GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things

This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, a...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiao, Hongyu, Zhang, Zhenjiang, Zhou, Zhangbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111855/
https://www.ncbi.nlm.nih.gov/pubmed/30065224
http://dx.doi.org/10.3390/s18082479
_version_ 1783350747243479040
author Xiao, Hongyu
Zhang, Zhenjiang
Zhou, Zhangbing
author_facet Xiao, Hongyu
Zhang, Zhenjiang
Zhou, Zhangbing
author_sort Xiao, Hongyu
collection PubMed
description This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, and is based on the Nash bargaining solution (NBS) for a cooperative game between FCNs. Pareto optimality is achieved through the collaborative working of FCNs to improve the performance of every FCN. Lastly the simulation results demonstrate that the game-theory based work-stealing algorithm (GWS) outperforms the classical work-stealing algorithm (CWS).
format Online
Article
Text
id pubmed-6111855
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-61118552018-08-30 GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things Xiao, Hongyu Zhang, Zhenjiang Zhou, Zhangbing Sensors (Basel) Article This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, and is based on the Nash bargaining solution (NBS) for a cooperative game between FCNs. Pareto optimality is achieved through the collaborative working of FCNs to improve the performance of every FCN. Lastly the simulation results demonstrate that the game-theory based work-stealing algorithm (GWS) outperforms the classical work-stealing algorithm (CWS). MDPI 2018-07-31 /pmc/articles/PMC6111855/ /pubmed/30065224 http://dx.doi.org/10.3390/s18082479 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiao, Hongyu
Zhang, Zhenjiang
Zhou, Zhangbing
GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title_full GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title_fullStr GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title_full_unstemmed GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title_short GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things
title_sort gws—a collaborative load-balancing algorithm for internet-of-things
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111855/
https://www.ncbi.nlm.nih.gov/pubmed/30065224
http://dx.doi.org/10.3390/s18082479
work_keys_str_mv AT xiaohongyu gwsacollaborativeloadbalancingalgorithmforinternetofthings
AT zhangzhenjiang gwsacollaborativeloadbalancingalgorithmforinternetofthings
AT zhouzhangbing gwsacollaborativeloadbalancingalgorithmforinternetofthings

Ejemplares similares