Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing

Mobile edge computing (MEC) is an effective assistant technology that can overcome some defects of cloud computing. For the sake of alleviating the clashes between the capability constraint of cloudlets and the needs of mobile devices (MDs) for reducing executing latency as well as decreasing the po...

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Main Authors: Kai Peng, Hualong Huang, Wenjie Pan, Jiabin Wang
Format: Article
Language:English
Published: Wiley 2020-02-01
Series:IET Cyber-Physical Systems
Subjects:
mec
md
Online Access:https://digital-library.theiet.org/content/journals/10.1049/iet-cps.2019.0085
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spelling doaj-99f37944b17f4fdfa8a6aac9d1b294d52021-04-02T05:37:35ZengWileyIET Cyber-Physical Systems2398-33962020-02-0110.1049/iet-cps.2019.0085IET-CPS.2019.0085Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computingKai Peng0Hualong Huang1Wenjie Pan2Jiabin Wang3College of Engineering, Huaqiao UniversityCollege of Engineering, Huaqiao UniversityCollege of Engineering, Huaqiao UniversityCollege of Engineering, Huaqiao UniversityMobile edge computing (MEC) is an effective assistant technology that can overcome some defects of cloud computing. For the sake of alleviating the clashes between the capability constraint of cloudlets and the needs of mobile devices (MDs) for reducing executing latency as well as decreasing the power consumption of MDs, a user-oriented use case in the MEC named computation offloading is taken into consideration. Computation offloading is capable of effectively making the MEC adapt to the resources of cloudlets and MDs in different environments, and it is very beneficial to the development of the internet of things. Owing to the finite computation capabilities of the MDs and the resources of cloudlets are heterogeneous and limited; a three-objective model is established to optimise the time consumption, and the energy consumption of MDs as well as the load balancing of cloudlets jointly. Technically, the authors propose an effective multi-user multi-application computation offloading method in the multi-cloudlet environment on the basis of improved non-dominated sorting genetic algorithm III. Finally, comprehensive experiments and analysis were conducted to validate the effectiveness and efficiency of the proposed method.https://digital-library.theiet.org/content/journals/10.1049/iet-cps.2019.0085cloud computinggenetic algorithmsmobile computingresource allocationpower aware computingmeceffective assistant technologycloud computingmobile devicesmdpower consumptionuser-oriented use casefinite computation capabilitiesenergy consumptionmultiuser multiapplication computation offloading methodmulticloudlet environmentjoint optimisationmobile edge computing
collection DOAJ
language English
format Article
sources DOAJ
author Kai Peng
Hualong Huang
Wenjie Pan
Jiabin Wang
spellingShingle Kai Peng
Hualong Huang
Wenjie Pan
Jiabin Wang
Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
IET Cyber-Physical Systems
cloud computing
genetic algorithms
mobile computing
resource allocation
power aware computing
mec
effective assistant technology
cloud computing
mobile devices
md
power consumption
user-oriented use case
finite computation capabilities
energy consumption
multiuser multiapplication computation offloading method
multicloudlet environment
joint optimisation
mobile edge computing
author_facet Kai Peng
Hualong Huang
Wenjie Pan
Jiabin Wang
author_sort Kai Peng
title Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
title_short Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
title_full Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
title_fullStr Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
title_full_unstemmed Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
title_sort joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing
publisher Wiley
series IET Cyber-Physical Systems
issn 2398-3396
publishDate 2020-02-01
description Mobile edge computing (MEC) is an effective assistant technology that can overcome some defects of cloud computing. For the sake of alleviating the clashes between the capability constraint of cloudlets and the needs of mobile devices (MDs) for reducing executing latency as well as decreasing the power consumption of MDs, a user-oriented use case in the MEC named computation offloading is taken into consideration. Computation offloading is capable of effectively making the MEC adapt to the resources of cloudlets and MDs in different environments, and it is very beneficial to the development of the internet of things. Owing to the finite computation capabilities of the MDs and the resources of cloudlets are heterogeneous and limited; a three-objective model is established to optimise the time consumption, and the energy consumption of MDs as well as the load balancing of cloudlets jointly. Technically, the authors propose an effective multi-user multi-application computation offloading method in the multi-cloudlet environment on the basis of improved non-dominated sorting genetic algorithm III. Finally, comprehensive experiments and analysis were conducted to validate the effectiveness and efficiency of the proposed method.
topic cloud computing
genetic algorithms
mobile computing
resource allocation
power aware computing
mec
effective assistant technology
cloud computing
mobile devices
md
power consumption
user-oriented use case
finite computation capabilities
energy consumption
multiuser multiapplication computation offloading method
multicloudlet environment
joint optimisation
mobile edge computing
url https://digital-library.theiet.org/content/journals/10.1049/iet-cps.2019.0085
work_keys_str_mv AT kaipeng jointoptimisationfortimeconsumptionandenergyconsumptionofmultiapplicationandloadbalancingofcloudletsinmobileedgecomputing
AT hualonghuang jointoptimisationfortimeconsumptionandenergyconsumptionofmultiapplicationandloadbalancingofcloudletsinmobileedgecomputing
AT wenjiepan jointoptimisationfortimeconsumptionandenergyconsumptionofmultiapplicationandloadbalancingofcloudletsinmobileedgecomputing
AT jiabinwang jointoptimisationfortimeconsumptionandenergyconsumptionofmultiapplicationandloadbalancingofcloudletsinmobileedgecomputing
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