MOSO: multi-objective snake optimizer with density estimation and grid indexing mechanism for edge computing task offloading and scheduling optimization

The proposal of task offloading and scheduling optimization in edge computing aims to effectively alleviate network congestion caused by a large amount of data in ultra-dense networks (UDN), minimize energy consumption during data transmission, reduce transmission latency, and enhance Quality of Ser...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Cluster computing Ročník 28; číslo 4; s. 244
Hlavní autoři:	Zhang, Shi-Hui, Wang, Jie-Sheng, Zhang, Si-Wen, Xing, Yu-Xuan, Wang, Xiao-Tian, Sui, Xiao-Fei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.08.2025 Springer Nature B.V
Témata:	Algorithms Cloud computing Computation offloading Computer Communication Networks Computer Science Convexity Costs Data transmission Decision making Deep learning Density Dynamic programming Edge computing Energy consumption Genetic algorithms Indexing Mixed integer Multiple objective analysis Network latency Nonlinear programming Operating Systems Optimization Pareto optimization Processor Architectures Resource scheduling Scheduling Task scheduling User experience Internet of things Snake optimizer Multi-objective optimization Scheduling optimization Task uninstallation Edge computing
ISSN:	1386-7857, 1573-7543
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	The proposal of task offloading and scheduling optimization in edge computing aims to effectively alleviate network congestion caused by a large amount of data in ultra-dense networks (UDN), minimize energy consumption during data transmission, reduce transmission latency, and enhance Quality of Service (QoS). To address this issue, the Power Allocation (PA) problem for mobile users is presented, aiming to minimize energy consumption through the application of Convex Optimization Techniques. Subsequently, the Joint Request Offloading and Resource Scheduling (JRORS) problem is modeled as a mixed-integer nonlinear programming problem to minimize request response latency and enhance welfare. The JRORS problem can be further divided into two subproblems: the request offloading problem and the computational resource scheduling problem. The optimal solution is sought through mathematical modeling. A multi-objective snake optimizer based on density estimation and grid index mechanism is proposed to solve the multi-objective problem of edge computing task offloading and scheduling optimization. Firstly, applying the grid indexing mechanism transforms the single-objective snake optimizer to a multi-objective algorithm. Secondly, a roulette wheel selection method is utilized to choose the elite solutions, referred to as "Leaders". Density estimation is conducted based on the dominance capability of individuals, employing fast non-dominated sorting and density estimation for dual optimization of the archive. This approach not only yields an optimal Pareto solution set but also excludes similar individuals before the next iteration, ensuring population diversity and enhancing the effectiveness of the multi-objective snake optimizer. The proposed improved algorithm demonstrates outstanding performance across various test functions and conducts multi-objective optimization of energy consumption and efficiency for task offloading under nine different user scales. Comparative results against NSGA-II, MOPSO, MSSA, and MOALO show that MOSO effectively finds representative samples that achieve the optimal balance between energy consumption and welfare. The results further show that MOSO can maintain good performance in ultra-dense edge computing (UDEC) networks, find a set of representative samples with a wider range and better frontier between energy consumption and welfare, and complete the joint optimization between thm.
