Hybrid NOMA-OMA Transmission Scheduling for Production Efficiency Maximization in Industrial Edge Computing Networks

We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory are equipped with sensing devices. They sense raw products, generate and offload computing tasks, and finally process the raw products based on...

Full description

Saved in:
Bibliographic Details
Published inIEEE internet of things journal Vol. 11; no. 23; pp. 37493 - 37508
Main Authors Zhao, Yunzhi, Pei, Yanhua, Liu, Yong, Hou, Fen, Zhuang, Weihua
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.12.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Assembly lines
Computation offloading
Decomposition
Delay requirement
Delays
Edge computing
Efficiency
hybrid transmission
Industrial applications
Industrial Internet of Things
Industrial Internet of Things (IIoT)
Internet of Things
Maximization
Mobile computing
mobile edge computing (MEC)
NOMA
Nonorthogonal multiple access
Optimization
Production
Production scheduling
Quality of service
Quality of service architectures
Resource management
Sensors
Task analysis
task priority
Task scheduling
Online AccessGet full text
ISSN2327-4662
2327-4662
DOI10.1109/JIOT.2024.3433558

Cover

Abstract We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory are equipped with sensing devices. They sense raw products, generate and offload computing tasks, and finally process the raw products based on the computing results. In this scenario, different positions of the processing machines lead to different priorities and diverse Quality-of-Service (QoS) requirements of tasks. Therefore, how to schedule tasks and allocate the network resources becomes a critical and challenging issue. In this study, we introduce a novel batch-based hybrid nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) transmission scheme. The selection between NOMA and OMA schemes is optimized based on the QoS requirements of tasks. Then, we formulate a production efficiency maximization problem with the objective of maximizing the speed of the assembly lines subject to the deadline constraints of offloading and computing procedures. To this end, a two-layer decomposition method is used to decompose the formulated problem into two subproblems. Furthermore, we utilize a bisection searching method to approximate the optimal solution, and propose an efficient method to determine the feasibility of the top-layer subproblem. Simulation results demonstrate the significant performance improvement of our proposed method. In specific, the production efficiency is enhanced by 525% in comparison with pure NOMA scheme.
AbstractList We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory are equipped with sensing devices. They sense raw products, generate and offload computing tasks, and finally process the raw products based on the computing results. In this scenario, different positions of the processing machines lead to different priorities and diverse Quality-of-Service (QoS) requirements of tasks. Therefore, how to schedule tasks and allocate the network resources becomes a critical and challenging issue. In this study, we introduce a novel batch-based hybrid nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) transmission scheme. The selection between NOMA and OMA schemes is optimized based on the QoS requirements of tasks. Then, we formulate a production efficiency maximization problem with the objective of maximizing the speed of the assembly lines subject to the deadline constraints of offloading and computing procedures. To this end, a two-layer decomposition method is used to decompose the formulated problem into two subproblems. Furthermore, we utilize a bisection searching method to approximate the optimal solution, and propose an efficient method to determine the feasibility of the top-layer subproblem. Simulation results demonstrate the significant performance improvement of our proposed method. In specific, the production efficiency is enhanced by 525% in comparison with pure NOMA scheme.
