systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0ddb95a00d3746a4b97bf1297ca42b28
work_keys_str_mv	AT alejandrollorenscarrodeguas anenergyfriendlyschedulerforedgecomputingsystems AT stefanosgsagkriotis anenergyfriendlyschedulerforedgecomputingsystems AT cristinacervellopastor anenergyfriendlyschedulerforedgecomputingsystems AT dimitriosppezaros anenergyfriendlyschedulerforedgecomputingsystems AT alejandrollorenscarrodeguas energyfriendlyschedulerforedgecomputingsystems AT stefanosgsagkriotis energyfriendlyschedulerforedgecomputingsystems AT cristinacervellopastor energyfriendlyschedulerforedgecomputingsystems AT dimitriosppezaros energyfriendlyschedulerforedgecomputingsystems
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An Energy-Friendly Scheduler for Edge Computing Systems

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