Joint Optimization of Resources in Fog-Radio Access Network with Binary Computation Offloading

With the dramatic increase in the number of emerging Internet services, the Fog-Radio Access Network (F-RAN) has recently emerged as a promising paradigm to enhance high-load task processing capabilities for mobile devices, such as the Internet of things (IoT) and mobile terminals. Hence, it becomes...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mobile information systems Jg. 2023; S. 1 - 15
Hauptverfasser: Bai, Wenle, Wang, Zhuoqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Hindawi 21.04.2023
John Wiley & Sons, Inc
Schlagworte:
ISSN:1574-017X, 1875-905X
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract With the dramatic increase in the number of emerging Internet services, the Fog-Radio Access Network (F-RAN) has recently emerged as a promising paradigm to enhance high-load task processing capabilities for mobile devices, such as the Internet of things (IoT) and mobile terminals. Hence, it becomes a challenge for the F-RAN to reduce the offloading cost by designing an effective offloading strategy and rational planning of limited network resources to improve the quality of experience (QoE). This article investigates the F-RAN with a binary offload policy. It proposes an intelligent algorithm capable of optimally adapting to task offload policy, fog computing resource allocation, and offload channel resource allocation. To evaluate the offloading strategy intuitively, we design a system utility metric defined as a delay-energy weighted sum. The joint optimization problem is converted into a convex problem based on this metric, i.e., a mixed integer nonlinear programming (MINLP) problem. A novel algorithm based on improved double-deep Q neural networks is DDQN, which is proposed to address this problem. Furthermore, an action space mapping method in the DDQN framework is presented to obtain offloading decisions. Extensive experimental data indicate that the proposed DDQN algorithm can effectively reduce the offloading cost and is adaptable to different offloading scenarios.
AbstractList With the dramatic increase in the number of emerging Internet services, the Fog-Radio Access Network (F-RAN) has recently emerged as a promising paradigm to enhance high-load task processing capabilities for mobile devices, such as the Internet of things (IoT) and mobile terminals. Hence, it becomes a challenge for the F-RAN to reduce the offloading cost by designing an effective offloading strategy and rational planning of limited network resources to improve the quality of experience (QoE). This article investigates the F-RAN with a binary offload policy. It proposes an intelligent algorithm capable of optimally adapting to task offload policy, fog computing resource allocation, and offload channel resource allocation. To evaluate the offloading strategy intuitively, we design a system utility metric defined as a delay-energy weighted sum. The joint optimization problem is converted into a convex problem based on this metric, i.e., a mixed integer nonlinear programming (MINLP) problem. A novel algorithm based on improved double-deep Q neural networks is DDQN, which is proposed to address this problem. Furthermore, an action space mapping method in the DDQN framework is presented to obtain offloading decisions. Extensive experimental data indicate that the proposed DDQN algorithm can effectively reduce the offloading cost and is adaptable to different offloading scenarios.
Author Bai, Wenle
Wang, Zhuoqi
Author_xml – sequence: 1
  givenname: Wenle
  surname: Bai
  fullname: Bai, Wenle
  organization: Information Science and TechnologyNorth China University of TechnologyShijingshan DistrictBeijing 100043Chinancut.edu.cn
– sequence: 2
  givenname: Zhuoqi
  orcidid: 0000-0002-6352-6355
  surname: Wang