Author Pei, Yanhua
Zhao, Yunzhi
Zhuang, Weihua
Liu, Yong
Hou, Fen
Author_xml – sequence: 1
  givenname: Yunzhi
  surname: Zhao
  fullname: Zhao, Yunzhi
  email: yc17449@um.edu.mo
  organization: Department of Electrical and Computer Engineering, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China
– sequence: 2
  givenname: Yanhua
  orcidid: 0009-0000-0590-8227
  surname: Pei
  fullname: Pei, Yanhua
  email: yb87477@um.edu.mo
  organization: Department of Electrical and Computer Engineering, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China
– sequence: 3
  givenname: Yong
  orcidid: 0000-0002-2332-9066
  surname: Liu
  fullname: Liu, Yong
  email: yliu@m.scnu.edu.cn
  organization: School of Electronics and Information Engineering, South China Normal University, Foshan, China
– sequence: 4
  givenname: Fen
  orcidid: 0000-0003-2784-816X
  surname: Hou
  fullname: Hou, Fen
  email: fenhou@um.edu.mo
  organization: Department of Electrical and Computer Engineering, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China
– sequence: 5
  givenname: Weihua
  orcidid: 0000-0003-0488-511X
  surname: Zhuang
  fullname: Zhuang, Weihua
  email: wzhuang@uwaterloo.ca
  organization: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
BookMark eNpNkMtOwzAQRS0EEq9-ABILS6xT_G6yRFWhRYUiUdZR6oyLobGLnQjK1-NQFixGM_Lce8c6p-jQeQcIXVAypJQU1_ezxXLICBNDLjiXMj9AJ4yzUSaUYof_5mM0iPGNEJJskhbqBLXT3SrYGj8uHm6yVHgZKhcbG6P1Dj_rV6i7jXVrbHzAT8HXnW77zcQYqy04vcMP1Zdt7Hf1-24dnrm6i22w1QZP6jXgsW-2XdtnPEL76cN7PEdHptpEGPz1M_RyO1mOp9l8cTcb38wzzYRqM9BGCilZQVeQEwK5GbGKCT4CA1rKujas4Do3SuiCCEa14kVOOYiVAqlGip-hq33uNviPDmJbvvkuuHSy5JSTgrPEKqnoXqWDjzGAKbfBNlXYlZSUPd-y51v2fMs_vslzufdYAPinVyk0feEHmXV4-g
CODEN IITJAU
Cites_doi 10.1109/TETC.2021.3090061
10.1109/TVT.2017.2764002
10.1109/JIOT.2023.3279112
10.1109/WCNC49053.2021.9417322
10.1109/TCOMM.2020.3047440
10.1109/TII.2020.3019572
10.1109/JIOT.2018.2875046
10.1109/TWC.2020.2988532
10.1109/TII.2022.3206787
10.1109/JIOT.2021.3055510
10.1109/JIOT.2019.2959035
10.1109/JIOT.2024.3369069
10.1109/TII.2018.2852491
10.1109/MWC.2001.2200396
10.1109/JIOT.2020.2965898
10.1109/TCC.2018.2858266
10.1109/WCSP.2019.8928122
10.1109/TMC.2021.3051670
10.1109/TWC.2022.3185825
10.1109/TII.2022.3170900
10.1109/TWC.2021.3139932
10.1109/TMC.2018.2812722
10.1109/TII.2021.3125376
10.1007/s10723-021-09578-8
10.1109/JIOT.2021.3123554
10.1109/COMST.2017.2705720
10.1109/JSAC.2020.3018809
10.1016/j.sintl.2021.100129
10.1109/TNSE.2022.3176924
10.1109/TII.2022.3158974
10.1109/JSTSP.2019.2893057
10.1109/TMC.2021.3064314
10.1109/CSICC58665.2023.10105378
10.1109/TCOMM.2020.3020068
10.1109/TMC.2020.3017079
10.1109/JIOT.2022.3177425
10.23919/ICACT56868.2023.10079379
10.1109/TCOMM.2021.3070620
10.1109/TWC.2022.3194685
10.1109/JIOT.2019.2896946
10.1109/OJCOMS.2020.2969899
10.1007/s12083-022-01348-x
10.1109/JIOT.2018.2797187
10.1109/TII.2021.3117968
10.1109/WPMC52694.2021.9700453
10.1109/TVT.2023.3270859
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
DBID 97E
RIA
RIE
AAYXX
CITATION
7SC
8FD
JQ2
L7M
L~C
L~D
DOI 10.1109/JIOT.2024.3433558
DatabaseName IEEE Xplore (IEEE)
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
Computer and Information Systems 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
Computer and Information Systems Abstracts
Technology Research Database
Computer and Information Systems Abstracts – Academic
Advanced Technologies Database with Aerospace
ProQuest Computer Science Collection
Computer and Information Systems Abstracts Professional
