Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks

Via processing the computation intensive applications (apps) at the network edge, mobile edge computing (MEC) becomes a promising technology to enhance the ability of the user equipments (UEs). Most existing works usually focus on whether to offload or where to offload the apps under the premise tha...

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Main Authors: Heli Zhang, Fengxian Guo, Hong Ji, Chunsheng Zhu
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7967816/
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spelling doaj-a010735e3ba241b1ae6143e26eabf6a12021-03-29T20:14:30ZengIEEEIEEE Access2169-35362017-01-015134551346410.1109/ACCESS.2017.27219577967816Combinational Auction-Based Service Provider Selection in Mobile Edge Computing NetworksHeli Zhang0https://orcid.org/0000-0002-5994-9419Fengxian Guo1Hong Ji2Chunsheng Zhu3Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, ChinaKey Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, ChinaDepartment of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, CanadaVia processing the computation intensive applications (apps) at the network edge, mobile edge computing (MEC) becomes a promising technology to enhance the ability of the user equipments (UEs). Most existing works usually focus on whether to offload or where to offload the apps under the premise that sufficient resources are owned by the network edge. However, the demand heterogeneity of UEs and the limitation of resources are usually failed to be considered. Since the limited resources may constrain the number of accessed UEs, how the MEC service providers (SPs) choose the UEs to serve while ensuring UEs' Quality of Service (QoS) is a key issue. Under this context, in this paper, we study the matching problem between the MEC SPs and the UEs in a multi-MEC and multi-UE scenario. Within this scenario, MEC SPs are equipped with limited wireless and computational resources. Auction theory is utilized to model the matching relationship between MEC SPs and UEs as the commodity trading. With this trading, UEs can obtain MEC service from SPs, when they successfully purchase the combinational resources (including computational and wireless resources) from SPs. To complete the auction process, a multi-round-sealed sequential combinatorial auction mechanism is proposed. The properties of the auction are proved and various simulation results are done to show that the proposed approach has better system performance compared with the existing algorithms.https://ieeexplore.ieee.org/document/7967816/Mobile edge computingcomputation offloadingMEC SP and UE matchingcombinational auctiondemand heterogeneity
collection DOAJ
language English
format Article
sources DOAJ
author Heli Zhang
Fengxian Guo
Hong Ji
Chunsheng Zhu
spellingShingle Heli Zhang
Fengxian Guo
Hong Ji
Chunsheng Zhu
Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
IEEE Access
Mobile edge computing
computation offloading
MEC SP and UE matching
combinational auction
demand heterogeneity
author_facet Heli Zhang
Fengxian Guo
Hong Ji
Chunsheng Zhu
author_sort Heli Zhang
title Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
title_short Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
title_full Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
title_fullStr Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
title_full_unstemmed Combinational Auction-Based Service Provider Selection in Mobile Edge Computing Networks
title_sort combinational auction-based service provider selection in mobile edge computing networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description Via processing the computation intensive applications (apps) at the network edge, mobile edge computing (MEC) becomes a promising technology to enhance the ability of the user equipments (UEs). Most existing works usually focus on whether to offload or where to offload the apps under the premise that sufficient resources are owned by the network edge. However, the demand heterogeneity of UEs and the limitation of resources are usually failed to be considered. Since the limited resources may constrain the number of accessed UEs, how the MEC service providers (SPs) choose the UEs to serve while ensuring UEs' Quality of Service (QoS) is a key issue. Under this context, in this paper, we study the matching problem between the MEC SPs and the UEs in a multi-MEC and multi-UE scenario. Within this scenario, MEC SPs are equipped with limited wireless and computational resources. Auction theory is utilized to model the matching relationship between MEC SPs and UEs as the commodity trading. With this trading, UEs can obtain MEC service from SPs, when they successfully purchase the combinational resources (including computational and wireless resources) from SPs. To complete the auction process, a multi-round-sealed sequential combinatorial auction mechanism is proposed. The properties of the auction are proved and various simulation results are done to show that the proposed approach has better system performance compared with the existing algorithms.
topic Mobile edge computing
computation offloading
MEC SP and UE matching
combinational auction
demand heterogeneity
url https://ieeexplore.ieee.org/document/7967816/
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AT fengxianguo combinationalauctionbasedserviceproviderselectioninmobileedgecomputingnetworks
AT hongji combinationalauctionbasedserviceproviderselectioninmobileedgecomputingnetworks
AT chunshengzhu combinationalauctionbasedserviceproviderselectioninmobileedgecomputingnetworks
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