AbstractList	The proposal of task offloading and scheduling optimization in edge computing aims to effectively alleviate network congestion caused by a large amount of data in ultra-dense networks (UDN), minimize energy consumption during data transmission, reduce transmission latency, and enhance Quality of Service (QoS). To address this issue, the Power Allocation (PA) problem for mobile users is presented, aiming to minimize energy consumption through the application of Convex Optimization Techniques. Subsequently, the Joint Request Offloading and Resource Scheduling (JRORS) problem is modeled as a mixed-integer nonlinear programming problem to minimize request response latency and enhance welfare. The JRORS problem can be further divided into two subproblems: the request offloading problem and the computational resource scheduling problem. The optimal solution is sought through mathematical modeling. A multi-objective snake optimizer based on density estimation and grid index mechanism is proposed to solve the multi-objective problem of edge computing task offloading and scheduling optimization. Firstly, applying the grid indexing mechanism transforms the single-objective snake optimizer to a multi-objective algorithm. Secondly, a roulette wheel selection method is utilized to choose the elite solutions, referred to as "Leaders". Density estimation is conducted based on the dominance capability of individuals, employing fast non-dominated sorting and density estimation for dual optimization of the archive. This approach not only yields an optimal Pareto solution set but also excludes similar individuals before the next iteration, ensuring population diversity and enhancing the effectiveness of the multi-objective snake optimizer. The proposed improved algorithm demonstrates outstanding performance across various test functions and conducts multi-objective optimization of energy consumption and efficiency for task offloading under nine different user scales. Comparative results against NSGA-II, MOPSO, MSSA, and MOALO show that MOSO effectively finds representative samples that achieve the optimal balance between energy consumption and welfare. The results further show that MOSO can maintain good performance in ultra-dense edge computing (UDEC) networks, find a set of representative samples with a wider range and better frontier between energy consumption and welfare, and complete the joint optimization between thm.
ArticleNumber	244
Author	Wang, Jie-Sheng Xing, Yu-Xuan Zhang, Shi-Hui Sui, Xiao-Fei Zhang, Si-Wen Wang, Xiao-Tian
Author_xml	– sequence: 1 givenname: Shi-Hui surname: Zhang fullname: Zhang, Shi-Hui organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning – sequence: 2 givenname: Jie-Sheng surname: Wang fullname: Wang, Jie-Sheng email: wjs@ustl.edu.cn organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning – sequence: 3 givenname: Si-Wen surname: Zhang fullname: Zhang, Si-Wen organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning – sequence: 4 givenname: Yu-Xuan surname: Xing fullname: Xing, Yu-Xuan organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning – sequence: 5 givenname: Xiao-Tian surname: Wang fullname: Wang, Xiao-Tian organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning – sequence: 6 givenname: Xiao-Fei surname: Sui fullname: Sui, Xiao-Fei organization: School of Electronic and Information Engineering, University of Science and Technology Liaoning
