FogForge: Revolutionizing Waste Management Through Fault-Tolerant Cuckoo Search in Fog-Cloud IoT Systems

FogForge: Revolutionizing Waste Management Through Fault-Tolerant Cuckoo Search in Fog-Cloud IoT Systems | 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 FogForge: Revolutionizing Waste Management Through Fault-Tolerant Cuckoo Search in Fog-Cloud IoT Systems Sathish Kumar M, Gokulnath C, Rajmohan R, Saran Raj Sowrirajan, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5590996/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 In today's technological landscape, fog computing serves as a vital link, bridging edge devices with traditional cloud infrastructures. “Fog computing provides considerable benefits over cloud computing, in particular at reducing latency, delays and increasing fault tolerance”. By harnessing computational resources near the network edge, fog computing effectively mitigates latency challenges inherent in cloud-based architectures, while simultaneously bolstering fault tolerance mechanisms. The primary objectives is to optimize fog computing systems by reducing latency and assuring efficient error handling, which is vital to reliable and quick system functioning. Additionally, the study introduces novel enhancements to fault tolerance through the integration of queueing-based cuckoo search algorithms, thus optimizing system reliability. The paper's contributions extend to practical applications, notably in the realm of smart waste management, where fog computing demonstrates significant efficacy. Leveraging empirical analysis conducted using the iFogSim simulator, the study presents compelling outcomes, including a substantial 47.33% reduction in latency. Furthermore, fault tolerance sees notable improvements, evidenced by a reduced Fault Occurrence Frequency of 6 incidents per hour and a shortened Fault Recovery Time of 3 minutes and 20 seconds. These findings underscore the transformative potential of fog computing in revolutionizing the efficiency and reliability of IoT applications. The future direction implies the real-world implementation of the smart waste management and implementing over the geographically distributed. Fog computing Fault tolerance Latency Queuing theory based cuckoo search Smart waste management 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. 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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-5590996","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449795303,"identity":"90f74fe7-f31e-45ef-8c2b-cadef1ac378f","order_by":0,"name":"Sathish Kumar M","email":"","orcid":"","institution":"Hindustan Institute of Technology and Science","correspondingAuthor":false,"prefix":"","firstName":"Sathish","middleName":"Kumar","lastName":"M","suffix":""},{"id":449795305,"identity":"29803c5a-d356-4752-a632-37eb54f33b38","order_by":1,"name":"Gokulnath C","email":"","orcid":"","institution":"SRM Institute of Science and 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