Golden Jackal-Based Intelligent Routing Optimization Framework for QoS- Aware SDN-Enabled IoT Networks

Golden Jackal-Based Intelligent Routing Optimization Framework for QoS- Aware SDN-Enabled IoT Networks | 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 Golden Jackal-Based Intelligent Routing Optimization Framework for QoS- Aware SDN-Enabled IoT Networks Nidhi Bajpai, Madhavi Dhingra, Nisha Chaurasia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7297329/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 fast pace of Internet of Things (IoT) development has resulted in ever-increasing complicated network configurations which require very high Quality-of-Service (QoS) requirements with low latency, high throughput, and dependable data delivery requirements. Such dynamic environments usually underperform when using standard routing methods, particularly when dealing with distributed computing on the edge, fog, and cloud layers. In addition, the independent treatment routing solution and the locations of Software-Defined Network (SDN) controllers poses poor performance outcomes, higher latencies and resource wastages. This paper seeks to overcome these problems by introducing a new routing-oriented optimization technique of SDN enabled IoT, wherein intelligent routing direction will be accomplished using Golden Jackal Optimization (GJO). Based on the observations of golden jackals with their interaction in cooperative hunting process, the GJO algorithm is introduced to provide rapid convergence and strong exploration of solution space globally. The framework given has the attributes of parallel optimization of both the routes and controllers’ location, thus being more scalable and with lesser control overheads. The solution based on the GJO has the QoS-based goal namely minimized end to end latencies and packet drops, achieves network load balancing, and anticipates congestion. For finding performance of the network use a novel hybrid model can be created by integrating Capsule Network (CapsNet) with a Deep Belief Network (DBN). Simulated experiments show that our model is much better than the classical and learning-based routing strategies in throughput, delay, and flexibility to adapt to the changing IoT-based network scenarios. The suggested approach meets a low latency of 0.23, high throughput of 0.92, and low packet loss of 0.18 and also meets efficient load balancing with a score of 0.83, showing that it is very efficient and reliable in handling IoT network traffic. Software-Defined Networking Internet of Things Golden Jackal Optimization Routing Optimization Quality of Service Load Balancing 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-7297329","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510390769,"identity":"224b72bd-9156-453d-8949-d5718c513594","order_by":0,"name":"Nidhi Bajpai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIie2RvWrDMBRGrxHEi6Gr+xZ3kjEY5UG6WAiSqdCpHRroLYF26QPkJbqajCqCdjH1augS0RfwWsjQm6Qd/TMWqrPoQ9yjT0IAgcBfRIAETbxARNBhwVvRvZ2sRJurxUGhYQVY4fNPetK5YxhUslhUO79VcRY7ggQb9fzouGVVXPQp+Xp2g7o2In/i66X4Yapas/K6uKQeBV0iU/0gBFpWkBXJwUbkxpQ7gY0nKPHdSA5TFCew5RaLVsl2tGV2ner6TeQbTy+EppQtt5RDb2lcdf61vTXZ2dJ/7vdqLpul33Wrolf5xSCcvkMfJ8uR8QMKf8J8wnAgEAj8M74Bhzxk1tlZ0rAAAAAASUVORK5CYII=","orcid":"","institution":"Amity University","correspondingAuthor":true,"prefix":"","firstName":"Nidhi","middleName":"","lastName":"Bajpai","suffix":""},{"id":510390770,"identity":"26616fb8-8c86-492c-bffc-9111a27a6727","order_by":1,"name":"Madhavi Dhingra","email":"","orcid":"","institution":"Amity University","correspondingAuthor":false,"prefix":"","firstName":"Madhavi","middleName":"","lastName":"Dhingra","suffix":""},{"id":510390771,"identity":"ea681801-4bf7-4e97-9e98-a820cbca3e41","order_by":2,"name":"Nisha Chaurasia","email":"","orcid":"","institution":"Dr. B. 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