DatabaseTitleList
Computer and Information Systems Abstracts
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 2327-4662
EndPage 37508
ExternalDocumentID 10_1109_JIOT_2024_3433558
10609381
Genre orig-research
GrantInformation_xml – fundername: Natural Science Foundation of Guangdong Province
  grantid: 2022A1515010111; 2023A1515012890
– fundername: National Natural Science Foundation of China
  grantid: 62101369; 61901180
  funderid: 10.13039/501100001809
– fundername: Science and Technology Project of Guangzhou
  grantid: 202201010574
– fundername: Macau Young Scholars Program
  grantid: AM2021017
– fundername: University of Macau
  grantid: MYRG2022-00242-FST; MYRG-GRG2023-00200-FST
  funderid: 10.13039/501100005195
– fundername: Science and Technology Development Fund, Macau, SAR
  grantid: 0119 /2020/A3; SKL-IOTSC(UM)-2024-2026
GroupedDBID 0R~
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABJNI
ABQJQ
ABVLG
AGQYO
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
EBS
IFIPE
IPLJI
JAVBF
M43
OCL
PQQKQ
RIA
RIE
AAYXX
CITATION
7SC
8FD
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c246t-ecf5455291be800e8f72a2437efec55ddf293c8f64c90421c639813e4b6e56763
IEDL.DBID RIE
ISSN 2327-4662
IngestDate Mon Jun 30 12:59:14 EDT 2025
Tue Jul 01 00:38:11 EDT 2025
Wed Aug 27 03:06:45 EDT 2025
IsPeerReviewed false
IsScholarly true
Issue 23
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-037
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c246t-ecf5455291be800e8f72a2437efec55ddf293c8f64c90421c639813e4b6e56763
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-0488-511X
0000-0002-2332-9066
0000-0003-2784-816X
0009-0000-0590-8227
PQID 3130932558
PQPubID 2040421
PageCount 16
ParticipantIDs proquest_journals_3130932558
ieee_primary_10609381
crossref_primary_10_1109_JIOT_2024_3433558
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2024-12-01
PublicationDateYYYYMMDD 2024-12-01
PublicationDate_xml – month: 12
  year: 2024
  text: 2024-12-01
  day: 01
PublicationDecade 2020
PublicationPlace Piscataway
PublicationPlace_xml – name: Piscataway
PublicationTitle IEEE internet of things journal
PublicationTitleAbbrev JIoT
PublicationYear 2024
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref35
ref12
ref34
ref15
ref37
ref14
ref36
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref39
ref16
ref38
ref19
ref18
ref24
ref46
ref23
ref45
ref26
ref25
ref20
ref42
ref41
ref22
ref44
ref21
ref43
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
References_xml – ident: ref3
  doi: 10.1109/TETC.2021.3090061
– ident: ref15
  doi: 10.1109/TVT.2017.2764002
– ident: ref17
  doi: 10.1109/JIOT.2023.3279112
– ident: ref21
  doi: 10.1109/WCNC49053.2021.9417322
– ident: ref30
  doi: 10.1109/TCOMM.2020.3047440
– ident: ref4
  doi: 10.1109/TII.2020.3019572
– ident: ref45
  doi: 10.1109/JIOT.2018.2875046
– ident: ref33
  doi: 10.1109/TWC.2020.2988532
– ident: ref37
  doi: 10.1109/TII.2022.3206787
– ident: ref34
  doi: 10.1109/JIOT.2021.3055510
– ident: ref24
  doi: 10.1109/JIOT.2019.2959035
– ident: ref39
  doi: 10.1109/JIOT.2024.3369069
– ident: ref22
  doi: 10.1109/TII.2018.2852491
– ident: ref2
  doi: 10.1109/MWC.2001.2200396
– ident: ref40
  doi: 10.1109/JIOT.2020.2965898
– ident: ref8
  doi: 10.1109/TCC.2018.2858266
– ident: ref29
  doi: 10.1109/WCSP.2019.8928122
– ident: ref18
  doi: 10.1109/TMC.2021.3051670
– ident: ref10
  doi: 10.1109/TWC.2022.3185825
– ident: ref27
  doi: 10.1109/TII.2022.3170900
– ident: ref32
  doi: 10.1109/TWC.2021.3139932
– ident: ref41
  doi: 10.1109/TMC.2018.2812722
– ident: ref13
  doi: 10.1109/TII.2021.3125376
– ident: ref46
  doi: 10.1007/s10723-021-09578-8
– ident: ref14
  doi: 10.1109/JIOT.2021.3123554
– ident: ref9
  doi: 10.1109/COMST.2017.2705720
– ident: ref19
  doi: 10.1109/JSAC.2020.3018809
