A Hybrid Metaheuristic Approach for Multi-Objective Load Balancing in Digital Twin-Enabled Cloud Environment

A Hybrid Metaheuristic Approach for Multi-Objective Load Balancing in Digital Twin-Enabled Cloud Environment | 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 Hybrid Metaheuristic Approach for Multi-Objective Load Balancing in Digital Twin-Enabled Cloud Environment Anand Muni Mishra, Rahul Yadav, Prabhjot Kaur, Shubham Gargrish, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6978024/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 The rapid growth of digital twin services is pushing computational resources requirements to unprecedented levels. While cloud computing provides the scalable infrastructure needed to support these computational demands. However, the critical challenge lies in intelligently distributing workloads across distributed cloud environments through advanced load balancing techniques, where traditional deterministic approaches struggle to find optimal solutions within polynomial time. Therefore, addressing such challenges this paper proposes an efficient service placement approach based on Modified Cuckoo Search Optimization called CSOT-PM to optimize dynamic resource allocation in cloud computing which supporting digital twin services. The proposed work is benchmarked against established algorithms like the Genetic Algorithm (GA) and Ant Colony Optimization (ACO), using performance metrics such as makespan time, resource utilization, energy consumption, and Service Level Agreement (SLA) violations. The proposed algorithm achieves a 30% reduction in energy consumption and an 11% improvement in SLA. Load Balancing Clustering Algorithm Cuckoo Search Resource Management Cloud Computing 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. 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-6978024","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483249760,"identity":"5d89b647-de39-43dc-9983-c7ec574b1dc2","order_by":0,"name":"Anand Muni Mishra","email":"","orcid":"","institution":"Chandigarh Engineering College, Chandigarh Group of Colleges","correspondingAuthor":false,"prefix":"","firstName":"Anand","middleName":"Muni","lastName":"Mishra","suffix":""},{"id":483249761,"identity":"ca1cc81c-db22-4aa6-a545-42caf02b3a7c","order_by":1,"name":"Rahul 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