Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT

Mobile/multi-access edge computing (MEC) takes advantage of its proximity to end-users, which greatly reduces the transmission delay of task offloading compared to mobile cloud computing (MCC). Offloading computing tasks to edge servers with a certain amount of computing ability can also reduce the...

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Main Authors: Jingyan Wu, Jiawei Zhang, Yuming Xiao, Yuefeng Ji
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2021/9977700
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spelling doaj-641f3fc86b174ffb945e2de5d60d72f02021-08-30T00:01:11ZengHindawi-WileyWireless Communications and Mobile Computing1530-86772021-01-01202110.1155/2021/9977700Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoTJingyan Wu0Jiawei Zhang1Yuming Xiao2Yuefeng Ji3State Key Laboratory of Information Photonics and Optical CommunicationsState Key Laboratory of Information Photonics and Optical CommunicationsState Key Laboratory of Information Photonics and Optical CommunicationsState Key Laboratory of Information Photonics and Optical CommunicationsMobile/multi-access edge computing (MEC) takes advantage of its proximity to end-users, which greatly reduces the transmission delay of task offloading compared to mobile cloud computing (MCC). Offloading computing tasks to edge servers with a certain amount of computing ability can also reduce the computing delay. Meanwhile, device-to-device (D2D) cooperation can help to process small-scale delay-sensitive tasks to further decrease the delay of tasks. But where to offload the computing tasks is a critical issue. In this article, we integrate MEC and D2D cooperation techniques to optimize the offloading decisions and resource allocation problem in D2D-enabled three-tier MEC networks for Internet of Things (IoT). Mobile devices (MDs), edge clouds, and central cloud data center (DC) make up these three-tier MEC networks. They cooperate with each other to finish the offloading tasks. Each task can be processed by MD itself or its neighboring MDs at device tier, by edge servers at edge tier, or by remote cloud servers at cloud tier. Under the maximum energy cost constraints, we formulate the cooperative offloading problem into a mixed-integer nonlinear problem aiming to minimize the total delay of tasks. We utilize the alternating direction method of multipliers (ADMM) to speed up the computing process. The proposed scheme decomposes the complicated problem into 3 smaller subproblems, which are solved in a parallel fashion. Finally, we compare our proposal with D2D and MEC networks in simulations. Numerical results validate that the proposed D2D-enabled MEC networks for IoT can significantly enhance the computing abilities and reduce the total delay of tasks.http://dx.doi.org/10.1155/2021/9977700
collection DOAJ
language English
format Article
sources DOAJ
author Jingyan Wu
Jiawei Zhang
Yuming Xiao
Yuefeng Ji
spellingShingle Jingyan Wu
Jiawei Zhang
Yuming Xiao
Yuefeng Ji
Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
Wireless Communications and Mobile Computing
author_facet Jingyan Wu
Jiawei Zhang
Yuming Xiao
Yuefeng Ji
author_sort Jingyan Wu
title Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
title_short Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
title_full Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
title_fullStr Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
title_full_unstemmed Cooperative Offloading in D2D-Enabled Three-Tier MEC Networks for IoT
title_sort cooperative offloading in d2d-enabled three-tier mec networks for iot
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8677
publishDate 2021-01-01
description Mobile/multi-access edge computing (MEC) takes advantage of its proximity to end-users, which greatly reduces the transmission delay of task offloading compared to mobile cloud computing (MCC). Offloading computing tasks to edge servers with a certain amount of computing ability can also reduce the computing delay. Meanwhile, device-to-device (D2D) cooperation can help to process small-scale delay-sensitive tasks to further decrease the delay of tasks. But where to offload the computing tasks is a critical issue. In this article, we integrate MEC and D2D cooperation techniques to optimize the offloading decisions and resource allocation problem in D2D-enabled three-tier MEC networks for Internet of Things (IoT). Mobile devices (MDs), edge clouds, and central cloud data center (DC) make up these three-tier MEC networks. They cooperate with each other to finish the offloading tasks. Each task can be processed by MD itself or its neighboring MDs at device tier, by edge servers at edge tier, or by remote cloud servers at cloud tier. Under the maximum energy cost constraints, we formulate the cooperative offloading problem into a mixed-integer nonlinear problem aiming to minimize the total delay of tasks. We utilize the alternating direction method of multipliers (ADMM) to speed up the computing process. The proposed scheme decomposes the complicated problem into 3 smaller subproblems, which are solved in a parallel fashion. Finally, we compare our proposal with D2D and MEC networks in simulations. Numerical results validate that the proposed D2D-enabled MEC networks for IoT can significantly enhance the computing abilities and reduce the total delay of tasks.
url http://dx.doi.org/10.1155/2021/9977700
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AT jiaweizhang cooperativeoffloadingind2denabledthreetiermecnetworksforiot
AT yumingxiao cooperativeoffloadingind2denabledthreetiermecnetworksforiot
AT yuefengji cooperativeoffloadingind2denabledthreetiermecnetworksforiot
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