A novel multi-application offloading method formobile intelligent vehicles in a cloud-edge hybridenvironment

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Abstract

With the increasing demand for real-time computing services in the Internet ofVehicles(IoV) and the inability to meet the latency requirements of IoVapplications by using cloud computing, multi-access edge computing(MEC) isconsidered a promising paradigm to address the latency-sensitive andcomputation-intensive requirements for meeting IoV applications. We considerthe dependencies in IoV applications and design a hybrid cloud-edge architectureto ensure adaptability and flexibility. We propose a scheduling algorithm thatoffloads tasks to the eNode or cloud for execution after sorting them by urgency.Experimental results show that our algorithm outperforms existing algorithms interms of average completion time, average waiting time, and in-time completionrate of the application, which can provide a better quality of service(QoS) for IoV.
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A novel multi-application offloading method formobile intelligent vehicles in a cloud-edge hybridenvironment | 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 A novel multi-application offloading method formobile intelligent vehicles in a cloud-edge hybridenvironment Xifeng Xu, Yunni Xia, Feng Zeng, Fan Li, Hong Xie, Xiaodong Fu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1910542/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 With the increasing demand for real-time computing services in the Internet ofVehicles(IoV) and the inability to meet the latency requirements of IoVapplications by using cloud computing, multi-access edge computing(MEC) isconsidered a promising paradigm to address the latency-sensitive andcomputation-intensive requirements for meeting IoV applications. We considerthe dependencies in IoV applications and design a hybrid cloud-edge architectureto ensure adaptability and flexibility. We propose a scheduling algorithm thatoffloads tasks to the eNode or cloud for execution after sorting them by urgency.Experimental results show that our algorithm outperforms existing algorithms interms of average completion time, average waiting time, and in-time completionrate of the application, which can provide a better quality of service(QoS) for IoV. Internet of Vehicles Mutli-access edge computing Task scheduling Quality of service Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 23 Sep, 2022 Reviews received at journal 22 Aug, 2022 Reviewers agreed at journal 10 Aug, 2022 Reviewers invited by journal 06 Aug, 2022 Editor assigned by journal 02 Aug, 2022 Submission checks completed at journal 01 Aug, 2022 First submitted to journal 29 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. 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-1910542","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":125635444,"identity":"f3d971e9-0d4b-4032-9c41-858eb20383b1","order_by":0,"name":"Xifeng Xu","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xifeng","middleName":"","lastName":"Xu","suffix":""},{"id":125635447,"identity":"7075c57c-ab9f-4bf1-9333-02d89d7a6501","order_by":1,"name":"Yunni 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