PCP-ACO: a deadline-constrained workflow scheduling algorithm for cloud environment

PCP-ACO: a deadline-constrained workflow scheduling algorithm for cloud environment | 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 PCP-ACO: a deadline-constrained workflow scheduling algorithm for cloud environment Peyman Shobeiri, Mehdi Akbarian Rastaghi, Saeid Abrishami, Behnam Shobiri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2357522/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A cloud computing environment is the most popular choice for workflow execution, as it gives customers on-demand access to computing resources. However, in cloud workflow scheduling, cloud-native requirements regarding QoS requirements such as monetary cost and execution time should be taken into account. This paper proposes PCP-ACO, a list scheduling algorithm for minimizing the execution cost of a workflow, while meeting its user-defined deadline in cloud environments. In PCP-ACO, first a topological sort of the workflow tasks is computed to assign a priority to each task. Then, Ant Colony Optimization (ACO) meta-heuristic is used to assign a proper resource to each task of the workflow, in order of their priorities. The Partial Critical Path (PCP) concept is also used as a heuristic to guide ACO algorithm. Several experiments are conducted using real scientific workflows, and the cost saving is compared with PSO and IC-PCP algorithms. The experimental results show that the proposed algorithm outperforms other compared algorithms in terms of cost saving. deadline-constrained workflow scheduling cloud computing resource allocation Ant Colony Optimization Partial Critical Paths Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-2357522","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":159445888,"identity":"f4326ba4-b182-48bf-bed7-df1c6e5013b5","order_by":0,"name":"Peyman Shobeiri","email":"","orcid":"","institution":"Islamic Azad University, Mashhad","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peyman","middleName":"","lastName":"Shobeiri","suffix":""},{"id":159445890,"identity":"3a30c392-0f7d-4088-8c75-09890a08cfc7","order_by":1,"name":"Mehdi Akbarian Rastaghi","email":"","orcid":"","institution":"University of Alberta","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mehdi","middleName":"Akbarian","lastName":"Rastaghi","suffix":""},{"id":159445892,"identity":"f271d1df-4ea7-4ea8-be0d-f89d594538d5","order_by":2,"name":"Saeid Abrishami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYHACNgYGA4YEBgbGxgcQAcYGorU0G5CghQGkhYFNgihXyTcwP3tcUVCXxz/tcFs1bw6DPH8Dc9sHfFoMDrCZG54xOFwscTux7TbvNgbDGQcYm2fg1SL/wEyyweBAYgNUC+MGoKcIOIz9G1BLXeJ8oJZioBZ7gloYDvCAbGFO3ADUwgzUkkhQi8EBnnLDBoPDiRtvJzZLzt0mkTzjMGGHbXvY8Kcucd7t9Icf3m6zse1vb3+M32FoABg1zCRpGAWjYBSMglGADQAAt6NGGrg3bxMAAAAASUVORK5CYII=","orcid":"","institution":"Ferdowsi University of Mashhad","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Saeid","middleName":"","lastName":"Abrishami","suffix":""},{"id":159445893,"identity":"4dbf2a53-e0a2-4c70-be13-8ba0664d8eb9","order_by":3,"name":"Behnam Shobiri","email":"","orcid":"","institution":"Concordia University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Behnam","middleName":"","lastName":"Shobiri","suffix":""}],"badges":[],"createdAt":"2022-12-08 10:59:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2357522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2357522/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":41557477,"identity":"b2451864-b739-4bb9-bc86-ef750fd86398","added_by":"auto","created_at":"2023-08-14 23:37:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":712300,"visible":true,"origin":"","legend":"","description":"","filename":"PCPACOSupercomputing.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2357522/v1_covered_4c646d6a-4c30-45cf-8d07-bc874c009dd4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PCP-ACO: a deadline-constrained workflow scheduling algorithm for cloud environment","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"deadline-constrained workflow scheduling, cloud computing, resource allocation, Ant Colony Optimization, Partial Critical Paths","lastPublishedDoi":"10.21203/rs.3.rs-2357522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2357522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"A cloud computing environment is the most popular choice for workflow execution, as it gives customers on-demand access to computing resources. 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