  fullname: Wang, Zhuoqi
  organization: School of Information Science and TechnologyNorth China University of TechnologyShijingshan DistrictBeijing 100043Chinancut.edu.cn
BookMark eNp9UE1PAjEUbAwmAnrzBzTxqCv92N12j0jEjxBJiCac3LzddqEILW6XEP31liwnEz29l5eZeTPTQx3rrEbokpJbSpNkwAjjA5pKkQp2grpUiiTKSDLvhD0RcUSomJ-hnvcrQlLCE9FF78_O2AZPt43ZmG9ojLPYVXimvdvVpfbYWDx2i2gGyjg8LMPJ4xfd7F39gfemWeI7Y6H-wiO32e6aVmBaVWsXCHZxjk4rWHt9cZx99Da-fx09RpPpw9NoOIlKKhmLQGUAaaayWGoogBNgLBMhTklEwYEormKmUgpUckK1LOJSAsviUhUVAFe8j65a3W3tPnfaN_kq-LfhZc4kESKNk5gF1E2LKmvnfa2rfFubTXCfU5IfGswPDebHBgOc_YKXpk3Y1GDWf5GuW9LSWAV78_-LH8DGgqU
CitedBy_id crossref_primary_10_1007_s11227_024_06454_6
crossref_primary_10_1007_s11235_025_01332_9
Cites_doi 10.23919/jcc.2019.10.013
10.1109/access.2020.3022661
10.1109/twc.2017.2703901
10.1109/jiot.2020.2971323
10.1088/1742-6596/1873/1/012046
10.1109/access.2019.2929075
10.1109/access.2019.2941741
10.1109/ACCESS.2020.3000832
10.1109/jcn.2018.000036
10.1109/twc.2020.3007805
10.1109/access.2021.3058021
10.1109/access.2019.2947542
10.1109/JIOT.2022.3168885
10.1109/tmc.2019.2952354
10.1109/twc.2018.2821664
10.1109/TMC.2019.2892953
10.1109/tmc.2020.2967041
10.1109/ACCESS.2019.2947652
10.1109/tc.2020.2993561
10.1109/ICCC52777.2021.9580391
10.1049/iet-com.2017.0213
10.1109/TVT.2019.2919915
10.1109/tmc.2019.2928811
10.1109/jiot.2020.2972061
10.1109/PIMRC48278.2020.9217355
10.1109/tvt.2020.2981122
10.23919/icn.2020.0020
10.1109/access.2020.3004861
10.1109/JSAC.2020.3020659
10.1109/access.2021.3067702
10.1109/tvt.2018.2881191
10.1109/ICISPC.2019.8935698
10.1109/TWC.2020.2978843
10.1109/tcss.2020.3005761
10.1109/ACCESS.2020.3045304
10.1109/jiot.2020.3022699
ContentType Journal Article
Copyright Copyright © 2023 Wenle Bai and Zhuoqi Wang.
Copyright © 2023 Wenle Bai and Zhuoqi Wang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
Copyright_xml – notice: Copyright © 2023 Wenle Bai and Zhuoqi Wang.
– notice: Copyright © 2023 Wenle Bai and Zhuoqi Wang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
DBID RHU
RHW
RHX
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
DOI 10.1155/2023/1687672
DatabaseName Hindawi Publishing Complete
Hindawi Publishing Subscription Journals
Hindawi Publishing Open Access
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList CrossRef

Technology Research Database
Database_xml – sequence: 1
  dbid: RHX
  name: Hindawi Publishing Open Access
  url: http://www.hindawi.com/journals/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1875-905X
Editor Zhang, Yuexia
Editor_xml – sequence: 1
  givenname: Yuexia
  surname: Zhang
  fullname: Zhang, Yuexia
EndPage 15
ExternalDocumentID 10_1155_2023_1687672
GrantInformation_xml – fundername: Beijing Municipal Natural Science Foundation
  grantid: L182039
GroupedDBID -CS
-CY
.4S
.DC
0R~
4.4
5VS
AAFWJ
AAJEY
ABHFT
ABJNI
ACGFO
ACGFS
ADBBV
AEGXH
AENEX
AIAGR
ALMA_UNASSIGNED_HOLDINGS
ARCSS
ASPBG
AVWKF
BCNDV
EBS
EDO
GROUPED_DOAJ
HZ~
I-F
IAO
IHR
IOS
KQ8
KZ1
LMP
MIO
MV1
NGNOM
O9-
OK1
P2P
RHU
RHW
RHX
TUS
24P
AAMMB
AAYXX
ACCMX
AEFGJ
AGXDD
AIDQK
AIDYY
ALUQN
CITATION
H13
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c1822-ad9aa69d948eaba30a2297202c07b3a0d3d42d61a18301e8b4c8a294cdbfaa3d3
IEDL.DBID RHX
ISSN 1574-017X
IngestDate Fri Jul 25 09:29:36 EDT 2025
Sat Nov 29 02:31:03 EST 2025
Tue Nov 18 22:43:52 EST 2025
Sun Jun 02 19:20:30 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Language English
License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
https://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1822-ad9aa69d948eaba30a2297202c07b3a0d3d42d61a18301e8b4c8a294cdbfaa3d3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-6352-6355
OpenAccessLink https://dx.doi.org/10.1155/2023/1687672
PQID 2807764542
PQPubID 2048814
PageCount 15
ParticipantIDs proquest_journals_2807764542
crossref_primary_10_1155_2023_1687672
crossref_citationtrail_10_1155_2023_1687672
