Efficient Resource Allocation Algorithm for Maximizing Operator Profit in 5G Edge Computing network

Efficient Resource Allocation Algorithm for Maximizing Operator Profit in 5G Edge Computing network | 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 Efficient Resource Allocation Algorithm for Maximizing Operator Profit in 5G Edge Computing network Jing Liu, yuting huang, Chunhua Deng, Longxin Zhang, Cen Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4839448/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Jan, 2025 Read the published version in Journal of Grid Computing → Version 1 posted 12 You are reading this latest preprint version Abstract Resource allocation in edge computing is a research hotspot and difficulty in academia and Industry. The nature like urgency and the priority of tasks are not taken into account, which is adverse to obtain a good solution. Meanwhile, 5G has the characteristics of higher network speed, high reliability, low latency, and low-power massive connections. In this article, we present a novel algorithm to solve the multi-objective resource allocation problem in 5G edge computing (EC) network, aiming to maximize the operator profit and minimize the total completion time of tasks with priorities from the perspective of service operators under time and workload constraints. The algorithm is based on the beluga whale optimization algorithm, and it utilizes three methods to update the positions of beluga whales by swimming, predating, and migrating. In addition, to enhance the ability to escape from local optima during searching the best beluga whale position, it uses centroid information to improve the process of searching the optimal position, and adds the mutation operation in the process of position updating. Simulated results show that the proposed algorithm is high efficient in terms of reducing total task completion time and improving the revenue for operators, compared with existing strategies. Edge computing Edge computing multi-objective optimization revenue maximization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Jan, 2025 Read the published version in Journal of Grid Computing → Version 1 posted Editorial decision: Revision requested 25 Sep, 2024 Reviews received at journal 23 Sep, 2024 Reviews received at journal 20 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviews received at journal 31 Aug, 2024 Reviewers agreed at journal 27 Aug, 2024 Reviewers agreed at journal 27 Aug, 2024 Reviewers agreed at journal 27 Aug, 2024 Reviewers invited by journal 27 Aug, 2024 Editor assigned by journal 27 Aug, 2024 Submission checks completed at journal 19 Aug, 2024 First submitted to journal 01 Aug, 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. 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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-4839448","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":354706927,"identity":"1c26b0cd-b731-418a-868e-2e2317faba7d","order_by":0,"name":"Jing 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