BookMark	eNp9kctu3CAUhlGUSM3tBbpCytoNF2NMdlHUm5RoFm3WCBuYYcaGKeCm0yfJ4xbPjBSpi6zgnPN_5xz4L8CpD94A8BGjTxghfpswYm1TIVJXqBaIVOIEnGPGacVZTU_LnZYybxn_AC5SWiOEBCfiHLw-LX4s7uA4DdlVoVubPrvfBiavNgaGbXaj-2sifHF5BbXxyeUdNKmkVXbBQ-U1XEanofPa_HF-CUfTr5R3aYQ2RGj00sA-jNspz8Ws0gYGa4eg9BzPeOpXRk_DHB7n7VtfgTOrhmSuj-cleP7y-efDt-px8fX7w_1j1ZNa5Aory5ltOqs7QUnTtkqRmmOq2oZapXhbd4Z2tbBIIyaIwB0WQmjNtOZWtJhegptD320Mv6byNLkOU_RlpKSYY9ywhpGiag-qPoaUorGyd3m_Z47KDRIjOfsgDz7I4oPc-yBFQcl_6DaW74u79yF6gFIR-6WJb1u9Q_0DAH-gww
CitedBy_id	crossref_primary_10_1109_ACCESS_2025_3568297 crossref_primary_10_1051_epjconf_202532801071
Cites_doi	10.1007/s10489-022-03482-8 10.1109/TSUSC.2023.3295939 10.1109/COMST.2021.3106401 10.1007/s10586-024-04561-w 10.1016/j.knosys.2022.108320 10.1007/s11277-017-5200-5 10.3390/s21082628 10.3390/s21134527 10.1109/ACCESS.2021.3134941 10.1109/TMC.2020.2994232 10.1007/s11227-024-06315-2 10.1007/s11277-023-10318-2 10.1016/j.asoc.2023.110966 10.1007/s11276-020-02409-w 10.1109/JIOT.2019.2955311 10.1007/s10710-005-6164-x 10.1109/TNSM.2022.3163297 10.1109/ACCESS.2023.3241240 10.1016/j.future.2012.05.023 10.1109/CEC.2002.1004388 10.1016/j.jpdc.2022.09.006 10.1145/2757384.2757397 10.1109/TCE.2023.3321708 10.1109/MCE.2016.2590118 10.1109/4235.797969 10.1007/978-3-642-10665-1_63 10.1109/TEVC.2007.892759 10.1007/s10115-020-01503-x 10.1038/s41598-024-56957-8 10.1109/4235.996017 10.1109/MC.2017.9 10.3390/electronics12020366 10.1109/TVT.2020.2964821 10.1109/COMST.2017.2682318 10.1038/nature14539 10.1007/s10489-016-0825-8 10.1109/ISCC.2017.8024630 10.1109/TVT.2024.3361492 10.1109/JIOT.2022.3176631 10.1214/ss/1177011077 10.1007/s00521-023-08682-y 10.1109/TENCON.2017.8228329 10.1016/j.future.2020.03.028
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Copyright Springer Nature B.V. Aug 2025
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: Copyright Springer Nature B.V. Aug 2025
DBID	AAYXX CITATION JQ2
DOI	10.1007/s10586-024-04902-9
DatabaseName	CrossRef ProQuest Computer Science Collection
DatabaseTitle	CrossRef ProQuest Computer Science Collection
DatabaseTitleList	ProQuest Computer Science Collection
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1573-7543
ExternalDocumentID	10_1007_s10586_024_04902_9
GrantInformation_xml	– fundername: Postgraduate Education Reform Project of Liaoning Province grantid: LNYJG2022137 – fundername: Basic Scientific Research Project of Institution of Higher Learning of Liaoning Province grantid: LJ222410146054
GroupedDBID	-~C .86 .DC .VR 06D 0R~ 0VY 1N0 203 29B 2J2 2JN 2JY 2KG 2LR 2~H 30V 4.4 406 408 409 40D 40E 5GY 5VS 67Z 6NX 78A 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAJBT AAJKR AANZL AAPKM AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYZH ABAKF ABBBX ABBRH ABBXA ABDBE ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABRTQ ABSXP ABTEG ABTHY ABTKH ABTMW ABWNU ABXPI ACAOD ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACSNA ACZOJ ADHHG ADHIR ADKFA ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEFQL AEGAL AEGNC AEJHL AEJRE AEMSY AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFDZB AFLOW AFOHR AFQWF AFWTZ AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHPBZ AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARMRJ ASPBG ATHPR AVWKF AXYYD AYFIA AYJHY AZFZN B-. BA0 BGNMA BSONS CS3 CSCUP DDRTE DL5 DNIVK DPUIP EBLON EBS EIOEI ESBYG FEDTE FERAY FFXSO FIGPU FNLPD FRRFC FWDCC GGCAI GGRSB GJIRD GNWQR GQ7 GQ8 GXS HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF I09 IJ- IKXTQ IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV LAK LLZTM M4Y MA- NB0 NPVJJ NQJWS NU0 O93 O9J OAM P9O PF0 PT4 PT5 QOS R89 R9I RNS ROL RPX RSV S16 S1Z S27 S3B SAP SCO SDH SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 ZMTXR ~A9 -Y2 1SB 2P1 2VQ AAIAL AARHV AAYTO AAYXX ABQSL ABULA ACBXY ADHKG AEBTG AEKMD AFFHD AFGCZ AFKRA AGGDS AGQPQ AHSBF AJBLW ARAPS BDATZ BENPR BGLVJ CAG CCPQU CITATION COF EJD FINBP FSGXE H13 HCIFZ HZ~ IHE K7- N2Q O9- OVD PHGZM PHGZT PQGLB RNI RZC RZE RZK TEORI JQ2
ID	FETCH-LOGICAL-c249t-1af75f6bfdb932688aa24713a863faa784be3b49f0d059291b1999dd5dd7f9813
IEDL.DBID	RSV
ISICitedReferencesCount	1
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001433278600019&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1386-7857
IngestDate	Wed Nov 26 14:52:01 EST 2025 Tue Nov 18 22:42:28 EST 2025 Sat Nov 29 07:34:47 EST 2025 Sat Jul 12 02:39:38 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	4
Keywords	Internet of things Snake optimizer Multi-objective optimization Scheduling optimization Task uninstallation Edge computing
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c249t-1af75f6bfdb932688aa24713a863faa784be3b49f0d059291b1999dd5dd7f9813
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
PQID	3171165652
PQPubID	2043865
ParticipantIDs	proquest_journals_3171165652 crossref_citationtrail_10_1007_s10586_024_04902_9 crossref_primary_10_1007_s10586_024_04902_9 springer_journals_10_1007_s10586_024_04902_9
PublicationCentury	2000
PublicationDate	2025-08-01
PublicationDateYYYYMMDD	2025-08-01
PublicationDate_xml	– month: 08 year: 2025 text: 2025-08-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York – name: Dordrecht
PublicationSubtitle	The Journal of Networks, Software Tools and Applications
PublicationTitle	Cluster computing
PublicationTitleAbbrev	Cluster Comput
PublicationYear	2025
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	T Alfakih (4902_CR37) 2021; 9 4902_CR23 Y LeCun (4902_CR11) 2015; 521 L Dong (4902_CR19) 2023; 12 E Zitzler (4902_CR49) 1999; 3 Y Lu (4902_CR10) 2022; 19 JR Marden (4902_CR20) 2018; 1 M Mollajafari (4902_CR43) 2016; 32 M Mollajafari (4902_CR21) 2023; 35 Q Luo (4902_CR46) 2021; 23 MH Shojaeefard (4902_CR42) 2022; 38 FA Saif (4902_CR39) 2023; 11 AK Das (4902_CR26) 2020; 62 D Bertsimas (4902_CR16) 1993; 8 L Liao (4902_CR14) 2023; 171 M Huang (4902_CR31) 2021; 21 4902_CR18 CAC Coello (4902_CR48) 2005; 6 A Ali (4902_CR12) 2021; 21 Q Zhang (4902_CR7) 2020; 69 A Bozorgchenani (4902_CR38) 2020; 20 M Satyanarayanan (4902_CR8) 2017; 50 X Zhao (4902_CR29) 2019; 20 P Cong (4902_CR5) 2020; 53 4902_CR41 S Mirjalili (4902_CR25) 2017; 46 H Li (4902_CR45) 2023; 149 4902_CR47 P Mach (4902_CR1) 2017; 19 S Zhu (4902_CR40) 2023; 130 FA Hashim (4902_CR44) 2022; 242 S Hu (4902_CR36) 2019; 7 4902_CR30 N Fernando (4902_CR6) 2013; 29 4902_CR9 4902_CR32 4902_CR35 4902_CR34 S Xiao (4902_CR15) 2020; 109 Y Sun (4902_CR28) 2018; 102 X Zhang (4902_CR13) 2023; 53 K Deb (4902_CR22) 2002; 6 Q Zhang (4902_CR24) 2007; 11 4902_CR3 SN Hegde (4902_CR27) 2024; 14 P Shukla (4902_CR33) 2024; 80 H Liu (4902_CR17) 2022; 9 4902_CR2 D Sabella (4902_CR4) 2016; 5