hindawi_primary_10_1155_2023_1687672
PublicationCentury 2000
PublicationDate 2023-4-21
PublicationDateYYYYMMDD 2023-04-21
PublicationDate_xml – month: 04
  year: 2023
  text: 2023-4-21
  day: 21
PublicationDecade 2020
PublicationPlace Amsterdam
PublicationPlace_xml – name: Amsterdam
PublicationTitle Mobile information systems
PublicationYear 2023
Publisher Hindawi
John Wiley & Sons, Inc
Publisher_xml – name: Hindawi
– name: John Wiley & Sons, Inc
References 24
25
26
M. Tang (40) 2020
27
S. Balasubramanian (23)
28
Q. Li (29) 2019; 16
30
Y. Ouyang (37) 2021
31
10
32
11
33
12
34
13
35
14
36
15
16
38
17
39
18
Z. Shuchen (22) 2020; 178
19
1
2
Y. Jie (21) 2019; 16
4
5
6
7
8
9
M. Muniswamaiah (3)
41
20
References_xml – ident: 8
  doi: 10.23919/jcc.2019.10.013
– volume: 16
  start-page: 22
  issue: 3
  year: 2019
  ident: 21
  article-title: Game-theoretic online resource allocation scheme on fog computing for mobile multimedia users
  publication-title: China Commun
– volume: 178
  start-page: 1389
  issue: 3
  year: 2020
  ident: 22
  article-title: The partial computation offloading strategy based on game theory for multi-user in mobile edge computing environment
  publication-title: Computer Networks
– volume: 16
  start-page: 32
  issue: 3
  year: 2019
  ident: 29
  article-title: Energy-efficient computation offloading and resource allocation in fog computing for internet of everything
  publication-title: China Commun
– ident: 1
  doi: 10.1109/access.2020.3022661
– start-page: 139
  ident: 3
  article-title: A Survey on Cloudlets, mobile Edge, and Fog Computing
– ident: 10
  doi: 10.1109/twc.2017.2703901
– ident: 16
  doi: 10.1109/jiot.2020.2971323
– volume-title: Journal of Physics: Conference Series
  year: 2021
  ident: 37
  article-title: Task offloading algorithm of vehicle edge computing environment based on Dueling-DQN
  doi: 10.1088/1742-6596/1873/1/012046
– ident: 9
  doi: 10.1109/access.2019.2929075
– ident: 15
  doi: 10.1109/access.2019.2941741
– ident: 11
  doi: 10.1109/ACCESS.2020.3000832
– ident: 24
  doi: 10.1109/jcn.2018.000036
– ident: 28
  doi: 10.1109/twc.2020.3007805
– ident: 41
  doi: 10.1109/access.2021.3058021
– ident: 33
  doi: 10.1109/access.2019.2947542
– ident: 6
  doi: 10.1109/JIOT.2022.3168885
– ident: 31
  doi: 10.1109/tmc.2019.2952354
– ident: 13
  doi: 10.1109/twc.2018.2821664
– ident: 20
  doi: 10.1109/TMC.2019.2892953
– start-page: 1
  year: 2020
  ident: 40
  article-title: Deep reinforcement learning for task offloading in mobile edge computing systems
  publication-title: IEEE Transactions on Mobile Computing
– ident: 7
  doi: 10.1109/tmc.2020.2967041
– ident: 5
  doi: 10.1109/ACCESS.2019.2947652
– ident: 32
  doi: 10.1109/tc.2020.2993561
– ident: 36
  doi: 10.1109/ICCC52777.2021.9580391
– ident: 17
  doi: 10.1049/iet-com.2017.0213
– ident: 25
  doi: 10.1109/TVT.2019.2919915
– ident: 38
  doi: 10.1109/tmc.2019.2928811
– ident: 19
  doi: 10.1109/jiot.2020.2972061
– ident: 35
  doi: 10.1109/PIMRC48278.2020.9217355
– ident: 12
  doi: 10.1109/tvt.2020.2981122
– ident: 34
  doi: 10.23919/icn.2020.0020
– ident: 39
  doi: 10.1109/access.2020.3004861
– ident: 26
  doi: 10.1109/JSAC.2020.3020659
– ident: 18
  doi: 10.1109/access.2021.3067702
– ident: 14
  doi: 10.1109/tvt.2018.2881191
– ident: 23
  article-title: Enhancing the computational intelligence of smart fog gateway with boundary-constrained dynamic time warping based imputation and data reduction
  doi: 10.1109/ICISPC.2019.8935698
– ident: 27
  doi: 10.1109/TWC.2020.2978843
– ident: 30
  doi: 10.1109/tcss.2020.3005761
– ident: 2
  doi: 10.1109/ACCESS.2020.3045304
– ident: 4
  doi: 10.1109/jiot.2020.3022699
SSID ssj0060357
ssib050733852
Score 2.2595866
Snippet With the dramatic increase in the number of emerging Internet services, the Fog-Radio Access Network (F-RAN) has recently emerged as a promising paradigm to...
