Joint Optimization of Task Partial Offloading and Resource Allocation in a Dual-Blockchain-Enabled MEC System with Parallelism Constraints

Integrating data security with resource management enhances security, efficiency, and reliability of blockchain-enabled mobile edge computing (MEC) systems. However, challenges such as secure data storage, timely task execution, and limited parallelism introduce complexities in task offloading decis...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on communications p. 1
Main Authors: Huang, Xiaowen, Huang, Tao, Zhao, Shuguang, Xiang, Wei, Zhang, Wenqian, Zhang, Guanglin
Format: Journal Article
Language:English
Published: IEEE 2025
Subjects:
blockchain
Blockchains
Computational modeling
Delays
Heuristic algorithms
Memory
Mobile edge computing
Optimization
Parallel processing
parallelism
Reliability
Resource management
Servers
task partial offloading
ISSN:0090-6778, 1558-0857
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Integrating data security with resource management enhances security, efficiency, and reliability of blockchain-enabled mobile edge computing (MEC) systems. However, challenges such as secure data storage, timely task execution, and limited parallelism introduce complexities in task offloading decisions and resource allocation strategies. To address these challenges, the task latency minimization problem in blockchain-enabled MEC networks is formulated as an NP-hard optimization problem. The model incorporates constraints on parallelism, partial task offloading, bandwidth and computation resource allocation among mobile users (MUs) and edge servers (ESs). To enhance the reliability and transparency of data storage, a dual-blockchain framework is proposed, consisting of multiple MU blockchains and a dedicated ES blockchain. To tackle the NP-hard problem, the original optimization problem is decomposed into multiple sub-problems, facilitating parameter decoupling. An alternating optimization algorithm is employed to refine task offloading decisions and resource allocation of MUs and ESs with limited parallelism. The ESs update their strategies iteratively based on feedback mechanisms. Additionally, a task prioritization formulation is developed to enhance scalability, considering sub-level task importance, urgency, and first-level task classification. Extensive simulation experiments demonstrate that the proposed algorithm achieves lower task latency compared to existing methods across varying network sizes, offloading schemes, and parallelism constraints. By optimizing the parallel processing of tasks, the waiting latency of this algorithm is reduced on average by 35. 35%, 57. 16% and 35. 35% compared to other methods, respectively.
AbstractList Integrating data security with resource management enhances security, efficiency, and reliability of blockchain-enabled mobile edge computing (MEC) systems. However, challenges such as secure data storage, timely task execution, and limited parallelism introduce complexities in task offloading decisions and resource allocation strategies. To address these challenges, the task latency minimization problem in blockchain-enabled MEC networks is formulated as an NP-hard optimization problem. The model incorporates constraints on parallelism, partial task offloading, bandwidth and computation resource allocation among mobile users (MUs) and edge servers (ESs). To enhance the reliability and transparency of data storage, a dual-blockchain framework is proposed, consisting of multiple MU blockchains and a dedicated ES blockchain. To tackle the NP-hard problem, the original optimization problem is decomposed into multiple sub-problems, facilitating parameter decoupling. An alternating optimization algorithm is employed to refine task offloading decisions and resource allocation of MUs and ESs with limited parallelism. The ESs update their strategies iteratively based on feedback mechanisms. Additionally, a task prioritization formulation is developed to enhance scalability, considering sub-level task importance, urgency, and first-level task classification. Extensive simulation experiments demonstrate that the proposed algorithm achieves lower task latency compared to existing methods across varying network sizes, offloading schemes, and parallelism constraints. By optimizing the parallel processing of tasks, the waiting latency of this algorithm is reduced on average by 35. 35%, 57. 16% and 35. 35% compared to other methods, respectively.