References_xml	– volume: 32 start-page: 1541 issue: 6 year: 2016 ident: 4902_CR43 publication-title: J. Inf. Sci. Eng. – volume: 38 start-page: 1 issue: 1 year: 2022 ident: 4902_CR42 publication-title: Métod. Num. Cál. Dis. Ingen. Rev. Inter. – volume: 53 start-page: 1180 issue: 1 year: 2023 ident: 4902_CR13 publication-title: Appl. Intell. doi: 10.1007/s10489-022-03482-8 – ident: 4902_CR18 doi: 10.1109/TSUSC.2023.3295939 – volume: 23 start-page: 2131 issue: 4 year: 2021 ident: 4902_CR46 publication-title: IEEE. Commun. Surv. Tutor. doi: 10.1109/COMST.2021.3106401 – ident: 4902_CR35 doi: 10.1007/s10586-024-04561-w – volume: 242 year: 2022 ident: 4902_CR44 publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2022.108320 – volume: 102 start-page: 1369 year: 2018 ident: 4902_CR28 publication-title: Wireless Pers. Commun. doi: 10.1007/s11277-017-5200-5 – volume: 21 start-page: 2628 issue: 8 year: 2021 ident: 4902_CR31 publication-title: Sensors doi: 10.3390/s21082628 – volume: 21 start-page: 4527 issue: 13 year: 2021 ident: 4902_CR12 publication-title: Sensors doi: 10.3390/s21134527 – volume: 9 start-page: 167503 year: 2021 ident: 4902_CR37 publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3134941 – volume: 53 start-page: 1 issue: 2 year: 2020 ident: 4902_CR5 publication-title: ACM. Comp. Surv. (CSUR) – volume: 20 start-page: 2992 issue: 10 year: 2020 ident: 4902_CR38 publication-title: IEEE Trans. Mob. Comput. doi: 10.1109/TMC.2020.2994232 – volume: 80 start-page: 22315 issue: 15 year: 2024 ident: 4902_CR33 publication-title: J. Supercomput. doi: 10.1007/s11227-024-06315-2 – volume: 130 start-page: 1025 issue: 2 year: 2023 ident: 4902_CR40 publication-title: Wireless Pers. Commun. doi: 10.1007/s11277-023-10318-2 – volume: 149 year: 2023 ident: 4902_CR45 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2023.110966 – ident: 4902_CR30 doi: 10.1007/s11276-020-02409-w – volume: 7 start-page: 1426 issue: 2 year: 2019 ident: 4902_CR36 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2019.2955311 – volume: 1 start-page: 105 year: 2018 ident: 4902_CR20 publication-title: Ann. Rev. Cont. Robot. Auton. Syst. – volume: 6 start-page: 163 year: 2005 ident: 4902_CR48 publication-title: Genet. Program Evolvable Mach. doi: 10.1007/s10710-005-6164-x – volume: 19 start-page: 3163 issue: 3 year: 2022 ident: 4902_CR10 publication-title: IEEE Trans. Netw. Serv. Manage. doi: 10.1109/TNSM.2022.3163297 – volume: 11 start-page: 20635 year: 2023 ident: 4902_CR39 publication-title: IEEE Access doi: 10.1109/ACCESS.2023.3241240 – volume: 29 start-page: 84 issue: 1 year: 2013 ident: 4902_CR6 publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2012.05.023 – ident: 4902_CR23 doi: 10.1109/CEC.2002.1004388 – volume: 171 start-page: 28 year: 2023 ident: 4902_CR14 publication-title: J. Parall. Distrib. Comp. doi: 10.1016/j.jpdc.2022.09.006 – ident: 4902_CR3 doi: 