A Self-Adaptive Detoxify Particle Swarm Optimization Algorithm for Optimal Route Detection in Software Defined Wide Area Network

A Self-Adaptive Detoxify Particle Swarm Optimization Algorithm for Optimal Route Detection in Software Defined Wide Area 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 A Self-Adaptive Detoxify Particle Swarm Optimization Algorithm for Optimal Route Detection in Software Defined Wide Area Network Kwame Opuni-Boachie Obour Agyekum, Oyedum John Davis Chukwuemeka, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7955755/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 significant reliance on data in enterprise networks requires efficient routing of user data. Traditional WANs use routing techniques like MPLS and DSL, but they only provide data forwarding services and limit network scalability. SDN addresses these issues by decoupling control and data planes, offering network automation, scalability, and policy-driven management. The adoption of gradient-based ML algorithms in SDN improves data routing. However, the complexity of deployment and potential drawbacks of gradient-based algorithms led to the development of less complex, more adaptive gradient-free Nature Inspired Algorithms (NIAs). Though NIAs like PSO and ACO are easier to implement, they have limitations such as premature convergence and increased processing delay. Hence, this research proposes a Self-Adaptive Particle Swarm Optimization (SAPSO) algorithm for optimal route detection in a scalable SDWAN. This approach tracks convergence, uses a flow entry algorithm, and encourages global search with a detoxify swarm function to find the optimal route in a scalable space. Software-defined Networking (SDN) Particle Swarm Optimization (PSO) computer networks routing 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-7955755","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":541126432,"identity":"0cada776-9b40-4344-b048-9bd9b52c9af4","order_by":0,"name":"Kwame Opuni-Boachie Obour 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