Integrating Quantum Network Optimization into Queueing and Scheduling Models for Cloud Computing Environments

Integrating Quantum Network Optimization into Queueing and Scheduling Models for Cloud Computing Environments | 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 Integrating Quantum Network Optimization into Queueing and Scheduling Models for Cloud Computing Environments Dinesh Kumar Nishad, Raj Sinha, Vandna Rani Verma, Sandeep Gupta This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6778588/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 Integrating quantum network optimization with traditional cloud computing presents a groundbreaking approach to enhancing computational efficiency and resource management. This study investigates the quantifiable impact of quantum-classical hybrid systems in cloud environments, focusing on resource utilization enhancement and task scheduling optimization. Using a MATLAB-based simulation environment interfaced with Variational Quantum Eigensolver (VQE) simulations, this research implements a three-layer architecture across 50 nodes, combining quantum optimization algorithms with classical scheduling techniques through a GPS queue model. The hybrid quantum-classical framework achieves remarkable improvements, including a 180% increase in task throughput, 70% reduction in response time, 41.5% improvement in resource utilization, and 27.1% enhancement in energy efficiency while maintaining 85% efficiency under peak load conditions and demonstrating 99.5% success rate for short-term tasks and 97.8% for long-running operations. Despite hardware limitations of existing quantum processors and scalability constraints, the system establishes a foundation for future developments, including advanced error correction mechanisms, expanded system scalability beyond 50 nodes, and enhanced resource utilization. These findings establish quantum-enhanced cloud computing as a viable solution for next-generation cloud infrastructure, particularly in managing complex workloads and optimizing resource allocation. Quantum computing cloud computing resource optimization hybrid systems queueing theory scheduling algorithms 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. 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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-6778588","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473013606,"identity":"7eebd075-d57a-4811-b1a7-955448942e29","order_by":0,"name":"Dinesh Kumar Nishad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIie3PsUrEMBjA8S8EMiW9tUc97wmEQqEIB+2rtBTq4uImeHABIZPerCg+RnFMCdwtKa4dXFyclYODLocpwp1DWx0d8idLyPcjCYDN9h/TABJxMAsAwyU+nJBfCWmJ/iOBPUEC980dcnRVls1zNOHT63Jz8TSLTx5u312YR+B4vJOMq2WimM4CTkjm3RdnafG6Dl1YZUCOZCfxX6ivzHtSTmiIWaGSsM6JC0QCcZNeUjZiYchoi9mjir/JboBUN75kQrW3EMy4QkVLkOgnY619xcTa/CUPPLoyf6lzfJouM9pHHH0efDbiasKxetvQ+ax9GKo/ttHx9K6b7Ivlz50ZpsPzNpvNZhvqC1MUWoahWEyIAAAAAElFTkSuQmCC","orcid":"","institution":"Dr. Shakuntala Misra National Rehabilitation University","correspondingAuthor":true,"prefix":"","firstName":"Dinesh","middleName":"Kumar","lastName":"Nishad","suffix":""},{"id":473013607,"identity":"8bff037d-982e-41f1-80ed-689e18032a15","order_by":1,"name":"Raj Sinha","email":"","orcid":"","institution":"Parul University","correspondingAuthor":false,"prefix":"","firstName":"Raj","middleName":"","lastName":"Sinha","suffix":""},{"id":473013609,"identity":"e36aef80-e838-44a7-9c3a-ff4125c96098","order_by":2,"name":"Vandna Rani Verma","email":"","orcid":"","institution":"Golgotias College of Engineering Greater Noida","correspondingAuthor":false,"prefix":"","firstName":"Vandna","middleName":"Rani","lastName":"Verma","suffix":""},{"id":473013611,"identity":"c44ef7a5-c9e5-43a4-baa2-bce0bdeaacf3","order_by":3,"name":"Sandeep Gupta","email":"","orcid":"","institution":"Graphic Era (Deemed to Be University)","correspondingAuthor":false,"prefix":"","firstName":"Sandeep","middleName":"","lastName":"Gupta","suffix":""}],"badges":[],"createdAt":"2025-05-29 17:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6778588/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6778588/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92451847,"identity":"f385ef93-324f-4104-ad26-e1d42523d16d","added_by":"auto","created_at":"2025-09-30 00:16:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5337107,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchPaperCloudComputing1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6778588/v1_covered_c3a7b62a-4b85-4650-be06-97f7e2fbe421.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating Quantum Network Optimization into Queueing and Scheduling Models for Cloud Computing Environments","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":"Quantum computing, cloud computing, resource optimization, hybrid systems, queueing theory, scheduling algorithms","lastPublishedDoi":"10.21203/rs.3.rs-6778588/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6778588/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntegrating quantum network optimization with traditional cloud computing presents a groundbreaking approach to enhancing computational efficiency and resource management. This study investigates the quantifiable impact of quantum-classical hybrid systems in cloud environments, focusing on resource utilization enhancement and task scheduling optimization. Using a MATLAB-based simulation environment interfaced with Variational Quantum Eigensolver (VQE) simulations, this research implements a three-layer architecture across 50 nodes, combining quantum optimization algorithms with classical scheduling techniques through a GPS queue model. The hybrid quantum-classical framework achieves remarkable improvements, including a 180% increase in task throughput, 70% reduction in response time, 41.5% improvement in resource utilization, and 27.1% enhancement in energy efficiency while maintaining 85% efficiency under peak load conditions and demonstrating 99.5% success rate for short-term tasks and 97.8% for long-running operations. 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