Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing

By means of the complex systems, multiple renewable energy sources are integrated to provide energy supply for users. Considering that there are massive services needed to process in complex systems, the mobile services are offloaded from mobile devices to edge servers for efficient implementation....

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Main Authors: Xiaolong Xu, Yuan Xue, Mengmeng Cui, Yuan Yuan, Lianyong Qi
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/6180135
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author Xiaolong Xu
Yuan Xue
Mengmeng Cui
Yuan Yuan
Lianyong Qi
author_facet Xiaolong Xu
Yuan Xue
Mengmeng Cui
Yuan Yuan
Lianyong Qi
author_sort Xiaolong Xu
collection DOAJ
description By means of the complex systems, multiple renewable energy sources are integrated to provide energy supply for users. Considering that there are massive services needed to process in complex systems, the mobile services are offloaded from mobile devices to edge servers for efficient implementation. In spite of the benefits of complex systems and edge servers, massive resource requirements for implementing the increasing resource requests decrease the execution efficiency and affect the whole resource usage of edge servers. Therefore, it remains an issue to achieve dynamic scheduling of the computing resources across edge servers. With the consideration of this issue, a Balanced Resource Scheduling Method, named BRSM, for trade-offs between virtual machine (VM) migration cost and energy consumption of VM migrations for edge server management, named BRSM, is designed in this paper. Technically, we analyze the load conditions of edge servers and formulate the energy consumption of VM migrations and VM migration cost as a multi-objective optimization problem. Then, we propose a dynamic resource scheduling method for WMAN to deal with the multi-objective optimization problem. In addition, nondominated sorting genetic algorithm III (NSGA-III) is adopted to generate optimal resource scheduling strategies. Finally, we conduct experiment simulations to testify the efficiency of the proposed method BRSM.
format Article
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institution Kabale University
issn 1076-2787
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language English
publishDate 2019-01-01
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series Complexity
spelling doaj-art-3327c90cfd4440d1bb7c4a884f15af282025-02-03T05:53:19ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/61801356180135Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge ComputingXiaolong Xu0Yuan Xue1Mengmeng Cui2Yuan Yuan3Lianyong Qi4School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, ChinaSchool of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, ChinaSchool of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, ChinaDepartment of Computer Science and Engineering, Michigan State University, MI, USASchool of Information Science and Engineering, Qufu Normal University, Qufu, ChinaBy means of the complex systems, multiple renewable energy sources are integrated to provide energy supply for users. Considering that there are massive services needed to process in complex systems, the mobile services are offloaded from mobile devices to edge servers for efficient implementation. In spite of the benefits of complex systems and edge servers, massive resource requirements for implementing the increasing resource requests decrease the execution efficiency and affect the whole resource usage of edge servers. Therefore, it remains an issue to achieve dynamic scheduling of the computing resources across edge servers. With the consideration of this issue, a Balanced Resource Scheduling Method, named BRSM, for trade-offs between virtual machine (VM) migration cost and energy consumption of VM migrations for edge server management, named BRSM, is designed in this paper. Technically, we analyze the load conditions of edge servers and formulate the energy consumption of VM migrations and VM migration cost as a multi-objective optimization problem. Then, we propose a dynamic resource scheduling method for WMAN to deal with the multi-objective optimization problem. In addition, nondominated sorting genetic algorithm III (NSGA-III) is adopted to generate optimal resource scheduling strategies. Finally, we conduct experiment simulations to testify the efficiency of the proposed method BRSM.http://dx.doi.org/10.1155/2019/6180135
spellingShingle Xiaolong Xu
Yuan Xue
Mengmeng Cui
Yuan Yuan
Lianyong Qi
Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
Complexity
title Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
title_full Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
title_fullStr Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
title_full_unstemmed Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
title_short Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing
title_sort joint optimization of energy conservation and migration cost for complex systems in edge computing
url http://dx.doi.org/10.1155/2019/6180135
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AT yuanxue jointoptimizationofenergyconservationandmigrationcostforcomplexsystemsinedgecomputing
AT mengmengcui jointoptimizationofenergyconservationandmigrationcostforcomplexsystemsinedgecomputing
AT yuanyuan jointoptimizationofenergyconservationandmigrationcostforcomplexsystemsinedgecomputing
AT lianyongqi jointoptimizationofenergyconservationandmigrationcostforcomplexsystemsinedgecomputing