Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment

The application scenarios and market shares of industrial robots have been increasing in recent years, and with them comes a huge market and technical demand for industrial robot-monitoring system (IRMS). With the development of IoT and cloud computing technologies, industrial robot monitoring has e...

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Autores principales:	Xingju Xie, Xiaojun Wu, Qiao Hu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	industrial robot-monitoring system industrial robot-monitoring workflow workflow resource allocation edge–cloud collaboration bi-objective genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/19554d5d0a2a410d89b04ec258f48f33
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id	oai:doaj.org-article:19554d5d0a2a410d89b04ec258f48f33
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spelling	oai:doaj.org-article:19554d5d0a2a410d89b04ec258f48f332021-11-11T15:08:14ZBi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment10.3390/app1121100662076-3417https://doaj.org/article/19554d5d0a2a410d89b04ec258f48f332021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10066https://doaj.org/toc/2076-3417The application scenarios and market shares of industrial robots have been increasing in recent years, and with them comes a huge market and technical demand for industrial robot-monitoring system (IRMS). With the development of IoT and cloud computing technologies, industrial robot monitoring has entered the cloud computing era. However, the data of industrial robot-monitoring tasks have characteristics of large data volume and high information redundancy, and need to occupy a large amount of communication bandwidth in cloud computing architecture, so cloud-based IRMS has gradually become unable to meet its performance and cost requirements. Therefore, this work constructs edge–cloud architecture for the IRMS. The industrial robot-monitoring task will be executed in the form of workflow and the local monitor will allocate computing resources for the subtasks of the workflow by analyzing the current situation of the edge–cloud network. In this work, the allocation problem of industrial robot-monitoring workflow is modeled as a latency and cost bi-objective optimization problem, and its solution is based on the evolutionary algorithm of the heuristic improvement NSGA-II. The experimental results demonstrate that the proposed algorithm can find non-dominated solutions faster and be closer to the Pareto frontier of the problem. The monitor can select an effective solution in the Pareto frontier to meet the needs of the monitoring task.Xingju XieXiaojun WuQiao HuMDPI AGarticleindustrial robot-monitoring systemindustrial robot-monitoring workflowworkflow resource allocationedge–cloud collaborationbi-objective genetic algorithmTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10066, p 10066 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	industrial robot-monitoring system industrial robot-monitoring workflow workflow resource allocation edge–cloud collaboration bi-objective genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	industrial robot-monitoring system industrial robot-monitoring workflow workflow resource allocation edge–cloud collaboration bi-objective genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Xingju Xie Xiaojun Wu Qiao Hu Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
description	The application scenarios and market shares of industrial robots have been increasing in recent years, and with them comes a huge market and technical demand for industrial robot-monitoring system (IRMS). With the development of IoT and cloud computing technologies, industrial robot monitoring has entered the cloud computing era. However, the data of industrial robot-monitoring tasks have characteristics of large data volume and high information redundancy, and need to occupy a large amount of communication bandwidth in cloud computing architecture, so cloud-based IRMS has gradually become unable to meet its performance and cost requirements. Therefore, this work constructs edge–cloud architecture for the IRMS. The industrial robot-monitoring task will be executed in the form of workflow and the local monitor will allocate computing resources for the subtasks of the workflow by analyzing the current situation of the edge–cloud network. In this work, the allocation problem of industrial robot-monitoring workflow is modeled as a latency and cost bi-objective optimization problem, and its solution is based on the evolutionary algorithm of the heuristic improvement NSGA-II. The experimental results demonstrate that the proposed algorithm can find non-dominated solutions faster and be closer to the Pareto frontier of the problem. The monitor can select an effective solution in the Pareto frontier to meet the needs of the monitoring task.
format	article
author	Xingju Xie Xiaojun Wu Qiao Hu
author_facet	Xingju Xie Xiaojun Wu Qiao Hu
author_sort	Xingju Xie
title	Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
title_short	Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
title_full	Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
title_fullStr	Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
title_full_unstemmed	Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment
title_sort	bi-objective optimization for industrial robotics workflow resource allocation in an edge–cloud environment
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/19554d5d0a2a410d89b04ec258f48f33
work_keys_str_mv	AT xingjuxie biobjectiveoptimizationforindustrialroboticsworkflowresourceallocationinanedgecloudenvironment AT xiaojunwu biobjectiveoptimizationforindustrialroboticsworkflowresourceallocationinanedgecloudenvironment AT qiaohu biobjectiveoptimizationforindustrialroboticsworkflowresourceallocationinanedgecloudenvironment
_version_	1718437105789566976

Bi-Objective Optimization for Industrial Robotics Workflow Resource Allocation in an Edge–Cloud Environment

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