Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks

Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks

Mobile edge computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading (EECO) mechanisms for MEC in 5G heterogeneous networks. We formulate an...

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Main Authors: Ke Zhang, Yuming Mao, Supeng Leng, Quanxin Zhao, Longjiang Li, Xin Peng, Li Pan, Sabita Maharjan, Yan Zhang
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Energy-efficiency
offloading
mobile edge computing
5G
Online Access:https://ieeexplore.ieee.org/document/7553459/
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spelling doaj-94716cb215ef49639da09c4f62f7865b2021-03-29T19:44:15ZengIEEEIEEE Access2169-35362016-01-0145896590710.1109/ACCESS.2016.25971697553459Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous NetworksKe Zhang0Yuming Mao1Supeng Leng2Quanxin Zhao3Longjiang Li4Xin Peng5Li Pan6Sabita Maharjan7Yan Zhang8https://orcid.org/0000-0003-3081-7751School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaCollege of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaCollege of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaSimula Research Laboratory, Oslo, NorwaySimula Research Laboratory, Oslo, NorwayMobile edge computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading (EECO) mechanisms for MEC in 5G heterogeneous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogeneous network, we then design an EECO scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.https://ieeexplore.ieee.org/document/7553459/Energy-efficiencyoffloadingmobile edge computing5G
collection DOAJ
language English
format Article
sources DOAJ
author Ke Zhang
Yuming Mao
Supeng Leng
Quanxin Zhao
Longjiang Li
Xin Peng
Li Pan
Sabita Maharjan
Yan Zhang
spellingShingle Ke Zhang
Yuming Mao
Supeng Leng
Quanxin Zhao
Longjiang Li
Xin Peng
Li Pan
Sabita Maharjan
Yan Zhang
Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
IEEE Access
Energy-efficiency
offloading
mobile edge computing
5G
author_facet Ke Zhang
Yuming Mao
Supeng Leng
Quanxin Zhao
Longjiang Li
Xin Peng
Li Pan
Sabita Maharjan
Yan Zhang
author_sort Ke Zhang
title Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
title_short Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
title_full Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
title_fullStr Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
title_full_unstemmed Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
title_sort energy-efficient offloading for mobile edge computing in 5g heterogeneous networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2016-01-01
description Mobile edge computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading (EECO) mechanisms for MEC in 5G heterogeneous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogeneous network, we then design an EECO scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.
topic Energy-efficiency
offloading
mobile edge computing
5G
url https://ieeexplore.ieee.org/document/7553459/
work_keys_str_mv AT kezhang energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT yumingmao energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT supengleng energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT quanxinzhao energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT longjiangli energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT xinpeng energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT lipan energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT sabitamaharjan energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
AT yanzhang energyefficientoffloadingformobileedgecomputingin5gheterogeneousnetworks
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