Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA

Multiaccess edge computation (MEC) is a hotspot in 5G network. The problem of task offloading is one of the core problems in MEC. In this paper, a novel computation offloading model which partitions tasks into subtasksis proposed. This model takes communication and computing resources, energy consum...

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Autores principales:	Yang Liu, Jin Qi Zhu, Jinao Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/b22be917c35648afb5661cabeaacbfa7
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spelling	oai:doaj.org-article:b22be917c35648afb5661cabeaacbfa72021-11-15T01:19:35ZComputation Offloading Optimization in Mobile Edge Computing Based on HIBSA1875-905X10.1155/2021/7716654https://doaj.org/article/b22be917c35648afb5661cabeaacbfa72021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7716654https://doaj.org/toc/1875-905XMultiaccess edge computation (MEC) is a hotspot in 5G network. The problem of task offloading is one of the core problems in MEC. In this paper, a novel computation offloading model which partitions tasks into subtasksis proposed. This model takes communication and computing resources, energy consumption of intelligent mobile devices, and weight of tasks into account. We then transform the model into a multiobjective optimization problem based on Pareto that balances the task weight and time efficiency of the offloaded tasks. In addition, an algorithm based on hybrid immune and bat scheduling algorithm (HIBSA) is further designed to tackle the proposed multiobjective optimization problem. The experimental results show that HIBSA can meet the requirements of both the task execution deadline and the weight of the offloaded tasks.Yang LiuJin Qi ZhuJinao WangHindawi LimitedarticleTelecommunicationTK5101-6720ENMobile Information Systems, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Yang Liu Jin Qi Zhu Jinao Wang Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
description	Multiaccess edge computation (MEC) is a hotspot in 5G network. The problem of task offloading is one of the core problems in MEC. In this paper, a novel computation offloading model which partitions tasks into subtasksis proposed. This model takes communication and computing resources, energy consumption of intelligent mobile devices, and weight of tasks into account. We then transform the model into a multiobjective optimization problem based on Pareto that balances the task weight and time efficiency of the offloaded tasks. In addition, an algorithm based on hybrid immune and bat scheduling algorithm (HIBSA) is further designed to tackle the proposed multiobjective optimization problem. The experimental results show that HIBSA can meet the requirements of both the task execution deadline and the weight of the offloaded tasks.
format	article
author	Yang Liu Jin Qi Zhu Jinao Wang
author_facet	Yang Liu Jin Qi Zhu Jinao Wang
author_sort	Yang Liu
title	Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
title_short	Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
title_full	Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
title_fullStr	Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
title_full_unstemmed	Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA
title_sort	computation offloading optimization in mobile edge computing based on hibsa
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/b22be917c35648afb5661cabeaacbfa7
work_keys_str_mv	AT yangliu computationoffloadingoptimizationinmobileedgecomputingbasedonhibsa AT jinqizhu computationoffloadingoptimizationinmobileedgecomputingbasedonhibsa AT jinaowang computationoffloadingoptimizationinmobileedgecomputingbasedonhibsa
_version_	1718428943707537408

Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA

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