10.1145/2757384.2757397 – ident: 4902_CR41 doi: 10.1109/TCE.2023.3321708 – volume: 5 start-page: 84 issue: 4 year: 2016 ident: 4902_CR4 publication-title: IEEE. Cons. Electron. Mag. doi: 10.1109/MCE.2016.2590118 – volume: 3 start-page: 257 issue: 4 year: 1999 ident: 4902_CR49 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.797969 – ident: 4902_CR2 doi: 10.1007/978-3-642-10665-1_63 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 4902_CR24 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2007.892759 – volume: 62 start-page: 4407 year: 2020 ident: 4902_CR26 publication-title: Knowl. Inf. Syst. doi: 10.1007/s10115-020-01503-x – volume: 14 start-page: 6521 issue: 1 year: 2024 ident: 4902_CR27 publication-title: Sci. Rep. doi: 10.1038/s41598-024-56957-8 – ident: 4902_CR47 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 4902_CR22 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – volume: 50 start-page: 30 issue: 1 year: 2017 ident: 4902_CR8 publication-title: Computer doi: 10.1109/MC.2017.9 – volume: 12 start-page: 366 issue: 2 year: 2023 ident: 4902_CR19 publication-title: Electronics doi: 10.3390/electronics12020366 – volume: 69 start-page: 3280 issue: 3 year: 2020 ident: 4902_CR7 publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2020.2964821 – volume: 19 start-page: 1628 issue: 3 year: 2017 ident: 4902_CR1 publication-title: IEEE. Commun. Surv. Tutor. doi: 10.1109/COMST.2017.2682318 – volume: 521 start-page: 436 issue: 7553 year: 2015 ident: 4902_CR11 publication-title: Nature doi: 10.1038/nature14539 – volume: 46 start-page: 79 year: 2017 ident: 4902_CR25 publication-title: Appl. Intell. doi: 10.1007/s10489-016-0825-8 – ident: 4902_CR9 doi: 10.1109/ISCC.2017.8024630 – volume: 20 start-page: 1057 issue: 4 year: 2019 ident: 4902_CR29 publication-title: J. Int. Technol. – ident: 4902_CR34 doi: 10.1109/TVT.2024.3361492 – volume: 9 start-page: 20841 issue: 21 year: 2022 ident: 4902_CR17 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2022.3176631 – volume: 8 start-page: 10 issue: 1 year: 1993 ident: 4902_CR16 publication-title: Stat. Sci. doi: 10.1214/ss/1177011077 – volume: 35 start-page: 18035 issue: 24 year: 2023 ident: 4902_CR21 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-023-08682-y – ident: 4902_CR32 doi: 10.1109/TENCON.2017.8228329 – volume: 109 start-page: 17 year: 2020 ident: 4902_CR15 publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2020.03.028
SSID	ssj0009729
Score	2.3644886
Snippet	The proposal of task offloading and scheduling optimization in edge computing aims to effectively alleviate network congestion caused by a large amount of data...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	244
SubjectTerms	Algorithms Cloud computing Computation offloading Computer Communication Networks Computer Science Convexity Costs Data transmission Decision making Deep learning Density Dynamic programming Edge computing Energy consumption Genetic algorithms Indexing Mixed integer Multiple objective analysis Network latency Nonlinear programming Operating Systems Optimization Pareto optimization Processor Architectures Resource scheduling Scheduling Task scheduling User experience