Author Zhao, Shuguang
Xiang, Wei
Huang, Xiaowen
Zhang, Wenqian
Huang, Tao
Zhang, Guanglin
Author_xml – sequence: 1
  givenname: Xiaowen
  orcidid: 0000-0001-6323-7070
  surname: Huang
  fullname: Huang, Xiaowen
  email: huangxiaowen@mail.dhu.edu.cn
  organization: College of Information Science and Technology, Donghua University, Shanghai, China
– sequence: 2
  givenname: Tao
  orcidid: 0000-0002-8098-8906
  surname: Huang
  fullname: Huang, Tao
  email: tao.huang1@jcu.edu.au
  organization: College of Science and Engineering, James Cook University, Smithfield, QLD, Australia
– sequence: 3
  givenname: Shuguang
  orcidid: 0000-0002-6359-4091
  surname: Zhao
  fullname: Zhao, Shuguang
  email: sgzhao@dhu.edu.cn
  organization: College of Information Science and Technology, Donghua University, Shanghai, China
– sequence: 4
  givenname: Wei
  orcidid: 0000-0002-0608-065X
  surname: Xiang
  fullname: Xiang, Wei
  email: w.xiang@latrobe.edu.au
  organization: School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia
– sequence: 5
  givenname: Wenqian
  orcidid: 0000-0003-2007-6478
  surname: Zhang
  fullname: Zhang, Wenqian
  email: wqzhang@dhu.edu.cn
  organization: College of Information Science and Technology, Donghua University, Shanghai, China
– sequence: 6
  givenname: Guanglin
  orcidid: 0000-0003-4095-6843
  surname: Zhang
  fullname: Zhang, Guanglin
  email: glzhang@dhu.edu.cn
  organization: College of Information Science and Technology, Donghua University, Shanghai, China
BookMark eNpFkM1OAjEUhRuDiYC-gHHRFxhsp9POsMQR_wLBKPvJZeZWKqUl0xKDj-BTC0Li6iQn5zuLr0c6zjsk5JqzAedseDsvZ9PpIGWpHAjFGVf5GelyKYuEFTLvkC5jQ5aoPC8uSC-ET8ZYxoTokp8Xb1yks000a_MN0XhHvaZzCCv6Cm00YOlMa-uhMe6DgmvoGwa_bWukI2t9fUSMo0Dvt2CTu323qpdgXDJ2sLDY0Om4pO-7EHFNv0xcHn7BWrQmrGnpXYjtfh3DJTnXYANenbJP5g_jefmUTGaPz-VoktRcqJhADqgwKyBLBQ51I4a6KBouG8wWgqUqY0qmWkGGGUgOuWo0pk2BUEixyLTok_R4W7c-hBZ1tWnNGtpdxVl1kFn9yawOMquTzD10c4QMIv4DnCu5Fyx-AQUcdV4
CODEN IECMBT
ContentType Journal Article
DBID 97E
RIA
RIE
AAYXX
CITATION
DOI 10.1109/TCOMM.2025.3610167
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005-present
IEEE All-Society Periodicals Package (ASPP) 1998-Present
IEEE Electronic Library (IEL)
CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1558-0857
EndPage 1
ExternalDocumentID 10_1109_TCOMM_2025_3610167
11165085
Genre orig-research
GroupedDBID -~X
.DC
0R~
29I
4.4
5GY
6IK
85S
97E
AAJGR
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ACNCT
AENEX
AGQYO
AHBIQ
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
HZ~
IES
IFIPE
IPLJI
JAVBF
LAI
MS~
O9-
OCL
P2P
RIA
RIE
RNS
TAE
TN5
ZCA
3EH
5VS
AAYXX
ABFSI
ACKIV
AETIX
AGSQL
AI.
AIBXA
ALLEH
CITATION
E.L
EJD
H~9
IAAWW
IBMZZ
ICLAB
IFJZH
M43
VH1
ZCG
ID FETCH-LOGICAL-c136t-a7ae6e48a423e9fd39f88d15de4b302640652f6a4e4a51a76dfe2d8ea853b4f3
IEDL.DBID RIE
ISSN 0090-6778
IngestDate Sat Nov 29 07:27:20 EST 2025
Wed Oct 01 07:05:18 EDT 2025
IsPeerReviewed true
IsScholarly true
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-c136t-a7ae6e48a423e9fd39f88d15de4b302640652f6a4e4a51a76dfe2d8ea853b4f3
ORCID 0000-0003-2007-6478
0000-0001-6323-7070
0000-0002-0608-065X
0000-0002-6359-4091
0000-0002-8098-8906
0000-0003-4095-6843
PageCount 1
ParticipantIDs ieee_primary_11165085
crossref_primary_10_1109_TCOMM_2025_3610167
PublicationCentury 2000
PublicationDate 2025-00-00
PublicationDateYYYYMMDD 2025-01-01
PublicationDate_xml – year: 2025
  text: 2025-00-00
PublicationDecade 2020
PublicationTitle IEEE transactions on communications
PublicationTitleAbbrev TCOMM
PublicationYear 2025
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0004033
Score 2.4637666
Snippet Integrating data security with resource management enhances security, efficiency, and reliability of blockchain-enabled mobile edge computing (MEC) systems....
