Research and optimization of task schedulingalgorithm based on heterogeneous multi-coreprocessor

Research and optimization of task schedulingalgorithm based on heterogeneous multi-coreprocessor | 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 Research and optimization of task schedulingalgorithm based on heterogeneous multi-coreprocessor Junnan Liu, Yifan Liu, Yongkang Ding This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3848642/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Heterogeneous multi-core processor has the ability to switch between differenttypes of cores to perform tasks, which provides more space and possibility forrealizing efficient operation of computer system and improving computer computing power. Current research focuses on heterogeneous multiprocessor systemswith high performance or low power consumption to reduce system energy consumption. However, some studies have shown that excessive voltage reductionmay lead to an increase in transient failure rates, reducing system reliability. Inorder to solve this problem, this paper studies the energy optimal schedulingproblem of HMSS with DVFS under the constraints of minimum time and reliability, and proposes an improved wild horse optimization algorithm (OIWHO),which improves the efficiency of heterogeneous task scheduling and shortens thetask completion time. The algorithm uses the learning and chaos perturbationstrategies based on opposition and crossover strategies to balance the search andutilization capabilities, and can further improve the performance of OIWHO.Compared with previous work, our proposed algorithm has more advantagesthan existing algorithms. Experimental results show that the average computingtime of OIWHO algorithm is 13.38%, 10.90%, 6.97%, 2.39% and 3.21% fasterthan QHA, PSO, GWO, LFD and OIWOA, respectively. Especially when solvinglarge-scale problems, our algorithm takes less time than other algorithms. Distributed computing heterogeneous multi-core processors high performance computing task scheduling swarm intelligence optimization algorithms Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 02 Feb, 2024 Reviews received at journal 16 Jan, 2024 Reviewers agreed at journal 10 Jan, 2024 Reviewers invited by journal 10 Jan, 2024 Editor assigned by journal 10 Jan, 2024 Submission checks completed at journal 10 Jan, 2024 First submitted to journal 09 Jan, 2024 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3848642","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":266410063,"identity":"255bb6cf-edcf-40de-9b95-35cb0ec8732f","order_by":0,"name":"Junnan Liu","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Junnan","middleName":"","lastName":"Liu","suffix":""},{"id":266410064,"identity":"0d9540ca-c01e-44ad-bee7-5e2e9a2b1a1c","order_by":1,"name":"Yifan Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACef7G5gcfKtjk2OQfHyBOi+GMw8cMZ5zhM+ZnSEsg0poDaQnSvG1yiTMbcgyI08HYcMbAcAabmbHBgTMfb7xhsJPTbSCghZ25x+DBB540OYODvZst5zAkG5sdIMoWiWPGBod5t0nzMBxI3EZIC8OBHANpHoP/iRuO8TwjVgvQ+zwJbIkze3jYiNMCCeQDbMb8EmzGlnMMiPALOCo//gNGpQTzwxtvKuzkCGpBARI8REYNshZSdYyCUTAKRsGIAAD9b0VSA9ubywAAAABJRU5ErkJggg==","orcid":"","institution":"Henan University","correspondingAuthor":true,"prefix":"","firstName":"Yifan","middleName":"","lastName":"Liu","suffix":""},{"id":266410065,"identity":"12b1518d-6005-4cc8-a703-ac0ab5d5155a","order_by":2,"name":"Yongkang Ding","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Yongkang","middleName":"","lastName":"Ding","suffix":""}],"badges":[],"createdAt":"2024-01-09 15:29:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3848642/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3848642/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49473636,"identity":"5c92a8e0-d3ab-4e4f-8008-cf1ef9771113","added_by":"auto","created_at":"2024-01-11 12:44:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3570245,"visible":true,"origin":"","legend":"","description":"","filename":"Researchandoptimizationoftaskschedulingalgorithmbasedonheterogeneousmulticoreprocessor.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3848642/v1_covered_c9dde80b-847b-49b0-a8d0-273fb4a2218e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research and optimization of task schedulingalgorithm based on heterogeneous multi-coreprocessor","fulltext":[],"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":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cluster-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Cluster Computing](https://www.springer.com/journal/10586)","snPcode":"10586","submissionUrl":"https://submission.nature.com/new-submission/10586/3","title":"Cluster Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Distributed computing, heterogeneous multi-core processors, high performance computing, task scheduling, swarm intelligence optimization algorithms","lastPublishedDoi":"10.21203/rs.3.rs-3848642/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3848642/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeterogeneous multi-core processor has the ability to switch between differenttypes of cores to perform tasks, which provides more space and possibility forrealizing efficient operation of computer system and improving computer computing power. 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