– ident: ref23
  doi: 10.1016/j.sintl.2021.100129
– ident: ref35
  doi: 10.1109/TNSE.2022.3176924
– ident: ref1
  doi: 10.1109/TII.2022.3158974
– ident: ref42
  doi: 10.1109/JSTSP.2019.2893057
– ident: ref5
  doi: 10.1109/TMC.2021.3064314
– ident: ref20
  doi: 10.1109/CSICC58665.2023.10105378
– ident: ref43
  doi: 10.1109/TCOMM.2020.3020068
– ident: ref7
  doi: 10.1109/TMC.2020.3017079
– ident: ref12
  doi: 10.1109/JIOT.2022.3177425
– ident: ref31
  doi: 10.23919/ICACT56868.2023.10079379
– ident: ref44
  doi: 10.1109/TCOMM.2021.3070620
– ident: ref11
  doi: 10.1109/TWC.2022.3194685
– ident: ref36
  doi: 10.1109/JIOT.2019.2896946
– ident: ref16
  doi: 10.1109/OJCOMS.2020.2969899
– ident: ref28
  doi: 10.1007/s12083-022-01348-x
– ident: ref6
  doi: 10.1109/JIOT.2018.2797187
– ident: ref25
  doi: 10.1109/TII.2021.3117968
– ident: ref38
  doi: 10.1109/WPMC52694.2021.9700453
– ident: ref26
  doi: 10.1109/TVT.2023.3270859
SSID ssj0001105196
Score 2.3444827
Snippet We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Index Database
Publisher
StartPage 37493
SubjectTerms Assembly lines
Computation offloading
Decomposition
Delay requirement
Delays
Edge computing
Efficiency
hybrid transmission
Industrial applications
Industrial Internet of Things
Industrial Internet of Things (IIoT)
Internet of Things
Maximization
Mobile computing
mobile edge computing (MEC)
NOMA
Nonorthogonal multiple access
Optimization
Production
Production scheduling
Quality of service
Quality of service architectures
Resource management
Sensors
Task analysis
task priority
Task scheduling
Title Hybrid NOMA-OMA Transmission Scheduling for Production Efficiency Maximization in Industrial Edge Computing Networks
URI https://ieeexplore.ieee.org/document/10609381
https://www.proquest.com/docview/3130932558
Volume 11
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8NAEF60Jy_WR8VqlT14ElLz3CTHIi210NRDC72FZDOrRWzFpqD-emd2E-oDwUMgkE2y7OzsfLM73wxjV1IpEUo7tjLPjy1fgbIyKFzLVnYe5ARgNb9inIjhzB_Ng3lFVtdcGADQwWfQpVt9ll-s5Ia2ylDDBTrgRLTeRc_NkLW2GyoOoRFRnVw6dnwzuptM0QN0_a7ne5RG_Jvt0cVUfq3A2qwMmiypO2SiSZ66mzLvyo8fuRr_3eMDtl8BTN4zM-KQ7cDyiDXr4g280uVjVg7fiazFk8m4Z-HFtdVCqdP2GTZ7RBtEVHWOqJbfm7yw9KSvc04QYZOPs7fFc8Xj5Isl35YB4f3iAbj5KX0jMcHm6xabDfrT26FVlWCwpOuL0gKpEGIFbuzkgNASIhW6GeUwBAUyCIpCIVyQkRK-jFH9HYmAJ3I88HMBgcC164Q1lqslnDIuIumJ2M1CmaHPE6MrFUJUSJwd6LIIL2-z61o46YvJtJFqD8WOU5JkSpJMK0m2WYsG-0tDM85t1qnlmVbKuE49h4570XeKzv547Zzt0ddNmEqHNcrXDVwg2CjzSz3JPgGpoNNN
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LSwMxEA6iB734rFitmoMnYes-sunmWKRSH916aKG3ZTc7URGr6BbUX-9MssUXgoeFhU02IZNkvknmm2HsSBsjO9pXXh4J5QkDxsuhDD3f-EVcEIC1_IpBKvtjcTGJJzVZ3XJhAMA6n0GbXu1dfvmoZ3RUhitcogFOROslVPxCObrW55FKQHhE1neXga9OLs6HI7QBQ9GORESBxL9pH5tO5dcebBXL2RpL511y_iT37VlVtPX7j2iN_-7zOlutISbvujmxwRZgusnW5ukbeL2at1jVfyO6Fk-Hg66HD7d6C-VOB2hY7Ba1EJHVOeJafu0iw9KXno06QZRNPshf7x5qJie_m_LPRCC8V94Ad43SP1Lnbv7SYOOz3ui079VJGDwdCll5oA2OdRyqoAAEl5CYTphTFEMwoOO4LA0CBp0YKbTCDSDQCHmSIAJRSIgl7l7bbHH6OIUdxmWiI6nCvKNztHoUGlMdSEqN8wONFhkVTXY8F0725GJtZNZG8VVGksxIklktySZr0GB_KejGuclac3lm9XJ8yaKALnzRekp2_6h2yJb7o8FVdnWeXu6xFWrJOa202GL1PIN9hB5VcWAn3AfpPdad
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=Hybrid+NOMA-OMA+Transmission+Scheduling+for+Production+Efficiency+Maximization+in+Industrial+Edge+Computing+Networks&rft.jtitle=IEEE+internet+of+things+journal&rft.au=Zhao%2C+Yunzhi&rft.au=Pei%2C+Yanhua&rft.au=Liu%2C+Yong&rft.au=Hou%2C+Fen&rft.date=2024-12-01&rft.pub=IEEE&rft.eissn=2327-4662&rft.volume=11&rft.issue=23&rft.spage=37493&rft.epage=37508&rft_id=info:doi/10.1109%2FJIOT.2024.3433558&rft.externalDocID=10609381
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2327-4662&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2327-4662&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2327-4662&client=summon