SourceID crossref
ieee
SourceType Index Database
Publisher
StartPage 1
SubjectTerms blockchain
Blockchains
Computational modeling
Delays
Heuristic algorithms
Memory
Mobile edge computing
Optimization
Parallel processing
parallelism
Reliability
Resource management
Servers
task partial offloading
Title Joint Optimization of Task Partial Offloading and Resource Allocation in a Dual-Blockchain-Enabled MEC System with Parallelism Constraints
URI https://ieeexplore.ieee.org/document/11165085
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVIEE
  databaseName: IEEE Electronic Library (IEL)
  customDbUrl:
  eissn: 1558-0857
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0004033
  issn: 0090-6778
  databaseCode: RIE
  dateStart: 19720101
  isFulltext: true
  titleUrlDefault: https://ieeexplore.ieee.org/
  providerName: IEEE
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELZoxQADzyLKSx7YUNqkdmJnLKUVQupjyNAtcvwQUdMENSk_gl-N7aSiDAxsiZWLIt_J98h99wHwSAJhEKHaeKnCDqbKc5JE33KCheeKhCtVk02Q2Ywul-GiAatbLIyU0jafyZ65tP_yRcG3plTW98ysGB0jtECLkKAGa_2AIF3UjJw0_eyE7hAybtiPRvPpVOeCA7-HApOukl9eaI9WxXqVyek_v-cMnDThIxzW-j4HBzK_AMd7QwUvwddbkeYVnOuzYN2ALGGhYMTKFVwYQ9Hyc6WywnbPQ5YLuKvhw2FmfJsVSXPI4MuWZc6zXlvxd5bmztgirQScjkewnnUOTSHXvNdwsmRpuYaGAtQST1RlB0STcTR6dRrGBYd7KKgcRpgMJKZMB1kyVAKFilLh-ULiBOlsTXt_f6AChiVmvse0opUcCCqZdvoJVugKtPMil9cAEhUgTxHlCRRg4eqDw00YktTlFPMkZF3wtFNA_FHP1YhtPuKGsVVXbNQVN-rqgo7Z_Z8nm42_-WP9FhwZ8bpUcgfa1WYr78Eh_6zScvNg7eYbZQDClQ
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NT8IwFG8UTdSDnxjxswdvZrDRbuuOiBBUBhx24LZ0axsXYDNs-Ef4V9t2I-DBg7etWZulv5e-j77fewA8ug5TjFApvERgAxNhGVEkX2MXM8tkUSxE2WzCHY3IdOpNKrK65sJwznXyGW-qR32Xz7J4pUJlLUvVipE2wi7YszFumyVda0ODNFFVdFJltLtkzZExvVbQHfu-9AbbdhM5ymF1f-mhrcYqWq_0T_75R6fguDIgYadE_Azs8PQcHG2VFbwA329ZkhZwLE-DRUWzhJmAAc1ncKJERc4fCzHPdP48pCmD6yg-7MyVdtNTkhRS-LKic-NZjs3iD5qkRk9zrRj0e11YVjuHKpSr1lVdWeZJvoCqCahuPVHkdRD0e0F3YFQ9F4zYQk5hUJdyh2NCpZnFPcGQJwhhls04jpD016T-t9vCoZhjaltUQi14mxFOpdqPsECXoJZmKb8C0BUOsoQrLIYczEx5dJgRRZyYMcFx5NEGeFoDEH6WlTVC7ZGYXqjhChVcYQVXA9TV7m--rDb--o_xB3AwCPxhOHwdvd-AQ7VUGTi5BbViueJ3YD_-KpJ8ea9l6AetmMXc
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+Task+Partial+Offloading+and+Resource+Allocation+in+a+Dual-Blockchain-Enabled+MEC+System+with+Parallelism+Constraints&rft.jtitle=IEEE+transactions+on+communications&rft.au=Huang%2C+Xiaowen&rft.au=Huang%2C+Tao&rft.au=Zhao%2C+Shuguang&rft.au=Xiang%2C+Wei&rft.date=2025&rft.pub=IEEE&rft.issn=0090-6778&rft.spage=1&rft.epage=1&rft_id=info:doi/10.1109%2FTCOMM.2025.3610167&rft.externalDocID=11165085
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0090-6778&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0090-6778&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0090-6778&client=summon