SourceID proquest
crossref
hindawi
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1
SubjectTerms Algorithms
Communication
Computation offloading
Convex analysis
Decision making
Deep learning
Edge computing
Electronic devices
Energy consumption
Game theory
Integer programming
Internet of Things
Mixed integer
Neural networks
Nonlinear programming
Optimization
Reputations
Resource allocation
Servers
Strategy
Title Joint Optimization of Resources in Fog-Radio Access Network with Binary Computation Offloading
URI https://dx.doi.org/10.1155/2023/1687672
https://www.proquest.com/docview/2807764542
Volume 2023
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 1875-905X
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssib050733852
  issn: 1574-017X
  databaseCode: M~E
  dateStart: 20050101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVWIB
  databaseName: Wiley Online Library Open Access
  customDbUrl:
  eissn: 1875-905X
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0060357
  issn: 1574-017X
  databaseCode: 24P
  dateStart: 20050101
  isFulltext: true
  titleUrlDefault: https://authorservices.wiley.com/open-science/open-access/browse-journals.html
  providerName: Wiley-Blackwell
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3fS8MwEA5uKPjib3E6Rx7mkxTbNG2axymOIbKNodInS9KkWpitrFP_fZM0FXSIPhaOg15yd7nku-8A6EskMo6QdFQyYA5mIXJ46GZOJIMIERQG0qAJH27JeBzFMZ1akqRq9QlfZTtdnvsXXqjclqhY24oCjdyajeJm2wR67qBpAa4DcOj6huDTC4gGWJC4wbv_0PUtE2086xL4I18JySbPDHfAlj0gwkG9ortgTRZ7YLsZvgCtL-6Dx5syL5Zwolz-xfZSwjKDzXV8BfMCDssnZ8ZEXsKBmYsIxzXoG-rbV3hpWnFhrbpWMMmyeWlQ9Qfgfnh9dzVy7LAEJ1UlAnKYoIyFVFAcScaZ7zKEKFH_m7qE-8wVvsBIhB5TPux6MuI4jRiiOBU8Y8wX_iFoF2UhjwCMKOfqpEcxphJzgbke-oczKpGXel7odsB5Y7gktUzieqDFPDEVRRAk2syJNXMHnH1Jv9YMGr_I9e0a_CHWbRYose5WJZrSh2huMnT8Py0nYFN_6mch5HVBe7l4k6dgPX1f5tWiB1oIT3tmk30C7GXGTg
linkProvider Hindawi Publishing
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Joint+Optimization+of+Resources+in+Fog-Radio+Access+Network+with+Binary+Computation+Offloading&rft.jtitle=Mobile+information+systems&rft.au=Bai%2C+Wenle&rft.au=Wang%2C+Zhuoqi&rft.date=2023-04-21&rft.pub=John+Wiley+%26+Sons%2C+Inc&rft.issn=1574-017X&rft.eissn=1875-905X&rft.volume=2023&rft_id=info:doi/10.1155%2F2023%2F1687672&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1574-017X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1574-017X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1574-017X&client=summon