Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization Method

Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization Method | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization Method Kuanishbay Sadatdiynov, Laizhong Cui, Joshua Zhexue Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1824328/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract The rapid development of IoT-based services has resulted in an exponen- tial increase in the number of connected smart mobile devices (SMDs). Processing the massive data generated by the large number of SMDs is becoming a big problem for mobile devices, servers, and wireless com- munication channels. A Multi-access Edge Computing (MEC) paradigm partially mitigates this problem by deploying edge server nodes at the edge of wireless networks nearby SMDs, but the challenge still remains due to the limited computation capacity of MEC servers and the band- width of wireless channels. In addition, the dependency of tasks generated by applications on SMDs increases the complexity of the problem. In this paper, we propose a constrained multiobjective computation offload- ing optimization solution to resolve the problem of task dependency under limited resources. This solution improves the Quality of Ser- vice (QoS) through minimizing the latency, energy consumption, and rate of task failure caused by limited resources. We propose a two- staged hybrid computation offloading optimization method to solve the problem. In the first stage, the computation offloading decisions are made based on the preferences of tasks. Then, in the second stage, global optimal solutions are found using the modified Non-Dominated Sorting Genetic Algorithm (NSGA-III). The overall efficiency of the proposed method is increased owing to the preference-based algorithm reinforcing the NSGA-III algorithm by generating a better initial population. The results of extensive experiments show that the efficiency of the proposed method is significantly better than the existing methods. Multi-access Edge Computing computation offloading optimization latency energy consumption and task failure Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 04 Oct, 2022 Reviews received at journal 20 Sep, 2022 Reviewers agreed at journal 20 Sep, 2022 Reviews received at journal 14 Sep, 2022 Reviewers agreed at journal 30 Aug, 2022 Reviewers invited by journal 30 Aug, 2022 Editor assigned by journal 29 Aug, 2022 Submission checks completed at journal 07 Jul, 2022 First submitted to journal 04 Jul, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1824328","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":119384261,"identity":"7da4db9c-a9a2-4178-8902-707d934c5e3b","order_by":0,"name":"Kuanishbay Sadatdiynov","email":"","orcid":"","institution":"Shenzhen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kuanishbay","middleName":"","lastName":"Sadatdiynov","suffix":""},{"id":119384262,"identity":"7cebec89-5ea4-430b-b323-907a72a9fa44","order_by":1,"name":"Laizhong Cui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYFACxsYDDBUQpgSxWhoOMJwhTQsDwwHGNlK08M9Ibjj4c16dvcEB5oO3eRjs8ghqkbiR2HBActthZoMDbMnWPAzJxQS1GEgAtRhuO8BmcIDHTJqH4UBiA1FaEufU8Rgc4P9GgpaDDcwSQFvYiNMiceZhw8GGY4cNJA+zGVvOMUgmrIW/Pf3hwx81dfZ8x5sf3nhTYUdYCwIwg91JvPpRMApGwSgYBXgAAPVQOvl+YvDlAAAAAElFTkSuQmCC","orcid":"","institution":"Shenzhen University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Laizhong","middleName":"","lastName":"Cui","suffix":""},{"id":119384263,"identity":"99a7127d-0838-4e73-9b98-51dc60d3123f","order_by":2,"name":"Joshua Zhexue Huang","email":"","orcid":"","institution":"Shenzhen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"Zhexue","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2022-07-04 14:59:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1824328/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1824328/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23912371,"identity":"798dac44-7f8e-4273-bff0-bfd51fd1dfbf","added_by":"auto","created_at":"2022-07-15 17:04:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1055683,"visible":true,"origin":"","legend":"","description":"","filename":"Paper3SpringerLaTeXTemplate1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1824328/v1_covered.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Offloading Dependent Tasks in MEC-enabled IoT Systems: A Preference-based Hybrid Optimization Method","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1824328/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"peer-to-peer-networking-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ppna","sideBox":"Learn more about [Peer-to-Peer Networking and Applications](http://link.springer.com/journal/12083)","snPcode":"12083","submissionUrl":"https://submission.nature.com/new-submission/12083/3","title":"Peer-to-Peer Networking and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multi-access Edge Computing, computation offloading optimization, latency, energy consumption, and task failure","lastPublishedDoi":"10.21203/rs.3.rs-1824328/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1824328/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe rapid development of IoT-based services has resulted in an exponen- tial increase in the number of connected smart mobile devices (SMDs). 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