{"paper_id":"2a565ba6-2cd8-4fbd-bd92-14234729660f","body_text":"A Container Optimal Matching Deployment Algorithm based on CN-Graph for Mobile Edge Computing | 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 Container Optimal Matching Deployment Algorithm based on CN-Graph for Mobile Edge Computing Huanle Rao, Sheng Chen, Yuxuan Du, Xiaobin Xu, Haodong Chen, Gangyong Jia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4169429/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 17 You are reading this latest preprint version Abstract The deployment of increasingly diverse services on edge devices is becoming increasingly prevalent. Efficiently deploying functionally heterogeneous services to resource heterogeneous edge nodes while achieving superior user experience is a challenge that every edge system must address. In this paper, we propose a Container-Node Graph (CN-Graph) based container optimal matching deployment algorithm, Edge Kuhn-Munkres Algorithm (EKM) Based on Container-Node Graph, designed for heterogeneous environment to optimize systemperformance. Initially, containers are categorized by functional labels, followed by construction of a CN-Graph model based on the relationship between containers and nodes. Finally, the container deployment problem is transformed into a weighted bipartite graph optimal matching problem. In comparison with the mainstream container deployment algorithms, Swarm, Kubernetes, and the recently emerged ECSched-dp algorithm, the EKM algorithm demonstrates the ability to effectively enhance the average runtime performance of containers to 3.74 times, 4.10 times, and 2.39 times, respectively. Container Deployment Edge Services Heterogeneous Clusters Performance Optimization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Jul, 2024 Reviews received at journal 20 Jul, 2024 Reviews received at journal 18 Jul, 2024 Reviews received at journal 16 Jul, 2024 Reviews received at journal 12 Jul, 2024 Reviewers agreed at journal 03 Jul, 2024 Reviewers agreed at journal 02 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviewers agreed at journal 30 Jun, 2024 Reviewers agreed at journal 30 Jun, 2024 Reviewers agreed at journal 27 Jun, 2024 Reviewers invited by journal 27 Jun, 2024 Editor assigned by journal 26 Mar, 2024 Submission checks completed at journal 26 Mar, 2024 First submitted to journal 26 Mar, 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-4169429\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":284328542,\"identity\":\"b5382068-b5b5-41e3-88a6-db6b693b453d\",\"order_by\":0,\"name\":\"Huanle Rao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hangzhou Dianzi University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Huanle\",\"middleName\":\"\",\"lastName\":\"Rao\",\"suffix\":\"\"},{\"id\":284328543,\"identity\":\"cd1c80ac-c757-4528-83ac-218a0336c0de\",\"order_by\":1,\"name\":\"Sheng 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