Title	MOSO: multi-objective snake optimizer with density estimation and grid indexing mechanism for edge computing task offloading and scheduling optimization
URI	https://link.springer.com/article/10.1007/s10586-024-04902-9 https://www.proquest.com/docview/3171165652
Volume	28
WOSCitedRecordID	wos001433278600019&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: SpringerLink Contemporary customDbUrl: eissn: 1573-7543 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0009729 issn: 1386-7857 databaseCode: RSV dateStart: 19980101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3JTsMwELWgcOBCWUWhIB-4QaQmaRKbG0JUHKBFFFBvkRPbqLRNUBOQ4Ev4XGachAICJDh7lbd5tt-8IWRfgpW2WYyEJ9622lrZlvAjZrUCB8xdxIRfiCSdB90uGwz4ZekUllVs9-pL0pzUH5zdPIaEWSROcNjHfJ4sgLljGLDhqn87k9oNTGwy24XcAfOC0lXm-zo-m6MZxvzyLWqsTaf-v36ukOUSXdLjYjmskjmVrJF6FbmBlht5nbxe9Pq9I2rYhFYa3RenHs0SMVI0hVNkMnyB_PhISyVS3PNninIchZ8jFYmkd9OhpEZrETpHJwo9iIfZhAIIpvhGR2PTKibmIhvRVOtxagj7pjhcqsHIoS981Z6peoPcdE6vT86sMkaDFcPFLbdsoQNP-5GWESJBxoRwwN65gvmuFiKA-VZu1Oa6JQHIOdyOUPdASk_KQHNmu5uklqSJ2iKU-UxpwCMugjTP55FwAf9p21NKx1zrBrGrqQrjUsAc42iMw5n0Mg59CEMfmqEPeYMcvJd5KOQ7fs3drFZAWG7lLASAZSSKPKdBDqsZnyX_XNv237LvkCUHYwsbcmGT1PLpo9oli_FTPsyme2aJvwGGdPdY
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bb9MwFD4aHRK8rOMyraNsfuANIjVJk9i8TYiqaL0gWlDfIie2p25tgpps0vZL-Lk7x0koIJjEnn2Vb-ez_Z3vALxRaKVdnhLhSfSdvtGuI8OEO73IQ3OXcBlWIkmjaDLhi4X4XDuFFQ3bvfmStCf1L85uASfCLBEnBO5j8Qh2-2ixSDH_y-zbVmo3srHJXB9zRzyIaleZv9fxuznaYsw_vkWttRm0H9bPfdir0SU7rZbDM9jR2XNoN5EbWL2RX8CP8XQ2fc8sm9DJk4vq1GNFJi81y_EUWS9vMT890jJFFPfyhpEcR-XnyGSm2PlmqZjVWsTOsbUmD-JlsWYIghm90bHUtkqJpSwuWW7MKreEfVscL9Vo5MgXvmnPVv0Svg4-zj8MnTpGg5Pixa10XGmiwISJUQkhQc6l9NDe-ZKHvpEywvnWftIXpqcQyHnCTUj3QKlAqcgI7voH0MryTB8C4yHXBvGITyAtCEUifcR_xg20NqkwpgNuM1VxWguYUxyNVbyVXqahj3HoYzv0sejA259lvlfyHffm7jYrIK63chEjwLISRYHXgXfNjG-T_13b0f9lP4Enw_l4FI8-Tc5ewVOP4gxbomEXWuXmSr-Gx-l1uSw2x3a53wElk_o8
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1NT9wwEB0BRYgLtFDEAgUfuEEESTaJzQ1BVyC2u0i0aG-RE9togU3QJiDRX9Kfy4yTdLcVIFU9-1P-mmf7zRuAXYVW2uUpEZ5E22kb7ToyTLhzGHlo7hIuw0okqRv1enwwEJdTXvyW7d58SVY-DaTSlJUHD8ocTDm-BZzIs0SiELinxSx8aBORnu7rV9cT2d3Ixilzfcwd8SCq3WZer-NP0zTBm399kVrL01n-_z5_hKUadbLjapl8ghmdrcByE9GB1Rt8FX5961_1j5hlGTp5cludhqzI5J1mOZ4uo-FPzE-Pt0wR9b18ZiTTUfk_MpkpdjMeKmY1GLGjbKTJs3hYjBiCY0Zvdyy1rVJiKYs7lhtzn1sivy2Ol200fuQj37Rnq_4MPzpfv5-cOXXsBifFC13puNJEgQkToxJCiJxL6aEd9CUPfSNlhOtA-0lbmEOFAM8TbkJ6CEoFSkVGcNdfg7ksz_Q6MB5ybRCn-ATeglAk0kdcaNxAa5MKY1rgNtMWp7WwOcXXuI8nksw09DEOfWyHPhYt2Ptd5qGS9Xg391azGuJ6ixcxAi8rXRR4LdhvZn-S_HZtG_-WfQcWLk87cfe8d7EJix6FH7b8wy2YK8eP-gvMp0_lsBhv25X_Av8CAy8
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=MOSO%3A+multi-objective+snake+optimizer+with+density+estimation+and+grid+indexing+mechanism+for+edge+computing+task+offloading+and+scheduling+optimization&rft.jtitle=Cluster+computing&rft.au=Zhang%2C+Shi-Hui&rft.au=Wang%2C+Jie-Sheng&rft.au=Zhang%2C+Si-Wen&rft.au=Xing%2C+Yu-Xuan&rft.date=2025-08-01&rft.pub=Springer+US&rft.issn=1386-7857&rft.eissn=1573-7543&rft.volume=28&rft.issue=4&rft_id=info:doi/10.1007%2Fs10586-024-04902-9&rft.externalDocID=10_1007_s10586_024_04902_9
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1386-7857&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1386-7857&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1386-7857&client=summon