QAFHE: A QoS-aware framework forheterogeneous and dynamic edge-to-cloud Kubernetes deployments

QAFHE: A QoS-aware framework forheterogeneous and dynamic edge-to-cloud Kubernetes deployments | 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 QAFHE: A QoS-aware framework forheterogeneous and dynamic edge-to-cloud Kubernetes deployments Julián Cámara-Miró, Luis Costero, Francisco D. Igual This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7252141/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The introduction of the edge-to-cloud continuum paradigm introduces new chal-lenges due to the heterogeneity of computing entities in deployments. Thesechallenges primarily affect the ability to maintain appropriate levels of Qualityof Service (QoS) when assigning workloads and requests to nodes, particularlyconcerning response times, as well as application-specific metrics. Moreover, inscenarios where computing elements are inherently dynamic in terms of avail-ability, computing power, or latency, efficiently assigning workloads to the mostappropriate computing element becomes an even more significant challenge. Cur-rent generic orchestrators, like Kubernetes, have shown themselves to be effectivein homogeneous and static environments, where the usual QoS-unaware schedul-ing strategies focus mainly on load balancing, neglecting aspects such as reducinglatency or constraining application-level metrics. In this study, we reveal thatgeneric orchestrators like Kubernetes fall short when QoS-agnostic policies areapplied to heterogeneous and dynamic edge-to-cloud environments. We introduceQafhe, a novel framework that integrates effortlessly into Kubernetes via a ser-vice. This framework is designed with a set of QoS-aware scheduling policies toeffectively address the heterogeneity and dynamicity found in numerous edge-to-cloud setups. Our experiments, specifically involving the deployment of inferenceservers across diverse nodes, show considerable improvements in response timesacross various dynamic scenarios involving devices with varying capabilities, suchas multi-core CPUs and diverse GPU types. Kubernetes heterogeneity edge-to-cloud inference servers dynamic workload placement Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 16 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers agreed at journal 08 Aug, 2025 Reviewers invited by journal 04 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Submission checks completed at journal 31 Jul, 2025 First submitted to journal 30 Jul, 2025 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-7252141","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495378105,"identity":"4cf213c5-a667-42ae-a544-b22288ee0c2c","order_by":0,"name":"Julián Cámara-Miró","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Julián","middleName":"","lastName":"Cámara-Miró","suffix":""},{"id":495378107,"identity":"dd5144dd-f678-4aea-b0ee-ffd27f99d148","order_by":1,"name":"Luis Costero","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"","lastName":"Costero","suffix":""},{"id":495378109,"identity":"95350314-ebf0-444a-9ca5-bbbc2a2da753","order_by":2,"name":"Francisco D. 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